[med-svn] [roadtrips] 01/02: Imported Upstream version 2.0+dfsg
Andreas Tille
tille at debian.org
Fri Nov 20 14:53:04 UTC 2015
This is an automated email from the git hooks/post-receive script.
tille pushed a commit to branch master
in repository roadtrips.
commit 7710d8a0b8b84654243065736383e77435ec27bc
Author: Andreas Tille <tille at debian.org>
Date: Fri Nov 20 15:21:36 2015 +0100
Imported Upstream version 2.0+dfsg
---
Changelog.html | 37 +
Makefile | 28 +
ROADTRIPS_SOURCE.c | 5587 ++++++
ROADTRIPStest.out.ex | 39271 ++++++++++++++++++++++++++++++++++++++++++
ROADTRIPStest.pvalues.ex | 1001 ++
ROADTRIPStest.testvalues.ex | 1001 ++
ROADTRIPStest.top.ex | 80 +
cholesky.c | 75 +
genofile | 1000 ++
gpl.txt | 674 +
kinfile | 2720 +++
nrutil.c | 614 +
nrutil.h | 104 +
phenofile | 320 +
pnorms2.c | 207 +
prevalence | 1 +
16 files changed, 52720 insertions(+)
diff --git a/Changelog.html b/Changelog.html
new file mode 100644
index 0000000..d6b8a56
--- /dev/null
+++ b/Changelog.html
@@ -0,0 +1,37 @@
+<html>
+
+<head>
+<link rel="stylesheet" type="text/css" href="mystyle.css">
+<title>Changes to ROADTRIPS 2.0</title>
+</head>
+
+<body>
+
+<h2 style = "text-align: center">
+Changes to ROADTRIPS 2.0
+</h2>
+
+<p style = "text-align: center">
+Monday, August 20, 2012
+</p>
+
+<p style = "text-align: justify">
+Version 2.0 (Beta) is released.
+
+</p>
+
+
+</body>
+
+</html>
+
+
+
+
+
+
+
+
+
+
+
diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000..6017db2
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,28 @@
+# Uncomment the COMPILER and OPTIONS lines corresponding to
+# the platform and compiler you plan to use.
+
+# If compiling with the gcc compiler:
+COMPILER = gcc
+OPTIONS = -O3
+
+# If compiling with the Sun cc compiler on a Sparc machine.
+#COMPILER = cc
+#OPTIONS = -fast -xO4
+
+# Generic, should work on work on most machines but may not produce
+# the most optimal code
+#COMPILER = cc
+#OPTIONS = -O
+
+
+# You should not need to change anything below this line
+# Type 'make'. This will build the program 'ROADTRIPS'.
+##################################################################
+
+CC_LIB = -lm
+
+ROADTRIPS: ROADTRIPS_SOURCE.c cholesky.c pnorms2.c nrutil.c nrutil.h
+ $(COMPILER) $(CC_LIB) $(OPTIONS) ROADTRIPS_SOURCE.c -o ROADTRIPS
+
+
+
diff --git a/ROADTRIPS_SOURCE.c b/ROADTRIPS_SOURCE.c
new file mode 100644
index 0000000..d055d9e
--- /dev/null
+++ b/ROADTRIPS_SOURCE.c
@@ -0,0 +1,5587 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include<string.h>
+#include "nrutil.h"
+#include <math.h>
+#include "nrutil.c"
+#include "cholesky.c"
+#include "pnorms2.c"
+#define MAXFAM 10000
+#define MAXTOP 20
+#define MAX_SNPS_FOR_MATRIX 500000
+#define MAXLEN 1000
+
+struct FAM {
+ int N; //total number of individuals in a family
+ int Pheno; //number of individuals phenotyped in a family
+ int NoPheno; // number of individuals not phenotyped in a family
+ int Unknown; // number of individuals removed from the analysis
+ int INCORRECTPheno;
+ double **cholent;
+ double **chol;
+ int *MissingVec; // list of individuals with missing genotype
+ int *descri; // array of correspondance between rank in the family and Id's
+ double **MZ; //THIS IS FOR INDIVIDUALS THAT ARE MZ TWINS
+ double **AVEC; //THIS IS THE A PHENOTYPE VECTOR USING EVERYONE
+ int *AFFEC; //THIS IS TO RECORD THE AFFECTION STATUS
+ int *SEX ; // THIS IS TO RECORD THE SEX
+ int *STUDYID;
+};
+typedef struct Nsize {
+ int N; //total number of ind
+ int Nc; // number of cases
+ int Nt; //number of controls
+ int Nu; //number of unknown controls
+}Nsize;
+struct MARKER {
+ int Nball; //number of alleles
+ int Nc; //number of cases with known genotype
+ int Nt; //number of controls with known genotype
+ int Nu; //number of unkown controls with known genotype
+ int ***mark; //3-dim array. 1st dimension: family number; 2nd dim: indiv rank; 3rd dim has 3 components [1]:allele1,[2]:allele2 and [3]:status
+ Nsize *typed;
+};
+
+/* M is the number of alleles
+ N is the number of individuals in the marker data file
+ NPheno is the number of phenotyped individuals
+ NnoPheno the number of not phenotyped individuals
+ NnoUnknown is the number of not individuals that were removed from the anlysis (this is for option 2 since individuals that are not phenotyped are removed)
+ F number of independent families
+ outfile is the result file, genofile is the marker data file and idfile is the kinshipcoef file
+ famdata is an array of FAM with particular information regarding each family
+ Mark is an array of MARKER with particular information for each marker
+ Storekin is a 3-dim array storing the inbreeding and kinship coefficients in each family.
+
+ */
+
+int M=0,N,F,NbMark,NPheno=0,NnoPheno=0,NUnknown=0,Naffected=0,NUnaffected=0,X=0;
+int Nmale=0,Nfemale=0, PREVCOUNT=0,ERROR;
+FILE *outfile,*genofile,*idfile,*errfile,*penfile,*sigfile,*pvfile,*famfile,*chivfile,*empcorrfile;
+struct FAM famdata[MAXFAM];
+struct MARKER Mark[2];
+double ***Storekin;
+double Kp, *KP;
+int TOTALMZCOUNT=0;
+int MAXLINE,MAXMARK;
+int Option,Missing;
+int BIGMARKER;
+int **NMARKERS,*FINALTYPED,TYPEDNUM,MARKERCOUNT,NAMECOUNT;
+double PART1,PART2,PART3;
+double **ZMAT,**COVMAT,**ESTCOVMAT,**KINALLMATRIX;
+int *GENOTYPED,*D,*Place,FINALCOUNTED;
+FILE *fsnpname;
+char **SNPNAME;
+char **TOPSNPNAME,**TOPSNPNAME2,**TOPSNPNAME3,CURRENTSNPNAME[200];
+int MYCOUNT;
+double *DRVEC,*DPVEC,*AVEC, DRPART,DPPART,APART,*YVEC,*DR,*DP;
+int PRINT=0;
+
+void readpen(char *name);
+void readcar(char *name);
+void readdata (struct MARKER *Mark,struct FAM *famdata,FILE *errfile);
+void readGenotypes(int fam,int m,int length,double **cholaug,double **cholaugCase,double **cholaugControl,double **cholaugUnknown,int *MissingVec,int miss,double **kincoefmatrix,double **kincoefMatrixCase,double **kincoefmatrixControl,double **kincoefmatrixUnknown);
+void readkincoef(char *name,FILE *errfile,struct FAM *famdata,double ***Storekin);
+void alleleFreq(double **cholaug,double *frequency,int size, double *denominator);
+void naiveCount(double **cholaug,double *Naive,double *Naivefreq,int size);
+void getfrequency(double *Naivefreq,double *NaivefreqCase,double *NaivefreqControl,double *NaivefreqUnknown,double *frequency,double *frequencyCase,double *frequencyControl,double *frequencyUnknown,double denominator,double denomcases,double denomcontrols,double denomunknown,int Nall,int Ncase,int Ncontrol,int Nunknown);
+void modifcholaug(double **cholent,double **cholaug,double **chol,double *frequency,int size);
+int makeFreqMat(double **freqMatrix,double *frequency);
+void comput_info_score(double **cholaug,double **freqMatrix,double *infoQL_rr,double *infoQL_rf,double *infoQL_ff,double *Rvector,int size);
+void from_info2_chi2(double info_rr,double info_rf,double info_ff,double *Naive,double *Naivefreq,double **freqNaive,double *chi2val,int Nall,int Ncase);
+void from_info2_score(double **freqMatrix,double infoQL_rr,double infoQL_rf,double infoQL_ff,double *Rvector,double *testval);
+void comput_info_chi2(double **kincoefMatrix,double **cholaug,double *info_rr,double *info_rf,double *info_ff,int size);
+int findInd(int Id1,int family);
+void comput_info_scoreMQLS(double **cholaug,double **freqMatrix,double *infoQL_rr,double *infoQL_rf,double *infoQL_ff,double *Rvector,int size);
+void GET_PHENOVECTOR_AND_MZtwins(int fam,int length);
+void vecsrt(double *d, int *M,int n);
+void readFAM(char *name);
+void readdataFAM (struct FAM *famdata,FILE *errfile);
+int getgenoline_PLINK(struct MARKER *Mark,struct FAM *famdata,FILE *errfile);
+int getgenoline_LINKAGE(struct MARKER *Mark,struct FAM *famdata,FILE *errfile);
+int getgenoline_ADDITIVE(struct MARKER *Mark,struct FAM *famdata,FILE *errfile);
+void get_EMPIRICAL_MATRIX(FILE *errfile);
+void get_FINAL_MATRIX(int finaltyped, double **ESTCOVMAT,int *D,double **ZMAT);
+void readsnpnames (char *name,int MARKERCOUNT,char** SNPNAME);
+void vecsrt2(double *d, int *M,char **NAME,int n);
+void getsnpnamefile (char *name);
+void robustvar(double **cholaug,double *ROBUST_11,double *YYvector,double *Y1vector,int size,int *Nstu);
+void from_info2_scoreROBUST(double **freqMatrix,double infoQL_rr,double infoQL_rf,double infoQL_ff,double *Rvector,double *testval,double ROBUST_11,double *YYvector,double *Y1vector, int Nstu,double *ROBUSTVAR);
+void from_info2_chi2_ROBUST(double info_rr, double info_rf, double info_ff, double *Naive,double *Naivefreq,double **freqNaive,double *chi2val,int Nall,int Ncase,double ROBUST_11,double *YYvector,double *Y1vector, int Nstu,double *ROBUSTVAR);
+void WEIGHTS(double **cholaug,double **cholent,double *PART1,double *PART2,double *PART3,int size,int *Nstu);
+
+void GET_KIN_MATRIX(int fam, int length);
+void get_FINAL_MATRIX_KINSHIP(int finaltyped, double **ESTCOVMAT,int *D,double **ZMAT);
+void READ_EMPIRICAL_MATRIX(char *name);
+void readkincoefnoinfo(FILE *errfile, struct FAM *famdata,double ***Storekin);
+int main (int argc, char *argv[])
+
+
+{
+ /* cholent stores the allelic information in the M first columns. Column M+1 contains 2, column M+2 contains 2 for cases and 0 for controls
+ cholaug stores cholent times the inverse of the cholesky decompo of the covariance matrix
+ chol stores the cholesky decomposition of kincoefMatrix
+ kincoefMatrix stores the kinship based covariance Matrix
+ frequency stores the frequency estimates
+ freqMatrix is a matrix that is a function of the M-1 allele frequencies
+ MissingVec lists all individual number for whom genotype or phenotype info is missing
+ dmatrix and dvector are available from nrutil.c
+ */
+
+ double **cholaug,**cholentCase,**cholentControl,**cholentUnknown;
+ double **kincoefMatrix,**kincoefMatrixCase,**kincoefMatrixControl,**kincoefMatrixUnknown;
+ double *frequency,*frequencyCase,*frequencyControl,*frequencyUnknown;
+ double **freqMatrix;
+ double testval=0,chi2val=0, denominator=0, denomcases=0, denomcontrols=0,denomunknown=0;
+ double *Naive,*Naivefreq,**freqNaive,*NaiveCase,*NaiveControl,*NaiveUnknown,*NaivefreqCase,*NaivefreqControl,*NaivefreqUnknown,*Rvector;
+ double info_rr=0,info_rf=0,info_ff=0,infoQL_rr=0,infoQL_rf=0,infoQL_ff=0;
+ int i,j,k,fam,m,followcase=0,followcontrol=0,followunknown,followall=0,df=0,Npas,negfreq=0;
+ double MQLSval=0,MQLSvalrobust=0,chi2valrobust=0,testvalrobust=0;
+ double *Pvalues,*Pvalues2,*Pvalues3;
+ double *TOPPvalues,*TOPPvalues2,*TOPPvalues3,pval1,pval2,pval3;
+ int *Porder,*Porder2,*Porder3,top;
+ int *TOPPorder,*TOPPorder2,*TOPPorder3;
+ double *YYvector,*Y1vector,ROBUST_11,*ROBUSTVAR;
+ int Nstu;
+ double **CINVT,**cholaug2;
+ double **A1,**A2,sum,*tempV1,*tempV2,*tempV1A,*V1,val1,val2,val3,**COVMAT,*V,*TERM1,RW,RM,SBLUE,VARBLUE;
+ double RCHI;
+ int k1,l,row,col;
+ int mycount,numtyped,pers1,pers2,oldnumtyped,nonpolycount=0;
+ char tempname[100];
+ char str1[MAXLEN];
+ char pedfile[MAXLEN] = "phenofile";
+ char kinshipfile[MAXLEN] = "kinfile";
+ char prevfile[MAXLEN] = "prevalence";
+ char samplefile[MAXLEN] = "study.sample";
+ char output[MAXLEN] = "output";
+ char typedfile[MAXLEN]="genofile";
+ char input[MAXLEN];
+ char controlfile[MAXLEN];
+ char markerfile[MAXLEN];
+char empfile[MAXLEN];
+ char *ch;
+ int arg;
+ int gfile = 0; /* Change to 1 if there is a genotyped file */
+ int pfile = 0;
+ int ffile = 0;
+ int sfile = 0;
+ int ofile = 0;
+ int dfile = 0;
+ int cfile = 0;
+ int rfile =0;
+ int kfile =0;
+ int nfile=0;
+ int efile=0;
+ int pedinfo=1;
+ int HWE,POLYMORPHCOUNT=0;
+
+
+ Option=1;
+ Missing=1;
+ X=0;
+ HWE=1;
+ PRINT=0;
+ pedinfo=1;
+ /*printf("argc = %d\n", argc);*/
+
+
+
+
+
+
+
+
+if (argc > 1) {
+ for (arg=1; arg < argc && argv[arg][0] == '-'; arg++) {
+ switch (argv[arg][1])
+ {case 'p':
+ strncpy(pedfile, argv[++arg], MAXLEN);
+ printf("user specified phenotype file: %s\n", pedfile);
+ pfile = 1;
+ break;
+ case 'g':
+ strncpy(typedfile, argv[++arg], MAXLEN);
+ printf("user specified genotype file: %s\n", typedfile);
+ gfile = 1;
+ break;
+
+ case 'k':
+ strncpy(kinshipfile, argv[++arg], MAXLEN);
+ printf("user specified pedigree information file: %s\n", kinshipfile);
+ kfile = 1;
+ break;
+ case 'r':
+ strncpy(prevfile, argv[++arg], MAXLEN);
+ printf("user specified prevalence file: %s\n", prevfile);
+ rfile = 1;
+ break;
+ case 'n':
+ strncpy(markerfile, argv[++arg], MAXLEN);
+ printf("user specified SNP names file: %s\n", markerfile);
+ nfile = 1;
+ break;
+
+case 'u':
+ Option = 2;
+ printf("Will remove unknown controls from the analysis \n");
+ break;
+
+
+case 'm':
+ Missing = 2;
+ printf("Will exclude phenotypes of individuals with missing genotypes for the RM test.\n");
+ break;
+
+
+
+case 'h':
+ HWE = 1;
+ printf("User specified association tests calculated assuming Hardy-Weinberg equilibrium. \n");
+ break;
+
+case 'e':
+ strncpy(empfile, argv[++arg], MAXLEN);
+ printf("user specified empirical correlation file: %s\n", empfile);
+ efile = 1;
+ break;
+
+case 'f':
+ PRINT = 1;
+ printf("User has specified for the empirical matrix to be printed to a file. The matrix will be printed to a file named 'ROADTRIPS_MATRIX.txt' \n");
+ break;
+
+case 'o':
+ pedinfo = 0;
+ printf("User specified that there is no pedigree information, so pedigree information will not be used in the analysis. \n");
+ break;
+
+
+ default:
+ printf ("Unknown option \"%s\"\n", argv[arg]);
+ exit(1);
+
+ }}
+
+ }
+
+
+
+ X=0;
+
+
+
+if (!pfile) {
+printf("phenotype file: %s\n", pedfile);
+ }
+
+ if (!gfile) {
+printf("genotype file: %s\n", typedfile);
+ }
+
+if (!kfile) {
+printf("pedigree information file: %s\n", kinshipfile);
+
+
+
+}
+
+
+if (!rfile) {printf("prevalence file: %s\n", prevfile);
+ }
+
+
+ if(PRINT==1&&efile==1)
+ {printf("Error! User specified flag -e and flag -f. Flag -e will be used so that the empirical correclation matrix will be read in. Flag -f is ignored. The empirical matrix will not be calculated and will not be printed to a file \n");}
+
+
+
+
+
+/*
+
+ if (!pfile) {
+ printf("Enter pedigree file (-p): ");
+ fgets(pedfile, MAXLEN, stdin);
+ ch = strchr(pedfile, '\n');
+ if (ch != NULL)
+ *ch = '\0';
+ printf("\npedigree file: %s\n", pedfile);
+ }
+
+ if (!gfile) {
+ printf("Enter genotype file (-g): ");
+ fgets(typedfile, MAXLEN, stdin);
+ ch = strchr(typedfile, '\n');
+ if (ch != NULL)
+ *ch = '\0';
+ printf("\ngenotype file: %s\n", typedfile);
+ }
+
+
+ if (!kfile) {
+ printf("Enter kinship coefficient file (-k): ");
+ fgets(kinshipfile, MAXLEN, stdin);
+ ch = strchr(kinshipfile, '\n');
+ if (ch != NULL)
+ *ch = '\0';
+ printf("\n kinship file: %s\n", kinshipfile);
+ }
+
+
+ if (!rfile) {
+ printf("Enter kinship coefficient file (-k): ");
+ fgets(prevfile, MAXLEN, stdin);
+ ch = strchr(prevfile, '\n');
+ if (ch != NULL)
+ *ch = '\0';
+ printf("\n prevalence file: %s\n", prevfile);
+ }
+
+
+*/
+
+
+
+ MAXMARK=2;
+
+
+
+Kp=0;
+ KP=dvector(0,3);
+
+/* readpen(argv[4]); */
+
+ readpen(prevfile);
+
+
+
+
+ /* readFAM(argv[1]); */
+
+
+readFAM(pedfile);
+
+
+ for (i=0;i<=F;i++)
+ {
+
+ famdata[i].NoPheno=0;
+ famdata[i].Pheno=0;
+ famdata[i].Unknown=0;
+ famdata[i].INCORRECTPheno=0;
+ famdata[i].descri=(int*)malloc(((famdata[i].N)+1)*sizeof(int));
+ if (!famdata[i].descri) {printf("Error in memory allocation 5\n");
+ exit(1);}
+
+ famdata[i].MZ=(double **)malloc((size_t)(((famdata[i].N)+1)*sizeof(double*)));
+
+ for (j=0;j<=famdata[i].N;j++)
+ {famdata[i].MZ[j]=(double *)malloc((size_t) ((4)*sizeof(double)));}
+
+famdata[i].AVEC=(double **)malloc((size_t)(((famdata[i].N)+1)*sizeof(double*))); for (j=0;j<=famdata[i].N;j++)
+ {famdata[i].AVEC[j]=(double *)malloc((size_t) ((4)*sizeof(double)));}
+
+
+
+
+ famdata[i].AFFEC=(int *)malloc((size_t)(((famdata[i].N)+1)*sizeof(int)));
+ famdata[i].SEX=(int *)malloc((size_t)(((famdata[i].N)+1)*sizeof(int)));
+
+
+
+ famdata[i].STUDYID=(int *)malloc((size_t)(((famdata[i].N)+1)*sizeof(int)));
+
+
+
+
+
+
+
+ }
+
+
+ if((errfile=fopen("ROADTRIPS_Software.err", "w"))==NULL)
+ {
+ printf("Can't open ROADTRIPS_Software.err .\n");
+ exit(1);
+ }
+
+
+
+
+
+ readdataFAM(famdata,errfile);
+
+
+
+ /* THIS IS THE MAXIMUM LENGTH FOR EACH ROW IN THE GENOTYPE FILE */
+
+
+ MAXLINE=NPheno*30;
+
+
+
+ Storekin = (double ***)malloc((size_t) ((F+1)*sizeof(double**)));
+ for (i=0;i<=F;i++)
+ { if (i==0) Npas=N;
+ else Npas=famdata[i].Pheno+famdata[i].NoPheno;
+
+ Storekin[i] = (double **)malloc((size_t) ((Npas+1)*sizeof(double*)));
+ if (!Storekin[i]) {printf("Error in memory allocation for kinship coefficient storage\n");
+ exit(1);}
+ for (j=0;j<=Npas;j++)
+ {
+ Storekin[i][j]= (double *)malloc((size_t) ((Npas+1)*sizeof(double)));
+ if (!Storekin[i][j]) {printf("Error in memory allocation for kinship coefficient storage\n");
+ exit(1);}
+ }
+ }
+
+
+ /* readkincoef(argv[2],errfile,famdata,Storekin); */
+
+
+ if(pedinfo==1)
+ {readkincoef(kinshipfile,errfile,famdata,Storekin);}
+ if(pedinfo==0)
+ {readkincoefnoinfo(errfile,famdata,Storekin);}
+
+
+
+
+ printf("Read in kinship coefficients and inbreeding coefficients. \n");
+
+
+FINALTYPED=ivector(0,NPheno);
+ESTCOVMAT=dmatrix(0,NPheno,0,NPheno);
+
+
+/*
+KINALLMATRIX=dmatrix(0,NPheno,0,NPheno);
+ for(i=1;i<=NPheno;i++)
+ {for(j=1;j<=NPheno;j++)
+ {KINALLMATRIX[i][j]=0;}}
+
+*/
+
+GENOTYPED=ivector(0,NPheno);
+D=ivector(0,NPheno);
+Place=ivector(0,NPheno);
+V=dvector(0,NPheno);
+TERM1=dvector(0,NPheno);
+
+
+/*
+ FINALCOUNTED=0;
+for (fam=1;fam<=F;fam++)
+ {GET_KIN_MATRIX(fam,famdata[fam].Pheno);}
+ printf("FINALCOUNTED is %d \n",FINALCOUNTED);
+*/
+
+
+for (fam=1;fam<=F;fam++)
+ {GET_PHENOVECTOR_AND_MZtwins(fam,famdata[fam].Pheno);}
+
+
+
+
+ printf("Read in phenotype information. \n");
+
+
+
+ NbMark=1;
+
+
+ for (m=1;m<=NbMark;m++)
+ {
+ Mark[NbMark].Nball=0;
+ Mark[NbMark].Nc=0;
+ Mark[NbMark].Nt=0;
+ Mark[NbMark].Nu=0;
+ Mark[m].typed = (Nsize *)malloc((size_t) ((MAXFAM+1)*sizeof(Nsize)));
+ if (!Mark[m].typed) {printf("Error in memory allocation 1\n");
+ exit(1);}
+
+ Mark[m].mark = (int ***)malloc((size_t) ((MAXFAM+1)*sizeof(int**)));
+ if (!Mark[m].mark) {printf("Error in memory allocation 2\n");
+ exit(1);}
+
+ for (i=0;i<=F;i++)
+ { Mark[m].typed[i].N=0;
+ Mark[m].typed[i].Nc=0;
+ Mark[m].typed[i].Nt=0;
+ Mark[m].typed[i].Nu=0;
+ Mark[m].mark[i] = (int **)malloc((size_t)(((famdata[i].N)+1)*sizeof(int*)));
+ if (!Mark[m].mark[i]) {printf("Error in memory allocation 3\n");
+ exit(1);}
+
+ for (j=0;j<=famdata[i].N;j++)
+ {Mark[m].mark[i][j]= (int *)malloc((size_t) ((6)*sizeof(int)));
+ if (!Mark[m].mark[i][j]) {printf("Error in memory allocation 4 %d %d %d\n",famdata[i].N,i,j);
+ exit(1);}
+ }
+
+
+
+
+
+ }
+ }
+
+
+
+ /* if((genofile=fopen(argv[3], "r"))==NULL)
+ {
+ printf("Can't open %s\n",argv[3]);
+ exit(1);
+ }*/
+
+
+if((genofile=fopen(typedfile, "r"))==NULL)
+ {
+ printf("Can't open %s\n",typedfile);
+ exit(1);
+ }
+
+
+
+
+
+
+
+ if(efile==1)
+ {printf("Reading the Empirical Correlation Matrix from the user specified file. \n");
+READ_EMPIRICAL_MATRIX(empfile);
+printf("Empirical Covariance Matrix has been read into memory. Now testing each SNP for association.\n");
+}
+
+ else{
+printf("Calculating The Empirical Correlation Matrix. \n");
+get_EMPIRICAL_MATRIX(errfile);
+ printf("Empirical Correlation Matrix has been calculated. Now testing each SNP for association.\n");
+}
+
+
+
+
+
+
+rewind(genofile);
+
+
+
+
+
+
+ if(X==0)
+ {
+
+if((sigfile=fopen("ROADTRIPStest.top", "w"))==NULL)
+ {
+ printf("Can't open ROADTRIPStest.top.\n");
+ exit(1);
+ }
+
+
+if((pvfile=fopen("ROADTRIPStest.pvalues", "w"))==NULL)
+ {
+ printf("Can't open ROADTRIPStest.pvalues.\n");
+ exit(1);
+ }
+
+
+if((chivfile=fopen("ROADTRIPStest.testvalues", "w"))==NULL)
+ {
+ printf("Can't open ROADTRIPStest.testvalues.\n");
+ exit(1);
+ }
+
+
+
+
+ if((outfile=fopen("ROADTRIPStest.out", "w"))==NULL)
+ {
+ printf("Can't open ROADTRIPStest.out .\n");
+ exit(1);
+ }
+
+
+
+ }
+
+
+
+
+ if(X==1)
+ {
+
+if((sigfile=fopen("XMtest.top", "w"))==NULL)
+ {
+ printf("Can't open XMtest.top.\n");
+ exit(1);
+ }
+
+
+if((pvfile=fopen("XMtest.pvalues", "w"))==NULL)
+ {
+ printf("Can't open XMtest.pvalue.\n");
+ exit(1);
+ }
+
+
+if((chivfile=fopen("XMtest.testvalues", "w"))==NULL)
+ {
+ printf("Can't open XMtest.testvalues.\n");
+ exit(1);
+ }
+
+
+
+ if((outfile=fopen("XMtest.out", "w"))==NULL)
+ {
+ printf("Can't open XMtest.out .\n");
+ exit(1);
+ }
+
+
+
+ }
+
+
+
+
+
+
+ DR=dvector(0,NPheno);
+ DP=dvector(0,NPheno);
+ DRVEC=dvector(0,NPheno);
+ DPVEC=dvector(0,NPheno);
+ AVEC=dvector(0,NPheno);
+ V1=dvector(0,NPheno);
+ YVEC=dvector(0,NPheno);
+
+
+
+
+ fprintf(outfile,"******Results of the Case-control Association tests ******\n\n");
+
+ if(Option==1)
+{fprintf(outfile,"There are %d individuals from %d independent families. %d of the individuals are affected, %d of the individuals are unaffected, and %d of the individuals are of unknown phenotype.\n\n",NPheno,F,Naffected,NUnaffected,NUnknown);
+}
+
+if(Option==2)
+{fprintf(outfile,"There are %d individuals from %d independent families. %d of the individuals are affected, %d of the individuals are unaffected, and %d are of unknown phenotype. The -u option was chosen by the user so individuals with unknown phenotypes were not used in the analysis.\n\n",NPheno,F,Naffected,NUnaffected,NUnknown);
+}
+
+if(X==0)
+ {fprintf(outfile,"There are %d males and %d females. The prevalence values used in the RM test statistic for males and females are %lf and %lf, respectively. \n",Nmale,Nfemale,KP[1],KP[2]);}
+
+
+if(X==1)
+ {fprintf(outfile,"There are %d males and %d females. The prevalence values used in the XM test statistic for males and females are %lf and %lf, respectively. \n",Nmale,Nfemale,KP[1],KP[2]);}
+
+
+
+
+if(TOTALMZCOUNT>0)
+{fprintf(outfile,"There are %d MZ twin pairs \n\n",TOTALMZCOUNT);}
+
+
+
+
+
+
+
+
+
+
+
+
+
+TOPPvalues=dvector(0,MAXTOP);
+TOPPvalues2=dvector(0,MAXTOP);
+TOPPvalues3=dvector(0,MAXTOP);
+
+
+
+
+TOPPorder=ivector(0,MAXTOP);
+TOPPorder2=ivector(0,MAXTOP);
+TOPPorder3=ivector(0,MAXTOP);
+
+
+
+
+
+
+/*
+ if(nfile==1)
+ { getsnpnamefile(markerfile);
+ }
+*/
+
+TOPSNPNAME=(char **)malloc((size_t) ((MAXTOP+1)*sizeof(char*)));
+TOPSNPNAME2=(char **)malloc((size_t) ((MAXTOP+1)*sizeof(char*)));
+TOPSNPNAME3=(char **)malloc((size_t) ((MAXTOP+1)*sizeof(char*)));
+
+
+ for(j=1;j<=MAXTOP;j++)
+ {TOPSNPNAME[j]=(char *)malloc((size_t) ((100)*sizeof(char)));
+TOPSNPNAME2[j]=(char *)malloc((size_t) ((100)*sizeof(char)));
+TOPSNPNAME3[j]=(char *)malloc((size_t) ((100)*sizeof(char)));
+
+
+ }
+
+
+
+
+
+/*
+fprintf(pvfile,"MARKER \t SNP_NAME \t RM \t RCHI \t RW \n");
+*/
+
+ if(X==0)
+ {
+ if(HWE==0)
+ {fprintf(pvfile,"SNP \t NAME \t\t \t MQLS_Robust \t CCHI_Robust \t WQLS_Robust \n");
+fprintf(chivfile,"SNP \t NAME \t\t \t MQLS_Robust \t CCHI_Robust \t WQLS_Robust \n");
+}
+else
+{fprintf(pvfile,"SNP \t NAME \t\t \t RM \t RCHI \t RW \n");
+fprintf(chivfile,"SNP \t NAME \t\t \t RM \t RCHI \t RW \n");
+}
+ }
+ else{
+
+if(HWE==0)
+ {fprintf(pvfile,"SNP \t NAME \t\t \t XM_Robust \t XCHI_Robust \t XW_Robust \n");
+fprintf(chivfile,"SNP \t NAME \t\t \t XM_Robust \t XCHI_Robust \t XW_Robust \n");
+
+}
+else
+{fprintf(pvfile,"SNP \t NAME \t\t \t XM_HWE \t XCHI_HWE \t XW_HWE \n");
+fprintf(chivfile,"SNP \t NAME \t\t \t XM_HWE \t XCHI_HWE \t XW_HWE \n");
+}
+
+ }
+
+
+
+
+ BIGMARKER=0;
+
+ printf("Calculating association test statistics for every marker. \n");
+
+ while(getgenoline_PLINK(Mark,famdata,errfile)>0 )
+ {
+BIGMARKER++;
+
+
+ if(BIGMARKER%1000==0)
+ {printf("Testing marker %d for association\n",BIGMARKER);}
+
+
+
+
+
+
+ m=1;
+
+
+
+
+
+
+
+
+ negfreq=0;
+ M=Mark[m].Nball;
+
+
+ freqMatrix=dmatrix(1,M,1,M);
+ frequency=dvector(1,M);
+ frequencyCase=dvector(1,M);
+ frequencyControl=dvector(1,M);
+ frequencyUnknown=dvector(1,M);
+ Naive=dvector(1,M);
+ NaiveCase=dvector(1,M);
+ NaiveControl=dvector(1,M);
+ NaiveUnknown=dvector(1,M);
+ Naivefreq=dvector(1,M);
+ Rvector=dvector(1,M);
+ NaivefreqCase=dvector(1,M);
+ NaivefreqControl=dvector(1,M);
+ NaivefreqUnknown=dvector(1,M);
+ freqNaive=dmatrix(1,M,1,M);
+ testval=0;
+ chi2val=0;
+ denominator=0;
+ denomcases=0;
+ denomcontrols=0;
+ denomunknown=0;
+ info_rr=0;
+ info_rf=0;
+ info_ff=0;
+ infoQL_rr=0;
+ infoQL_rf=0;
+ infoQL_ff=0;
+ MQLSval=0;
+
+
+ROBUSTVAR=dvector(1,M);
+ YYvector=dvector(1,M);
+ Y1vector=dvector(1,M);
+ ROBUST_11=0;
+ Nstu=0;
+
+
+
+
+ mycount=0;
+
+
+ FINALCOUNTED=0;
+
+
+ MYCOUNT=0;
+
+ DRPART=0;
+ DPPART=0;
+ APART=0;
+
+
+
+
+
+ for (i=1;i<=M;i++)
+ {
+ frequency[i]=0;
+ frequencyCase[i]=0;
+ frequencyControl[i]=0;
+ frequencyUnknown[i]=0;
+ Naive[i]=0;
+ NaiveCase[i]=0;
+ NaiveControl[i]=0;
+ NaiveUnknown[i]=0;
+ Naivefreq[i]=0;
+ NaivefreqCase[i]=0;
+ NaivefreqControl[i]=0;
+ NaivefreqUnknown[i]=0;
+ YYvector[i]=0;
+ Y1vector[i]=0;
+
+
+ if (i<M)
+ {
+ Rvector[i]=0;
+
+ for (j=1;j<=M-1;j++)
+ {
+ freqMatrix[i][j]=0;
+ freqNaive[i][j]=0;
+ }
+ }
+ }
+
+ for (fam=1;fam<=F;fam++)
+ {
+ followall=0;
+ followcase=0;
+ followcontrol=0;
+ followunknown=0;
+
+ if (Mark[m].typed[fam].N>0) {
+ followall=1;
+ famdata[fam].cholent=dmatrix(1,Mark[m].typed[fam].N,1,M+3+Mark[m].typed[fam].N);
+ famdata[fam].chol=dmatrix(1,Mark[m].typed[fam].N,1,Mark[m].typed[fam].N);
+
+
+ cholaug=dmatrix(1,Mark[m].typed[fam].N,1,M+3+Mark[m].typed[fam].N);
+
+kincoefMatrix=dmatrix(1,Mark[m].typed[fam].N,1,Mark[m].typed[fam].N);
+
+
+
+ }
+ if ((famdata[fam].Pheno-Mark[m].typed[fam].N)>0) famdata[fam].MissingVec=ivector(1,famdata[fam].Pheno-Mark[m].typed[fam].N);
+
+ if (Mark[m].typed[fam].Nc>0){
+ followcase=1;
+ cholentCase=dmatrix(1,Mark[m].typed[fam].Nc,1,M+2);
+ kincoefMatrixCase=dmatrix(1,Mark[m].typed[fam].Nc,1,Mark[m].typed[fam].Nc);
+ }
+ if (Mark[m].typed[fam].Nt>0){
+ followcontrol=1;
+ cholentControl=dmatrix(1,Mark[m].typed[fam].Nt,1,M+2);
+ kincoefMatrixControl=dmatrix(1,Mark[m].typed[fam].Nt,1,Mark[m].typed[fam].Nt);
+ }
+
+
+ if (Mark[m].typed[fam].Nu>0&&Option!=2){
+ followunknown=1;
+ cholentUnknown=dmatrix(1,Mark[m].typed[fam].Nu,1,M+2);
+ kincoefMatrixUnknown=dmatrix(1,Mark[m].typed[fam].Nu,1,Mark[m].typed[fam].Nu);
+ }
+
+
+
+
+
+
+ readGenotypes(fam,m,famdata[fam].Pheno,famdata[fam].cholent,cholentCase,cholentControl,cholentUnknown,famdata[fam].MissingVec,famdata[fam].Pheno-Mark[m].typed[fam].N,kincoefMatrix,kincoefMatrixCase,kincoefMatrixControl,kincoefMatrixUnknown);
+
+
+
+
+
+
+
+
+
+
+
+
+
+ /*computing allele frequencies in the cases... */
+
+ if (followcase==1)
+ {
+
+ naiveCount(cholentCase,NaiveCase,NaivefreqCase,Mark[m].typed[fam].Nc);
+
+ if (cholesky(kincoefMatrixCase,Mark[m].typed[fam].Nc,cholentCase,M+1,kincoefMatrixCase,cholentCase,1)!=1)
+ {printf("cholesky decomposition of the case cov matrix failed for family %d. Might be due to inconsistent kinship coefficient values...\n",fam);
+ exit(1);
+ }
+ alleleFreq(cholentCase,frequencyCase,Mark[m].typed[fam].Nc, &denomcases);
+ }
+ /*computing allele frequencies in the controls... */
+ if (followcontrol==1)
+ {
+
+ naiveCount(cholentControl,NaiveControl,NaivefreqControl,Mark[m].typed[fam].Nt);
+ if (cholesky(kincoefMatrixControl,Mark[m].typed[fam].Nt,cholentControl,M+1,kincoefMatrixControl,cholentControl,1)!=1)
+ { printf("cholesky decomposition of the control cov matrix failed for family %d. Might be due to inconsistent kinship coefficient values...\n",fam);
+ exit(1);
+ }
+
+ alleleFreq(cholentControl,frequencyControl,Mark[m].typed[fam].Nt, &denomcontrols);
+ }
+
+
+ /*computing allele frequencies in unknowns... */
+ if (followunknown==1)
+ {
+
+ naiveCount(cholentUnknown,NaiveUnknown,NaivefreqUnknown,Mark[m].typed[fam].Nu);
+ if (cholesky(kincoefMatrixUnknown,Mark[m].typed[fam].Nu,cholentUnknown,M+1,kincoefMatrixUnknown,cholentUnknown,1)!=1)
+ { printf("cholesky decomposition of the unknown phenotyped cov matrix failed for family %d. Might be due to inconsistent kinship coefficient values...\n",fam);
+ exit(1);
+ }
+
+ alleleFreq(cholentUnknown,frequencyUnknown,Mark[m].typed[fam].Nu, &denomunknown);
+ }
+
+
+
+
+
+ /*computing overall allele frequencies */
+
+
+
+
+
+ if (followall==1)
+ {
+
+ naiveCount(famdata[fam].cholent,Naive,Naivefreq,Mark[m].typed[fam].N);
+ // comput_info_chi2(kincoefMatrix,famdata[fam].cholent,&info_rr,&info_rf,&info_ff,Mark[m].typed[fam].N);
+
+if (cholesky(kincoefMatrix,Mark[m].typed[fam].N,famdata[fam].cholent,M+3+Mark[m].typed[fam].N,famdata[fam].chol,cholaug,1)!=1)
+ {printf("cholesky decomposition of the cov matrix failed for family %d. Might be due to inconsistent kinship coefficient values...\n",fam);
+ exit(1);
+ }
+
+ alleleFreq(cholaug,frequency,Mark[m].typed[fam].N, &denominator);
+
+
+
+ if(HWE==0)
+ { robustvar(cholaug,&ROBUST_11,YYvector,Y1vector,Mark[m].typed[fam].N,&Nstu); }
+
+
+
+ }
+
+
+
+
+ /*
+
+ if(fam<10)
+ { printf("We are here and number of individuals is %d \n",Mark[m].typed[fam].N);
+printf("KINSHIP MATRIX for family %d \n",fam);
+
+ for(i=1;i<=Mark[m].typed[fam].N;i++)
+ {for(j=1;j<=Mark[m].typed[fam].N;j++)
+ {printf("%lf ",kincoefMatrix[i][j]);}
+ printf("\n");
+ }
+
+
+
+printf("CHOLESKY INVERSE AUGMENTATION for family %d \n",fam);
+
+ for(i=1;i<=Mark[m].typed[fam].N;i++)
+ {for(j=1;j<=(M+3+Mark[m].typed[fam].N);j++)
+ {printf("%lf ",cholaug[i][j]);}
+ printf("\n");
+ }
+
+
+
+A1=dmatrix(0,Mark[m].typed[fam].N,0,Mark[m].typed[fam].N);
+
+ A2=dmatrix(0,Mark[m].typed[fam].N,0,Mark[m].typed[fam].N);
+
+
+for(k1=1;k1<=Mark[m].typed[fam].N;k1++)
+ {for(j=(M+3+1);j<=(M+3+Mark[m].typed[fam].N);j++)
+ {sum=0;
+ row=k1;
+ col=j;
+
+ for(l=1;l<=Mark[m].typed[fam].N;l++)
+ {
+ sum=sum+cholaug[l][col]*cholaug[l][M+3+row]; //Changed this since need transpose(CINVT)CINVT
+
+ }
+
+ A1[row][col-(M+3)]=sum;}}
+
+
+
+
+printf("CHOLESKY INVERSE for family %d \n",fam);
+
+ for(i=1;i<=Mark[m].typed[fam].N;i++)
+ {for(j=1;j<=Mark[m].typed[fam].N;j++)
+ {printf("%lf ",A1[i][j]);}
+ printf("\n");
+ }
+
+
+for(k1=1;k1<=Mark[m].typed[fam].N;k1++)
+ {for(j=1;j<=Mark[m].typed[fam].N;j++)
+ {sum=0;
+ row=k1;
+ col=j;
+ for(l=1;l<=Mark[m].typed[fam].N;l++)
+ {
+ sum=sum+A1[row][l]*kincoefMatrix[col][l];
+
+ }
+
+ A2[row][col]=sum;}}
+
+
+printf("Multiplying the two matrices we get for family %d \n",fam);
+
+ for(i=1;i<=Mark[m].typed[fam].N;i++)
+ {for(j=1;j<=Mark[m].typed[fam].N;j++)
+ {printf("%lf ",A2[i][j]);}
+ printf("\n");
+ }
+
+
+
+
+
+
+
+ }
+
+
+ */
+
+ WEIGHTS(cholaug,famdata[fam].cholent,&DPPART,&DRPART,&APART,Mark[m].typed[fam].N,&Nstu);
+
+
+
+
+ if (Mark[m].typed[fam].N>0) {
+
+ free_dmatrix(famdata[fam].cholent,1,Mark[m].typed[fam].N,1,M+3+Mark[m].typed[fam].N);
+ free_dmatrix(famdata[fam].chol,1,Mark[m].typed[fam].N,1,Mark[m].typed[fam].N);
+
+ free_dmatrix(cholaug,1,Mark[m].typed[fam].N,1,M+3+Mark[m].typed[fam].N);
+
+ free_dmatrix(kincoefMatrix,1,Mark[m].typed[fam].N,1,Mark[m].typed[fam].N);
+
+
+
+ }
+ if ((famdata[fam].Pheno-Mark[m].typed[fam].N)>0)
+ {free_ivector(famdata[fam].MissingVec,1,famdata[fam].Pheno-Mark[m].typed[fam].N);}
+
+ if (Mark[m].typed[fam].Nc>0){
+
+ free_dmatrix(cholentCase,1,Mark[m].typed[fam].Nc,1,M+2);
+ free_dmatrix(kincoefMatrixCase,1,Mark[m].typed[fam].Nc,1,Mark[m].typed[fam].Nc);
+ }
+ if (Mark[m].typed[fam].Nt>0){
+
+ free_dmatrix(cholentControl,1,Mark[m].typed[fam].Nt,1,M+2);
+ free_dmatrix(kincoefMatrixControl,1,Mark[m].typed[fam].Nt,1,Mark[m].typed[fam].Nt);
+ }
+
+
+ if (Mark[m].typed[fam].Nu>0&&Option!=2){
+ followunknown=1;
+ free_dmatrix(cholentUnknown,1,Mark[m].typed[fam].Nu,1,M+2);
+ free_dmatrix(kincoefMatrixUnknown,1,Mark[m].typed[fam].Nu,1,Mark[m].typed[fam].Nu);
+ }
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ /*
+
+ if (Mark[m].typed[fam].N>0) free_dmatrix(cholaug,1,Mark[m].typed[fam].N,1,M+3+Mark[m].typed[fam].N);
+ if (Mark[m].typed[fam].N>0) free_dmatrix(kincoefMatrix,1,Mark[m].typed[fam].N,1,Mark[m].typed[fam].N);
+
+
+
+ if (Mark[m].typed[fam].Nc>0) free_dmatrix(kincoefMatrixCase,1,Mark[m].typed[fam].Nc,1,Mark[m].typed[fam].Nc);
+ if (Mark[m].typed[fam].Nt>0) free_dmatrix(kincoefMatrixControl,1,Mark[m].typed[fam].Nt,1,Mark[m].typed[fam].Nt);
+
+ if (Mark[m].typed[fam].Nc>0) free_dmatrix(cholentCase,1,Mark[m].typed[fam].Nc,1,M+2);
+ if (Mark[m].typed[fam].Nt>0) free_dmatrix(cholentControl,1,Mark[m].typed[fam].Nt,1,M+2);
+
+
+
+ if (followunknown==1)
+ {
+ if (Mark[m].typed[fam].Nu>0) free_dmatrix(kincoefMatrixUnknown,1,Mark[m].typed[fam].Nu,1,Mark[m].typed[fam].Nu);
+ if (Mark[m].typed[fam].Nu>0) free_dmatrix(cholentUnknown,1,Mark[m].typed[fam].Nu,1,M+2);
+ }
+
+
+
+ */
+
+
+
+
+
+
+
+
+
+
+
+ }
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ getfrequency(Naivefreq,NaivefreqCase,NaivefreqControl,NaivefreqUnknown,frequency, frequencyCase,frequencyControl,frequencyUnknown,denominator,denomcases,denomcontrols,denomunknown,Mark[m].Nc+Mark[m].Nt+Mark[m].Nu,Mark[m].Nc,Mark[m].Nt,Mark[m].Nu);
+
+ makeFreqMat(freqNaive,Naivefreq);
+
+
+
+ /*
+ if(HWE==1)
+ {
+ if(Option==1)
+ {from_info2_chi2(info_rr,info_rf,info_ff,Naive,Naivefreq,freqNaive,&chi2val,Mark[m].Nc+Mark[m].Nu+Mark[m].Nt,Mark[m].Nc);}
+
+
+ if(Option==2)
+ {from_info2_chi2(info_rr,info_rf,info_ff,Naive,Naivefreq,freqNaive,&chi2val,Mark[m].Nc+Mark[m].Nt,Mark[m].Nc);}
+
+ }
+
+ */
+
+
+
+
+
+
+
+
+
+ if(HWE==0)
+ { from_info2_scoreROBUST(freqMatrix,infoQL_rr,infoQL_rf,infoQL_ff,Rvector,&MQLSvalrobust,ROBUST_11,YYvector,Y1vector,Nstu,ROBUSTVAR);
+
+ if(Option==1)
+ { from_info2_chi2_ROBUST(info_rr,info_rf,info_ff,Naive,Naivefreq,freqNaive,&chi2valrobust,Mark[m].Nc+Mark[m].Nt+Mark[m].Nu,Mark[m].Nc,ROBUST_11,YYvector,Y1vector,Nstu,ROBUSTVAR);
+ }
+
+
+
+ if(Option==2)
+ { from_info2_chi2_ROBUST(info_rr,info_rf,info_ff,Naive,Naivefreq,freqNaive,&chi2valrobust,Mark[m].Nc+Mark[m].Nt,Mark[m].Nc,ROBUST_11,YYvector,Y1vector,Nstu,ROBUSTVAR);
+ }
+
+
+ }
+
+
+ /*
+ if (makeFreqMat(freqMatrix,frequency)==1) {negfreq=1;}
+
+
+ if (negfreq==0)
+ {
+
+
+
+
+for (fam=1;fam<=F;fam++)
+ {
+
+
+ if (Mark[m].typed[fam].N>0)
+ {
+ cholaug=dmatrix(1,Mark[m].typed[fam].N,1,M+3);
+ modifcholaug(famdata[fam].cholent,cholaug,famdata[fam].chol,frequency,Mark[m].typed[fam].N);
+ comput_info_scoreMQLS(cholaug,freqMatrix,&infoQL_rr,&infoQL_rf,&infoQL_ff,Rvector,Mark[m].typed[fam].N);
+ free_dmatrix(cholaug,1,Mark[m].typed[fam].N,1,M+3);
+ }
+
+
+
+ }
+
+
+
+
+ if(HWE==1)
+ { from_info2_score(freqMatrix,infoQL_rr,infoQL_rf,infoQL_ff,Rvector,&MQLSval); }
+
+
+ if(HWE==0)
+ { from_info2_scoreROBUST(freqMatrix,infoQL_rr,infoQL_rf,infoQL_ff,Rvector,&MQLSvalrobust,ROBUST_11,YYvector,Y1vector,Nstu,ROBUSTVAR);
+
+ if(Option==1)
+ { from_info2_chi2_ROBUST(info_rr,info_rf,info_ff,Naive,Naivefreq,freqNaive,&chi2valrobust,Mark[m].Nc+Mark[m].Nt+Mark[m].Nu,Mark[m].Nc,ROBUST_11,YYvector,Y1vector,Nstu,ROBUSTVAR);
+ }
+
+
+
+ if(Option==2)
+ { from_info2_chi2_ROBUST(info_rr,info_rf,info_ff,Naive,Naivefreq,freqNaive,&chi2valrobust,Mark[m].Nc+Mark[m].Nt,Mark[m].Nc,ROBUST_11,YYvector,Y1vector,Nstu,ROBUSTVAR);
+ }
+
+
+ }
+
+
+
+
+ }
+
+ */
+
+
+
+/*output printing ... */
+
+
+
+
+/* MAKE SURE NO HETEROZYGOTE MAKERS FOR FIRST 10 POLYMORPHIC MARKERS WITH MINOR ALLELE FREQUENCY GREATER THAN .1 */
+
+ if(X==1 &&POLYMORPHCOUNT<=100&&Naivefreq[1]>.1&&Naivefreq[1]<.9)
+ {POLYMORPHCOUNT++;
+ERROR=0;
+for (i=1;i<=F;i++)
+ {for(j=1;j<=famdata[i].N;j++)
+
+ if(famdata[i].SEX[j]==1 && Mark[m].mark[i][j][1]>0 && Mark[m].mark[i][j][1]!=Mark[m].mark[i][j][2])
+ {ERROR=1;
+fprintf(errfile,"Error in the X-chromosome analysis. Individual %d from family %d is a male with a heterozygous genotype (%d,%d) for marker %d \n",famdata[i].descri[j],i, Mark[m].mark[i][j][1], Mark[m].mark[i][j][2],BIGMARKER);
+ }
+ }
+ if(ERROR==1)
+ {printf("ERROR! User specified X Chromosome analysis. Checking the first 100 markers with minor allele frequency greater than .1 to identify any heterozygous males. Marker %d has at least one heterozygous male. Please make sure that all markers in the genotype input file include only X-linked markers (and no autosomal markers). \n",BIGMARKER);
+ }
+
+ }
+
+
+
+
+
+ //get_FINAL_MATRIX_KINSHIP(FINALCOUNTED,ESTCOVMAT,D,KINALLMATRIX);
+
+
+
+
+ get_FINAL_MATRIX(FINALCOUNTED,ESTCOVMAT,D,ZMAT);
+
+
+
+
+
+
+ numtyped=FINALCOUNTED;
+
+
+
+for(k=1;k<=FINALCOUNTED;k++)
+{V[k]=AVEC[k]-(APART/DPPART)*DPVEC[k];
+
+}
+
+sum=0;
+for(k=1;k<=numtyped;k++)
+{sum=sum+V[k]*YVEC[k];
+}
+SBLUE=sum;
+
+
+
+ if(HWE==1)
+ {
+for(k=1;k<=numtyped;k++)
+ {sum=0;
+for(j=1;j<=numtyped;j++)
+ {sum=sum+ESTCOVMAT[k][j]*V[j]*2*frequency[1]*(1-frequency[1]);}
+TERM1[k]=sum;
+ }
+ }
+ else
+ {
+
+for(k=1;k<=numtyped;k++)
+ {sum=0;
+for(j=1;j<=numtyped;j++)
+ {sum=sum+ESTCOVMAT[k][j]*V[j]*ROBUSTVAR[1];}
+TERM1[k]=sum;
+ }
+
+
+
+ }
+
+
+
+sum=0;
+ for(k=1;k<=numtyped;k++)
+{sum=sum+V[k]*TERM1[k];
+}
+VARBLUE=sum;
+
+
+
+
+
+RM=SBLUE*SBLUE/VARBLUE;
+
+
+// printf("RM USING NEW WAY is %lf, robustvar is %lf and HWE variance is %lf \n",RM,ROBUSTVAR[1],2*frequency[1]*(1-frequency[1]));
+
+//printf("RM USING NEW WAY is %lf \n",RM);
+
+for(k=1;k<=FINALCOUNTED;k++)
+{V[k]=DRVEC[k]-(DRPART/DPPART)*DPVEC[k];
+}
+
+sum=0;
+for(k=1;k<=numtyped;k++)
+{sum=sum+V[k]*YVEC[k];
+}
+SBLUE=sum;
+
+
+
+ if(HWE==1)
+ {
+for(k=1;k<=numtyped;k++)
+ {sum=0;
+for(j=1;j<=numtyped;j++)
+ {
+ sum=sum+ESTCOVMAT[k][j]*V[j]*2*frequency[1]*(1-frequency[1]);
+
+
+
+}
+TERM1[k]=sum;
+ }
+ }
+ else
+ {
+
+for(k=1;k<=numtyped;k++)
+ {sum=0;
+for(j=1;j<=numtyped;j++)
+ {sum=sum+ESTCOVMAT[k][j]*V[j]*ROBUSTVAR[1];}
+TERM1[k]=sum;
+ }
+
+
+
+ }
+
+
+
+sum=0;
+ for(k=1;k<=numtyped;k++)
+{sum=sum+V[k]*TERM1[k];
+}
+VARBLUE=sum;
+
+
+
+
+
+RW=SBLUE*SBLUE/VARBLUE;
+
+
+//printf("RW USING NEW WAY is %lf \n",RW);
+
+
+
+
+ val1=0;
+ val2=0;
+for(k=1;k<=numtyped;k++)
+ {val1+=DR[k];
+ val2+=DP[k];
+}
+
+
+
+for(k=1;k<=numtyped;k++)
+{V[k]=DR[k]-(val1/val2)*DP[k];
+
+
+}
+
+
+sum=0;
+for(k=1;k<=numtyped;k++)
+{sum=sum+V[k]*YVEC[k];
+
+
+}
+SBLUE=sum;
+
+
+
+ if(HWE==1)
+ {
+for(k=1;k<=numtyped;k++)
+ {sum=0;
+for(j=1;j<=numtyped;j++)
+ {
+ sum=sum+ESTCOVMAT[k][j]*V[j]*2*Naivefreq[1]*(1-Naivefreq[1]);
+ }
+TERM1[k]=sum;
+ }
+ }
+ else
+ {
+
+for(k=1;k<=numtyped;k++)
+ {sum=0;
+for(j=1;j<=numtyped;j++)
+ {sum=sum+ESTCOVMAT[k][j]*V[j]*ROBUSTVAR[1];}
+TERM1[k]=sum;
+ }
+
+
+
+ }
+
+
+
+sum=0;
+ for(k=1;k<=numtyped;k++)
+{sum=sum+V[k]*TERM1[k];
+}
+VARBLUE=sum;
+
+
+
+
+RCHI=SBLUE*SBLUE/VARBLUE;
+
+
+
+//printf("New RCHI is %lf \n",RCHI);
+
+
+
+
+
+
+ fprintf(outfile,"****************************************");
+ fprintf(outfile,"\n\nAnalysis of Marker %d: %s \n\n",BIGMARKER,CURRENTSNPNAME);
+ fprintf(outfile,"****************************************\n");
+
+ if(Option==1)
+{fprintf(outfile,"There are %d affected individuals, %d unaffected individuals, and %d individuals of unknown phenotype available. \n\n",Mark[m].Nc,Mark[m].Nt,Mark[m].Nu);
+}
+
+ if(Option==2)
+{fprintf(outfile,"%d affected individuals and %d unaffected individuals available.\n\n",Mark[m].Nc,Mark[m].Nt);
+}
+
+ fprintf(outfile,"*****************************************\n");
+
+
+
+
+
+
+
+
+ pval1=1;
+ pval2=1;
+ pval3=1;
+
+if ( (Mark[m].Nt!=0 ||Mark[m].Nu!=0) && Mark[m].Nc!=0&&Naivefreq[1]>.01&&Naivefreq[1]<.99)
+ {df=0;
+ for (i=1;i<=M-1;i++)
+ if (frequency[i]!=0)
+ df++;
+
+
+
+
+ /******* RM TESTS ************/
+
+
+
+ MQLSvalrobust=RM;
+MQLSval=RM;
+
+
+ if(X==0)
+ {
+ if(HWE==0)
+ {fprintf(outfile,"RM test using robust variance estimator\n\n");}
+ if(HWE==1)
+fprintf(outfile,"RM test \n\n");
+
+
+ }
+
+else{if(HWE==0)
+ {fprintf(outfile,"XM test using robust variance estimator\n\n");}
+ if(HWE==1)
+fprintf(outfile,"XM test using HWE variance estimator\n\n");
+
+
+ }
+
+
+ if (Naivefreq[1]>0&&Naivefreq[1]<1)
+ {
+
+
+ /* fprintf(outfile,"RM statistic value = %f\t pvalue = %g df = %d\n\n",RM,pochisq(RM,df),df); */
+
+ if(HWE==1)
+ {
+ if(X==0)
+ {
+
+ fprintf(outfile,"RM statistic value = %f\t pvalue = %g df = %d\n\n",MQLSval,2*pnorms(-1*sqrt(MQLSval)),df);
+
+/*fprintf(outfile,"MQLS statistic value = %f\t pvalue = %g df = %d\n\n",MQLSval,pochisq(MQLSval,df),df);*/
+
+}
+else
+ { /*fprintf(outfile,"XM statistic value = %f\t pvalue = %g df = %d\n\n",MQLSval,pochisq(MQLSval,df),df);*/
+ fprintf(outfile,"XM statistic value = %f\t pvalue = %g df = %d\n\n",MQLSval,2*pnorms(-1*sqrt(MQLSval)),df);
+
+}
+
+
+ RM=MQLSval;
+
+}
+
+ if(HWE==0)
+ {
+ if(X==0)
+ {
+
+ /*fprintf(outfile,"MQLS statistic value = %f\t pvalue = %g df = %d\n\n",MQLSvalrobust,pochisq(MQLSvalrobust,df),df);*/
+fprintf(outfile,"MQLS statistic value = %f\t pvalue = %g df = %d\n\n",MQLSvalrobust,2*pnorms(-1*sqrt(MQLSvalrobust)),df);
+
+
+ }
+ else
+ {
+
+ /* fprintf(outfile,"XM statistic value = %f\t pvalue = %g df = %d\n\n",MQLSvalrobust,pochisq(MQLSvalrobust,df),df); */
+
+fprintf(outfile,"XM statistic value = %f\t pvalue = %g df = %d\n\n",MQLSvalrobust,2*pnorms(-1*sqrt(MQLSvalrobust)),df);
+
+
+}
+ RM=MQLSvalrobust;
+}
+
+ // printf("OLD RM is %lf \n",RM);
+ pval1=2*pnorms(-1*sqrt(RM));
+
+ /*
+ printf("Value is %lf and old p-value is %g and new p-value is %g \n",MQLSvalrobust,pochisq(MQLSvalrobust,df),2*pnorms(-1*sqrt(MQLSvalrobust)));
+ */
+
+
+ if ( pval1<=0.05) {
+
+ if (Rvector[1]>0) fprintf(outfile,"Frequency of allele %d is increased in the cases (quasi-score associated to this allele is %.4f)\n\n",1,Rvector[1]);
+ if (Rvector[1]<0) fprintf(outfile,"Frequency of allele %d is increased in the controls (quasi-score associated to this allele is %.4f)\n\n",1,Rvector[1]);
+ if (Rvector[1]==0) fprintf(outfile,"Frequency of allele %d is the same in cases and controls (quasi-score associated to this allele is 0)\n\n",1);
+
+ }
+
+
+ for (i=1;i<=M;i++)
+ {if (((Mark[m].Nc)*frequencyCase[i])<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in cases\n",i);
+
+
+ if(Option==2)
+ { if (((Mark[m].Nt)*frequencyControl[i])<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in controls\n",i);}
+
+ if(Option==1)
+ { if ( ( (Mark[m].Nt)*frequencyControl[i] + (Mark[m].Nu)*frequencyUnknown[i] )<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in controls\n",i);}
+
+
+
+
+
+ }
+
+
+
+ }
+ else
+
+ {if(X==0) {printf("Computation of the MQLS statistic is not possible\n\n");}
+ else { printf("Computation of the XM statistic is not possible\n\n");}
+ }
+
+
+
+
+
+ /******** Corrected Chi-Squared and X-Chi TESTS ************/
+
+
+
+
+
+
+ chi2valrobust=RCHI;
+chi2val=RCHI;
+
+
+ df=0;
+ for (i=1;i<=M-1;i++)
+ if (frequency[i]!=0)
+ df++;
+ fprintf(outfile,"\n*****************************************\n");
+ /* fprintf(outfile,"RCHI test \n\n"); */
+
+ if(X==0)
+ {
+ if(HWE==0)
+ {fprintf(outfile,"RCHI test using robust variance estimator\n\n");}
+ if(HWE==1)
+fprintf(outfile,"RCHI test \n\n");
+
+
+ }
+
+else{if(HWE==0)
+ {fprintf(outfile,"XCHI test using robust variance estimator\n\n");}
+ if(HWE==1)
+fprintf(outfile,"XCHI test using HWE variance estimator\n\n");
+
+
+ }
+
+
+
+if (Naivefreq[1]>0&&Naivefreq[1]<1)
+ {
+ /* fprintf(outfile,"RCHI statistic value = %f\t pvalue = %g df = %d\n\n",RCHI,pochisq(RCHI,df),df); */
+
+ if(HWE==1)
+ {
+ if(X==0)
+ {
+
+ /*fprintf(outfile,"Corrected chi-squared statistic value = %f\t pvalue = %g df = %d \n\n",chi2val,pochisq(chi2val,df),df);*/
+
+fprintf(outfile,"RCHI statistic value = %f\t pvalue = %g df = %d \n\n",chi2val,2*pnorms(-1*sqrt(chi2val)),df);
+
+
+
+
+}
+ else
+ {
+
+ /*fprintf(outfile,"XCHI statistic value = %f\t pvalue = %g df = %d \n\n",chi2val,pochisq(chi2val,df),df); */
+
+fprintf(outfile,"XCHI statistic value = %f\t pvalue = %g df = %d \n\n",chi2val,2*pnorms(-1*sqrt(chi2val)),df);
+
+
+}
+
+ RCHI=chi2val;
+}
+
+
+
+ if(HWE==0)
+ {
+ if(X==0)
+ {
+
+ /*fprintf(outfile,"Corrected chi-squared statistic value = %f\t pvalue = %g df = %d \n\n",chi2valrobust,pochisq(chi2valrobust,df),df);*/
+fprintf(outfile,"RCHI statistic value = %f\t pvalue = %g df = %d \n\n",chi2valrobust,2*pnorms(-1*sqrt(chi2valrobust)),df);
+
+}
+ else
+ {
+ /* fprintf(outfile,"XCHI statistic value = %f\t pvalue = %g df = %d \n\n",chi2valrobust,pochisq(chi2valrobust,df),df); */
+fprintf(outfile,"XCHI statistic value = %f\t pvalue = %g df = %d \n\n",chi2valrobust,2*pnorms(-1*sqrt(chi2valrobust)),df);
+
+
+}
+ RCHI=chi2valrobust;
+ }
+
+
+ // printf("Old RCHI is %lf \n",RCHI);
+ pval2=2*pnorms(-1*sqrt(RCHI));
+
+ for (i=1;i<=M;i++)
+ {if (((Mark[m].Nc)*NaivefreqCase[i])<5) fprintf(outfile,"The p-value might not be exact because of the small number of allele %d in cases\n\n",i);
+
+
+
+ if(Option==2)
+ { if (((Mark[m].Nt)*NaivefreqControl[i])<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in controls\n",i);}
+
+ if(Option==1)
+ { if ( ( (Mark[m].Nt)*NaivefreqControl[i] + (Mark[m].Nu)*NaivefreqUnknown[i] )<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in controls\n",i);}
+
+
+
+if (((Mark[m].Nt)*NaivefreqControl[i])<5) fprintf(outfile,"The p-value might not be exact because of the small number of allele %d in controls\ni\n",i);
+
+
+
+
+
+}
+
+ }
+
+ else
+
+ {if(X==0) {printf("Computation of the RCHI statistic is not possible\n\n");}
+ else{printf("Computation of the XCHI statistic is not possible\n\n");}
+ }
+
+
+ /********* WQLS and XW TESTS *********/
+
+/*
+info_rr=0;
+ info_rf=0;
+ info_ff=0;
+ infoQL_rr=0;
+ infoQL_rf=0;
+ infoQL_ff=0;
+ testval=0;
+ for(j=1;j<=M;j++)
+ {Rvector[j]=0;}
+
+ for (fam=1;fam<=F;fam++)
+ {
+
+ if (Mark[m].typed[fam].N>0)
+ {
+ cholaug=dmatrix(1,Mark[m].typed[fam].N,1,M+3);
+ modifcholaug(famdata[fam].cholent,cholaug,famdata[fam].chol,frequency,Mark[m].typed[fam].N);
+ comput_info_score(cholaug,freqMatrix,&infoQL_rr,&infoQL_rf,&infoQL_ff,Rvector,Mark[m].typed[fam].N);
+ free_dmatrix(cholaug,1,Mark[m].typed[fam].N,1,M+3);
+ free_dmatrix(famdata[fam].cholent,1,Mark[m].typed[fam].N,1, M+3+Mark[m].typed[fam].N);
+ free_dmatrix(famdata[fam].chol,1,Mark[m].typed[fam].N,1,Mark[m].typed[fam].N);
+
+ }
+
+ }
+
+
+
+
+
+
+
+ if(HWE==1)
+ { from_info2_score(freqMatrix,infoQL_rr,infoQL_rf,infoQL_ff,Rvector,&testval);}
+
+
+
+ if(HWE==0)
+ { from_info2_scoreROBUST(freqMatrix,infoQL_rr,infoQL_rf,infoQL_ff,Rvector,&testvalrobust,ROBUST_11,YYvector,Y1vector,Nstu,ROBUSTVAR); }
+
+
+
+
+
+
+*/
+
+
+ df=0;
+ for (i=1;i<=M-1;i++)
+ if (frequency[i]!=0)
+ df++;
+
+
+
+
+ fprintf(outfile,"*****************************************\n");
+
+
+
+ testval=RW;
+testvalrobust=RW;
+
+ if(X==0)
+ {
+ if(HWE==0)
+ {fprintf(outfile,"RW test using robust variance estimator\n\n");}
+ if(HWE==1)
+fprintf(outfile,"RW test\n\n");
+
+
+ }
+
+else{if(HWE==0)
+ {fprintf(outfile,"XW test using robust variance estimator\n\n");}
+ if(HWE==1)
+fprintf(outfile,"XW test using HWE variance estimator\n\n");
+
+
+ }
+
+
+ if (Naivefreq[1]>0&&Naivefreq[1]<1)
+ {
+ /* fprintf(outfile,"RW statistic value = %f\t pvalue = %g df = %d\n\n",RW,pochisq(RW,df),df); */
+
+ if(HWE==1)
+ {
+ if(X==0)
+ {
+
+ /* fprintf(outfile,"WQLS statistic value = %f\t pvalue = %g df = %d\n\n",testval,pochisq(testval,df),df); */
+
+
+fprintf(outfile,"RW statistic value = %f\t pvalue = %g df = %d\n\n",testval,2*pnorms(-1*sqrt(testval)),df);
+
+
+
+}
+else
+ {
+
+ /* fprintf(outfile,"XW statistic value = %f\t pvalue = %g df = %d\n\n",testval,pochisq(testval,df),df); */
+
+fprintf(outfile,"XW statistic value = %f\t pvalue = %g df = %d\n\n",testval,2*pnorms(-1*sqrt(testval)),df);
+
+
+}
+
+
+ RW=testval;
+
+}
+
+ if(HWE==0)
+ {
+ if(X==0)
+ {
+
+ /*fprintf(outfile,"WQLS statistic value = %f\t pvalue = %g df = %d\n\n",testvalrobust,pochisq(testvalrobust,df),df); */
+
+fprintf(outfile,"RW statistic value = %f\t pvalue = %g df = %d\n\n",testvalrobust,2*pnorms(-1*sqrt(testvalrobust)),df);
+
+
+}
+ else
+ {
+ /*fprintf(outfile,"XW statistic value = %f\t pvalue = %g df = %d\n\n",testvalrobust,pochisq(testvalrobust,df),df); */
+
+fprintf(outfile,"XW statistic value = %f\t pvalue = %g df = %d\n\n",testvalrobust,2*pnorms(-1*sqrt(testvalrobust)),df);
+
+
+
+ }
+ RW=testvalrobust;
+ }
+
+
+
+
+
+ /* pval3=pochisq(RW,df); */
+ // printf("OLD RW is %lf \n",RW);
+pval3=2*pnorms(-1*sqrt(RW));
+
+ if (pval3<=0.05) {
+
+ if (Rvector[1]>0) fprintf(outfile,"Frequency of allele %d is increased in the cases (quasi-score associated to this allele is %.4f)\n\n",1,Rvector[1]);
+ if (Rvector[1]<0) fprintf(outfile,"Frequency of allele %d is increased in the controls (quasi-score associated to this allele is %.4f)\n\n",1,Rvector[1]);
+ if (Rvector[1]==0) fprintf(outfile,"Frequency of allele %d is the same in cases and controls (quasi-score associated to this allele is 0)\n\n",1);
+
+ }
+
+
+ for (i=1;i<=M;i++)
+ {if (((Mark[m].Nc)*frequencyCase[i])<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in cases\n",i);
+
+
+ if(Option==2)
+ { if (((Mark[m].Nt)*frequencyControl[i])<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in controls\n",i);}
+
+ if(Option==1)
+ { if ( ( (Mark[m].Nt)*frequencyControl[i] + (Mark[m].Nu)*frequencyUnknown[i] )<5) fprintf(outfile,"The p-value might not be exact because of the small number of type %d alleles in controls\n",i);}
+
+
+ }
+
+
+
+ }
+ else{
+if(X==0) {printf("Computation of the RW statistic is not possible\n\n");}
+ else { printf("Computation of the XW statistic is not possible\n\n");}
+
+ }
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ }
+
+ else { if ((Mark[m].Nc)==0) fprintf(outfile,"\n\nTest statistics are not computed because there are no genotyped cases in the sample for this SNP\n\n");
+ else if ((Mark[m].Nt)==0&&(Mark[m].Nu)==0) fprintf(outfile,"\n\nTest statistics are not computed because there are no genotyped controls in the sample for this SNP\n\n");
+ else {nonpolycount++;
+ fprintf(outfile,"\n\n Test statistics are not computed because the SNP is not polymorphic: minor allele frequency is less than .01 \n\n");}
+
+ }
+
+
+ fprintf(outfile,"\n*****************************************\n");
+ if (negfreq==0)
+ {
+
+ if(Option==2)
+
+
+{
+
+if(frequencyCase[1]==0&&frequencyCase[2]==0)
+ {denomcases=1;}
+
+ if(frequencyControl[1]==0&&frequencyControl[2]==0)
+ {denomcontrols=1;}
+
+
+
+
+ fprintf(outfile,"allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in \n");
+
+ fprintf(outfile,"\t\t cases\t\t\t unaffected controls \t\t\t all sample \n");
+ for (i=1;i<=M;i++)
+ fprintf(outfile,"allele %d : freq = %.4f sd = %.4f\t freq = %.4f sd = %.4f\t\t freq = %.4f sd = %.4f\n",i,frequencyCase[i],sqrt(2*frequencyCase[i]*(1-frequencyCase[i])/denomcases),frequencyControl[i],sqrt(2*frequencyControl[i]*(1-frequencyControl[i])/denomcontrols),frequency[i],sqrt(2*frequency[i]*(1-frequency[i])/denominator));
+ }
+
+
+ if(Option!=2)
+ {
+if(frequencyCase[1]==0&&frequencyCase[2]==0)
+ {denomcases=1;}
+ if(frequencyControl[1]==0&&frequencyControl[2]==0)
+ {denomcontrols=1;}
+if(frequencyUnknown[1]==0&&frequencyUnknown[2]==0)
+ {denomunknown=1;}
+
+
+
+ fprintf(outfile,"allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in \n");
+
+ fprintf(outfile,"\t\t\t cases \t\t unaffected controls \t\t unknown controls \t\t all sample \n");
+ for (i=1;i<=M;i++)
+ fprintf(outfile,"allele %d : freq = %.4f sd = %.4f \t freq = %.4f sd = %.4f \t freq = %.4f sd = %.4f \t freq = %.4f sd = %.4f\n",i,frequencyCase[i],sqrt(2*frequencyCase[i]*(1-frequencyCase[i])/denomcases),frequencyControl[i],sqrt(2*frequencyControl[i]*(1-frequencyControl[i])/denomcontrols),frequencyUnknown[i],sqrt(2*frequencyUnknown[i]*(1-frequencyUnknown[i])/denomunknown),frequency[i],sqrt(2*frequency[i]*(1-frequency[i])/denominator));
+
+
+ }
+
+
+ }
+
+
+
+ else fprintf(outfile,"QL computation of allele frequencies gives negative values....\n\nskipped... \n\nUse naive estimates\n\n");
+
+
+ fprintf(outfile,"*****************************************\n");
+
+
+
+ if(Option==2)
+ { fprintf(outfile,"allele frequency estimates using naive counting in\n");
+ fprintf(outfile,"\t\t cases \t\t unaffected controls \t\t all sample \n");
+ for (i=1;i<=M;i++)
+ fprintf(outfile,"allele %d : freq = %.4f \t\t freq = %.4f \t\t freq = %.4f\n",i,NaivefreqCase[i],NaivefreqControl[i],Naivefreq[i]);
+fprintf(outfile,"*****************************************\n");
+ }
+
+
+
+if(Option!=2)
+ { fprintf(outfile,"allele frequency estimates using naive counting in\n");
+ fprintf(outfile,"\t\tcases \t\t unaffected controls \t\tunknown controls \t all sample \n");
+ for (i=1;i<=M;i++)
+ fprintf(outfile,"allele %d : freq = %.4f \t\t freq = %.4f \t\t freq = %.4f \t\t freq = %.4f\n",i,NaivefreqCase[i],NaivefreqControl[i],NaivefreqUnknown[i],Naivefreq[i]);
+fprintf(outfile,"*****************************************\n");
+ }
+
+
+
+
+
+
+fprintf(outfile,"\n\n\n\n");
+
+
+
+
+
+
+
+ free_dmatrix(freqMatrix,1,M,1,M);
+ free_dvector(frequency,1,M);
+ free_dvector(frequencyCase,1,M);
+ free_dvector(frequencyControl,1,M);
+ free_dvector(frequencyUnknown,1,M);
+ free_dvector(Naive,1,M);
+ free_dvector(NaiveCase,1,M);
+ free_dvector(NaiveControl,1,M);
+ free_dvector(NaiveUnknown,1,M);
+ free_dvector(Naivefreq,1,M);
+ free_dvector(Rvector,1,M);
+ free_dvector(NaivefreqCase,1,M);
+ free_dvector(NaivefreqControl,1,M);
+ free_dvector(NaivefreqUnknown,1,M);
+ free_dmatrix(freqNaive,1,M,1,M);
+ free_dvector(ROBUSTVAR,1,M);
+ free_dvector(YYvector,1,M);
+ free_dvector(Y1vector,1,M);
+
+
+
+fprintf(pvfile,"%d \t %s \t %g \t %g \t %g \n",BIGMARKER,CURRENTSNPNAME,pval1,pval2,pval3);
+
+fprintf(chivfile,"%d \t %s \t %g \t %g \t %g \n",BIGMARKER,CURRENTSNPNAME,RM,RCHI,RW);
+
+
+if(BIGMARKER==1)
+ {TOPPvalues[BIGMARKER]=pval1;
+ TOPPorder[BIGMARKER]=BIGMARKER;
+strncpy(TOPSNPNAME[BIGMARKER],CURRENTSNPNAME,100);
+
+
+TOPPvalues2[BIGMARKER]=pval2;
+ TOPPorder2[BIGMARKER]=BIGMARKER;
+strncpy(TOPSNPNAME2[BIGMARKER],CURRENTSNPNAME,100);
+
+
+TOPPvalues3[BIGMARKER]=pval3;
+ TOPPorder3[BIGMARKER]=BIGMARKER;
+strncpy(TOPSNPNAME3[BIGMARKER],CURRENTSNPNAME,100);
+
+
+
+
+
+}
+ else
+ {if(BIGMARKER<=MAXTOP)
+ {
+
+ TOPPvalues[BIGMARKER]=pval1;
+ TOPPorder[BIGMARKER]=BIGMARKER;
+strncpy(TOPSNPNAME[BIGMARKER],CURRENTSNPNAME,100);
+
+
+ vecsrt2(TOPPvalues,TOPPorder,TOPSNPNAME,BIGMARKER);
+
+
+TOPPvalues2[BIGMARKER]=pval2;
+ TOPPorder2[BIGMARKER]=BIGMARKER;
+strncpy(TOPSNPNAME2[BIGMARKER],CURRENTSNPNAME,100);
+
+
+ vecsrt2(TOPPvalues2,TOPPorder2,TOPSNPNAME2,BIGMARKER);
+
+
+
+
+TOPPvalues3[BIGMARKER]=pval3;
+ TOPPorder3[BIGMARKER]=BIGMARKER;
+strncpy(TOPSNPNAME3[BIGMARKER],CURRENTSNPNAME,100);
+
+
+ vecsrt2(TOPPvalues3,TOPPorder3,TOPSNPNAME3,BIGMARKER);
+
+
+
+
+
+}
+ else
+ {if(pval1<TOPPvalues[MAXTOP])
+ {TOPPvalues[MAXTOP]=pval1;
+ TOPPorder[MAXTOP]=BIGMARKER;
+strncpy(TOPSNPNAME[MAXTOP],CURRENTSNPNAME,100);
+
+ vecsrt2(TOPPvalues,TOPPorder,TOPSNPNAME,MAXTOP);
+
+
+ }
+
+
+if(pval2<TOPPvalues[MAXTOP])
+ {TOPPvalues2[MAXTOP]=pval2;
+ TOPPorder2[MAXTOP]=BIGMARKER;
+strncpy(TOPSNPNAME2[MAXTOP],CURRENTSNPNAME,100);
+vecsrt2(TOPPvalues2,TOPPorder2,TOPSNPNAME2,MAXTOP);
+
+ }
+
+if(pval3<TOPPvalues[MAXTOP])
+ {TOPPvalues3[MAXTOP]=pval3;
+ TOPPorder3[MAXTOP]=BIGMARKER;
+
+strncpy(TOPSNPNAME3[MAXTOP],CURRENTSNPNAME,100);
+vecsrt2(TOPPvalues3,TOPPorder3,TOPSNPNAME3,MAXTOP);
+
+ }
+
+
+
+ }
+ }
+
+
+
+
+
+
+}
+
+
+
+
+
+/*
+ printf("TOTAL MARKERS ANALYZED is %d and nonpolycount is %d\n",BIGMARKER,nonpolycount);
+*/
+
+
+
+
+
+fclose(pvfile);
+
+
+
+
+
+
+top=MAXTOP;
+if(MAXTOP>=BIGMARKER)
+{top=BIGMARKER;}
+
+
+if(X==0 & HWE==0)
+ {fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the MQLS robust test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder[m],TOPSNPNAME[m],TOPPvalues[m]);}
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the Corrected Chi-Squred robust test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder2[m],TOPSNPNAME2[m],TOPPvalues2[m]);}
+
+
+
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of top %d markers with the smallest p-values using the WQLS HWE test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder3[m],TOPSNPNAME3[m],TOPPvalues3[m]);}
+
+
+
+ }
+
+
+
+if(X==0 & HWE==1)
+ {fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the RM test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder[m],TOPSNPNAME[m],TOPPvalues[m]);}
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the RCHI test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder2[m],TOPSNPNAME2[m],TOPPvalues2[m]);}
+
+
+
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of top %d markers with the smallest p-values using the RW test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder3[m],TOPSNPNAME3[m],TOPPvalues3[m]);}
+
+
+
+ }
+
+
+if(X==1 & HWE==0)
+ {fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the XM robust test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder[m],TOPSNPNAME[m],TOPPvalues[m]);}
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the XCHI robust test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder2[m],TOPSNPNAME2[m],TOPPvalues2[m]);}
+
+
+
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of top %d markers with the smallest p-values using the XW robust test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder3[m],TOPSNPNAME3[m],TOPPvalues3[m]);}
+
+
+
+ }
+
+
+
+if(X==1 & HWE==1)
+ {fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the XM HWE test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder[m],TOPSNPNAME[m],TOPPvalues[m]);}
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of the top %d markers with the smallest p-values using the XCHI HWE test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder2[m],TOPSNPNAME2[m],TOPPvalues2[m]);}
+
+
+
+
+fprintf(sigfile,"\n\n############################################### \n\n");
+
+
+fprintf(sigfile,"Below is a list of top %d markers with the smallest p-values using the XW HWE test statistic \n\n",top);
+fprintf(sigfile,"**************************************************\n\n");
+for (m=1;m<=top;m++)
+ {fprintf(sigfile,"MARKER %d: %s has a p-value of %g\n",TOPPorder3[m],TOPSNPNAME3[m],TOPPvalues3[m]);}
+
+
+
+ }
+
+
+
+
+fclose(sigfile);
+
+
+
+
+ fclose(outfile);
+
+
+ return 0;
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+}
+
+
+
+
+
+
+
+
+void readFAM (char *name)
+{
+
+ int all1=0, all2=0,fam=0,famold=1,n=0;
+ int indnumber=0,ind=0,par1,par2,sex,aff;
+ /* char line[MAXLINE];
+ int length=MAXLINE; */
+
+ if((famfile=fopen(name, "r"))==NULL)
+ {
+ printf("Can't open %s\n",name);
+ exit(1);
+ }
+
+
+ famdata[1].N=0;
+ while((fscanf(famfile, "%d %d %*d %*d %d %d",&fam,&ind,&sex,&aff))==4)
+ {
+
+
+ if (fam==famold) famdata[fam].N++;
+ else famdata[fam].N=1;
+ if (fam!=famold && fam!=(famold+1)) {printf("Problems with family %d.\n Family should have following Id numbers from 1 to N\n",fam);
+ exit(1);}
+
+ indnumber++;
+ famold=fam;
+ }
+
+ N=indnumber;
+ F=fam;
+ if (F>MAXFAM) { printf("Number of families exceeds the maximum number of families allowed\n. You should try to change the value of MAXFAM in the CC-QLStest.c file and recompile.\n\n");
+ exit(1);}
+ rewind(famfile);
+
+
+ /* printf("There are %d families and %d study individuals \n",F,N); */
+}
+
+
+void readdataFAM (struct FAM *famdata,FILE *errfile)
+{
+
+ int all1=0, all2=0,i=0,fam=0,famold=1,n=0;
+ int status=0,indnumber=0,ind=0,m=0,j,indiv=0,sex=0;
+ int mycount=0;
+ /* char line[MAXLINE];
+ int length=MAXLINE;
+ */
+
+
+
+
+ while((fscanf(famfile, "%d %d %*d %*d %d %d",&fam,&ind,&sex,&status))==4)
+ {
+ if (fam!=famold && fam!=(famold+1))
+ {
+ printf("Problems with family %d.\n Family should have following Id numbers from 1 to N\n ",fam);
+ exit(1);
+ }
+
+
+ if (fam!=famold) {indnumber=0;
+ NPheno+=famdata[famold].Pheno;
+ NnoPheno+=famdata[famold].NoPheno;
+ }
+
+
+
+
+
+
+
+ if(sex==1)
+ {Nmale++;
+ }
+
+ if(sex==2)
+ {Nfemale++;
+ }
+
+
+
+
+
+ if ((status<0) ||(status>2)) {
+ fprintf(errfile,"individual %d from family %d does not have a phenotype value of 0, 1, or 2 ..will be skipped\n",ind,fam);
+
+
+famdata[fam].INCORRECTPheno++;
+
+ }
+
+
+
+ else if (status==0 || status==1 || status==2)
+ {
+
+
+ if(status==0)
+ {famdata[fam].Unknown++;
+ NUnknown=NUnknown+1;
+ }
+
+ if(status==1)
+ {NUnaffected++;
+ }
+
+if(status==2)
+ {Naffected++;
+ }
+
+
+
+famdata[fam].Pheno++;
+
+
+ }
+
+
+
+
+ indnumber++;
+
+
+
+ famdata[fam].descri[indnumber]=ind;
+
+famdata[fam].AFFEC[indnumber]=status;
+famdata[fam].SEX[indnumber]=sex;
+
+ if ((status<0) ||(status>2))
+ {famdata[fam].AFFEC[indnumber]=-9;}
+
+
+
+
+
+ mycount++;
+ famdata[fam].STUDYID[indnumber]=mycount;
+
+
+
+ fscanf(famfile,"\n");
+ famold=fam;
+ }
+
+
+NPheno+=famdata[fam].Pheno;
+NnoPheno+=famdata[fam].NoPheno;
+
+
+
+/* printf("mycount in reading fam is %d \n",mycount); */
+
+
+
+
+
+printf("There are %d individuals from %d independent families.\n%d of the individuals are affected, %d of the individuals are unaffected, and %d of the individuals are of unknown phenotype.\n\n",NPheno,F,Naffected,NUnaffected,NUnknown);
+
+ if(X==0)
+ {printf("There are %d males and %d females. The prevalence values used in the RM test statistic for males and females are %lf and %lf, respectively. \n",Nmale,Nfemale,KP[1],KP[2]);}
+
+if(X==1)
+ {printf("There are %d males and %d females. The prevalence values used in the XM test statistic for males and females are %lf and %lf, respectively. \n",Nmale,Nfemale,KP[1],KP[2]);}
+
+}
+
+
+
+
+
+/******************************************************
+Reads the kinship coefficients of the individual pairs from the kinshipcoef file and stores the values in the Storekin array. Storekin returns value -1 for pairs of individuals for which no coefficient is available
+*****************************************************/
+void readkincoef(char *name,FILE *errfile, struct FAM *famdata,double ***Storekin)
+{
+ double coef=0;
+ int follow=0,j,i,n,famold=0;
+ long int Id1,Id2;
+ int family=0,ind1=0,ind2=0,indold1=0,indold2=0,Idold1=0,Idold2=0;
+ int err_array[N];
+ int test=0,lim=0;
+
+
+ for (i=1;i<=N;i++)
+ err_array[i]=0;
+ if((idfile=fopen(name, "r"))==NULL)
+ {
+ printf("Can't open %s\n",name);
+ exit(1);
+ }
+for (follow=1;follow<=F;follow++)
+ for (i=1;i<=famdata[follow].Pheno;i++)
+ for (j=i;j<=famdata[follow].Pheno;j++)
+ {
+ Storekin[follow][i][j]=-1;
+ if (i!=j) Storekin[follow][j][i]=-1;
+ }
+
+ while (fscanf(idfile, "%d %ld %ld %lf\n",&family,&Id1,&Id2,&coef)==4)
+ {
+ if (family>F) {
+ printf("Problem with family number %d. Family should have following Id numbers from 1 to N\n",family);
+ exit(1);
+ }
+ if (family==famold) {
+ if (Id1==Idold1) ind1=indold1;
+ else if (Id1==Idold2) ind1=indold2;
+ else ind1=findInd(Id1,family);
+
+ if (Id2==Idold1) ind2=indold1;
+ else if (Id2==Idold2) ind2=indold2;
+ else ind2=findInd(Id2,family);
+ }
+ else { ind1=findInd(Id1,family);
+ ind2=findInd(Id2,family);
+ }
+ famold=family;
+
+ if (ind1!=0 && ind2!=0)
+ {
+ Storekin[family][ind1][ind2]=coef;
+ Storekin[family][ind2][ind1]=coef;
+
+ if(X==1)
+ { if(ind1==ind2&& famdata[family].SEX[ind1]==1)
+ {if(coef!=1)
+ { printf("\nERROR! There is a problem with the kinship coefficient input file. User specfied option -x for an X-chromsome analysis. Individual %ld from family %d is a male and has an inbreeding coefficient value of %lf. All males must have an X-chromosome inbreeding coefficient set to 1 in this kinship coefficient file. Please check the kinship coefficient file and make sure that the file contains only X-chromsome kinship and inbreeding coefficients. \n",Id1,family,coef);
+ exit(1);
+ }}}
+
+ }
+ if (ind1==0)
+ { test=0;
+ for (j=1;j<=lim;j++)
+ if (Id1==err_array[j])
+ {
+ test=1;
+ j=lim+1;
+ }
+
+ if (test==0) {
+ fprintf(errfile,"individual %ld from family %d is in the kinshipcoef file but is not phenotyped or not available from marker data file\n",Id1,family);
+ lim++;
+ err_array[lim]=Id1;
+ }
+ }
+ if (ind2==0)
+ { test=0;
+ for (j=1;j<=lim;j++)
+ if (Id2==err_array[j])
+ {
+ test=1;
+ j=lim+1;
+ }
+ if (test==0) {
+ fprintf(errfile,"individual %ld from family %d is in the kinshipcoef file but is not phenotyped or not available from marker data file\n",Id2,family);
+ lim++;
+ err_array[lim]=Id2;
+ }
+ }
+
+ Idold1=Id1;
+ Idold2=Id2;
+ indold1=ind1;
+ indold2=ind2;
+ }
+}
+
+/******************************************************
+returns the rank of an individual in his family from its family number and Id
+ *****************************************************/
+
+int findInd(Id1,family)
+{
+ int indpas=1;
+ while (indpas<=famdata[family].Pheno)
+ { if (famdata[family].descri[indpas]==Id1) return(indpas);
+ indpas++;
+ }
+ return(0);
+}
+
+
+
+
+
+
+
+int getgenoline_PLINK(struct MARKER *Mark,struct FAM *famdata,FILE *errfile)
+{
+
+int all1=0, all2=0,fam=0,famold=1,n=0;
+ char line[MAXLINE];
+ int length=MAXLINE;
+ int Ngenotypes=0;
+ int status=0,indnumber=0,ind=0,m=0,indiv=0,sex=0;
+ int i,j,k,l;
+ int MYCONTINUE,genovalue,mytyped=0,pers1,pers2,num;
+char str1[200],str2[200],str3[200],str4[200];
+ FILE *ftemp;
+ int **GENOVALUE;
+
+ GENOVALUE=imatrix(0,NPheno,0,2);
+
+
+ fgets(line,length,genofile);
+
+ //strncpy(line2,line,MAXLINE);
+
+
+ MYCONTINUE=0;
+
+ Ngenotypes=0;
+
+
+
+n=sscanf(line,"%s %s %s %s %[^\n]",str1,CURRENTSNPNAME,str3,str4,line);
+
+
+
+
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ /* n=sscanf(line,"%d %[^\n]",&genovalue,line);*/
+ if (n<2) {
+
+ if(BIGMARKER==0)
+ {
+ printf("No marker to test. Please check first line in marker data file\n\n");
+ exit(1);
+ }
+
+ }
+ else {
+
+ Ngenotypes++;
+ GENOVALUE[Ngenotypes][1]=all1;
+ GENOVALUE[Ngenotypes][2]=all2;
+ while (n==3)
+ {
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ if (n>=2) {
+ Ngenotypes++;
+ GENOVALUE[Ngenotypes][1]=all1;
+ GENOVALUE[Ngenotypes][2]=all2;
+ }
+ }
+ }
+
+
+
+
+ if(Ngenotypes!=NPheno)
+ {printf("Program has completed. Tested %d SNPs for association. \n",BIGMARKER);}
+
+
+if(Ngenotypes==NPheno)
+ {MYCONTINUE=1;
+
+ m=1;
+
+
+
+Mark[m].Nball=0;
+ Mark[m].Nc=0;
+ Mark[m].Nt=0;
+ Mark[m].Nu=0;
+
+
+ for(i=1;i<=F;i++)
+ {
+ Mark[m].typed[i].N=0;
+ Mark[m].typed[i].Nc=0;
+ Mark[m].typed[i].Nt=0;
+ Mark[m].typed[i].Nu=0;
+
+ }
+
+
+
+
+ // n=sscanf(line2,"%s %s %s %s %[^\n]",str1,CURRENTSNPNAME,str3,str4,line2);
+
+ num=0;
+for (i=1;i<=F;i++)
+ {for(j=1;j<=famdata[i].N;j++)
+ { //n=sscanf(line2,"%d %d %[^\n]",&all1,&all2,line2);
+ num++;
+ all1=GENOVALUE[num][1];
+ all2=GENOVALUE[num][2];
+
+ if( ( (all1==1 || all1==2) && (all2==1 ||all2==2)) && (famdata[i].MZ[j][1]==-10||(famdata[i].MZ[j][1]>0&&famdata[i].MZ[j][1]!=2)))
+ {
+
+ mytyped++;
+
+
+
+
+
+
+ /*
+GENOTYPED[num]=1;
+ */
+
+
+
+
+
+
+ /* printf("%d %d %d \n",i,j,FINALTYPED[mytyped]); */
+
+
+ }
+
+
+else{all1=0;
+ all2=0;
+ /* GENOTYPED[num]=0; */
+}
+
+
+
+fam=i;
+ indnumber=j;
+ status=famdata[i].AFFEC[j];
+ ind=famdata[i].descri[j];
+
+
+
+ /* sex=famdata[i].SEX[j]; */
+
+
+
+ Mark[m].mark[fam][indnumber][1]=all1;
+ Mark[m].mark[fam][indnumber][2]=all2;
+ Mark[m].mark[fam][indnumber][3]=status;
+ Mark[m].mark[fam][indnumber][4]=ind;
+ /* Mark[m].mark[fam][indnumber][5]=sex;*/
+ if ( (status==0||status==1) && all1!=0 && all2!=0)
+ {
+
+
+
+ Mark[m].typed[fam].N++;
+
+
+ if(status==1)
+ {Mark[m].typed[fam].Nt++;
+ Mark[m].Nt++;
+ }
+
+ if(status==0)
+ {Mark[m].Nu++;
+ Mark[m].typed[fam].Nu++;
+ }
+ }
+ if (status==2 && all1!=0 && all2!=0)
+ {
+ Mark[m].typed[fam].Nc++;
+ Mark[m].typed[fam].N++;
+ Mark[m].Nc++;
+ }
+ if (all1>Mark[m].Nball) Mark[m].Nball=all1;
+ if (all2>Mark[m].Nball) Mark[m].Nball=all2;
+
+ }
+ }
+
+
+
+ }
+
+/*
+printf("There are %d total typed for marker %d \n",mytyped,BIGMARKER);
+*/
+
+ if(MYCONTINUE==1)
+ {
+ TYPEDNUM=mytyped;
+ /* printf("There are %d total typed for marker %d \n",mytyped,BIGMARKER); */
+ }
+
+
+ free_imatrix(GENOVALUE,0,NPheno,0,2);
+
+
+
+ return(MYCONTINUE);
+
+}
+
+
+
+
+
+void readpen (char *name)
+{
+
+ int all1=0, all2=0,fam=0,famold=1,n=0,i=0;
+ int indnumber=0,ind=0, count=0;
+ double val;
+
+ if((penfile=fopen(name, "r"))==NULL)
+ {
+ printf("Can't open %s\n",name);
+ exit(1);
+ }
+
+
+ count=0;
+ while(fscanf(penfile,"%lf",&val) ==1 && count<2)
+ {count++;
+ KP[count]=val;
+ }
+
+ PREVCOUNT=count;
+
+
+ if(PREVCOUNT==0)
+ {printf("Error: Input Prevelance file %s does not have prevelance values. \n",name);
+ exit(1);
+ }
+
+ if(PREVCOUNT==1)
+ {KP[2]=KP[1];
+ }
+
+
+
+}
+
+
+
+
+
+
+void GET_PHENOVECTOR_AND_MZtwins(int fam,int length)
+{
+ int j=0,i=0,k=0;
+ int m=1;
+ double val1=0,val2=0;
+ int MZCOUNT=0,totalcount=0;
+ int numcases=0,numcontrols=0,totalnum=0;
+
+
+
+for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {famdata[fam].MZ[i][1]=-10;
+ /*
+if(Mark[m].mark[fam][i][3]==2)
+ {numcases=numcases+1;}
+if(Mark[m].mark[fam][i][3]==1)
+ {numcontrols=numcontrols+1;}
+ totalnum=totalnum+1;
+ */
+
+ }
+
+
+ for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {
+
+
+
+for (j=i+1;j<=length;j++)
+ {totalcount=totalcount+1;
+if((Storekin[fam][i][j]>=.5) && ((Storekin[fam][i][i]<1. && Storekin[fam][j][j] < 1.) || Storekin[fam][i][j]==1.))
+{
+ val1=(1.0+Storekin[fam][i][i])/2;
+ val2=(1.0+Storekin[fam][j][j])/2;
+
+ if( (val1==Storekin[fam][i][j]) && (val2==Storekin[fam][i][j]) &&(val1==val2)) {
+famdata[fam].MZ[i][1]=1;
+ famdata[fam].MZ[j][1]=2;
+ MZCOUNT=MZCOUNT+1;
+ TOTALMZCOUNT=TOTALMZCOUNT+1;
+
+
+
+
+
+/*** FOR WQLS OF MZ TWINS ***/
+val1=0;
+if(famdata[fam].AFFEC[i]==2)
+{val1=1;}
+
+val2=0;
+if(famdata[fam].AFFEC[j]==2)
+{val2=1;}
+
+
+famdata[fam].MZ[i][2]=(val1+val2)/2;
+
+
+
+
+
+/** FOR MQLS OF MZ TWINS **/
+
+val1=0;
+if(famdata[fam].AFFEC[i]==1)
+{val1=-KP[famdata[fam].SEX[i]];}
+
+if(famdata[fam].AFFEC[i]==2)
+{val1=1-KP[famdata[fam].SEX[i]];}
+
+
+val2=0;
+if(famdata[fam].AFFEC[j]==1)
+{val2=-KP[famdata[fam].SEX[j]];}
+
+if(famdata[fam].AFFEC[j]==2)
+{val2=1-KP[famdata[fam].SEX[j]];}
+
+
+famdata[fam].MZ[i][3]=val1+val2;
+
+
+
+
+
+
+
+
+
+
+}}}
+}
+
+m=1;
+
+ for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {
+
+val1=0;
+
+
+if(famdata[fam].MZ[i][1]!=-10)
+ {
+ val1+=famdata[fam].MZ[i][3];
+
+ }
+
+ else
+ {
+if (famdata[fam].AFFEC[i]==2)
+ {
+ val1+=(Storekin[fam][i][i]+1)*(1-KP[famdata[fam].SEX[i]]);}
+
+
+if (famdata[fam].AFFEC[i]==1)
+ {
+ val1+=(Storekin[fam][i][i]+1)*(-KP[famdata[fam].SEX[i]]);}
+
+
+
+ }
+
+
+
+
+
+ for(j=1;j<=length;j++)
+ {
+ if(j!=i)
+ {
+
+if(famdata[fam].MZ[j][1]!=-10)
+ {
+ val1+=2*Storekin[fam][i][j]*famdata[fam].MZ[j][3];
+
+ }
+
+ else
+ {
+
+
+
+
+ if (famdata[fam].AFFEC[j]==2)
+ {
+ val1+=2*Storekin[fam][i][j]*(1-KP[famdata[fam].SEX[j]]);
+ }
+
+if (famdata[fam].AFFEC[j]==1)
+{val1+=2*Storekin[fam][i][j]*(-KP[famdata[fam].SEX[j]]);}
+
+
+
+/*
+printf("fam is %d and individual is %d with relative %d with affection status %d (and kinship coef %lf), and new value is %lf\n",fam,i,j,Mark[m].mark[fam][j][3],Storekin[fam][i][j],val1);
+
+*/
+
+}
+
+
+ }
+ }
+
+
+
+ famdata[fam].AVEC[i][1]=val1;
+
+
+ }
+
+
+
+
+
+}
+
+
+
+
+
+
+void readGenotypes(int fam,int m,int length,double **cholaug,double **cholaugCase,double **cholaugControl,double **cholaugUnknown,int *MissingVec,int miss,double **kincoefmatrix,double **kincoefMatrixCase,double **kincoefmatrixControl,double **kincoefmatrixUnknown)
+{
+ int all1=0, all2=0,j=0,i=0,family=0,follow=0;
+ int a1=0,tot=1,controls=1,cases=1,unknown=1;
+ int nbc1=0,nbc2=0,nbt1=0,nbt2=0,nb1=0,nb2=0,nbu1=0,nbu2=0;
+ double val1=0;
+ int k,num;
+
+ k=m;
+
+ /* IF THERE ARE MZ TWINS THEN REMOVING ONE OF THEM */
+
+ if(TOTALMZCOUNT>0)
+ { for (j=1;j<=length;j++) //length is famdata[fam].NPheno
+ {
+ if(famdata[fam].MZ[j][1]>0&&famdata[fam].MZ[j][1]==2)
+ {
+ k=m;
+
+if(Mark[k].mark[fam][j][3]==2&&Mark[k].mark[fam][j][1]>0&& Mark[k].mark[fam][j][2]>0)
+ {Mark[k].typed[fam].Nc--;
+ Mark[k].Nc--;}
+
+if(Mark[k].mark[fam][j][3]==1&&Mark[k].mark[fam][j][1]>0&& Mark[k].mark[fam][j][2]>0)
+ {Mark[k].typed[fam].Nt--;
+ Mark[k].Nt--;
+}
+
+if(Mark[k].mark[fam][j][1]>0&& Mark[k].mark[fam][j][2]>0)
+ {Mark[k].typed[fam].N--;}
+
+
+Mark[k].mark[fam][j][1]=0;
+Mark[k].mark[fam][j][2]=0;
+
+
+
+
+ }}}
+
+
+
+
+
+ for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {
+
+
+
+ /* REMOVING INDIVIDUALS WITH UNRECOGNIZED PHENOTYPES */
+if ((Mark[k].mark[fam][i][3]<0) ||(Mark[k].mark[fam][i][3]>2)) {
+
+printf("fam %d and individual %d has an unrecognized phenotype of %d \n",fam,i,Mark[k].mark[fam][i][3]);
+
+if(Mark[k].mark[fam][i][3]==2&&Mark[k].mark[fam][i][1]>0&& Mark[k].mark[fam][i][2]>0)
+ {Mark[k].typed[fam].Nc--;
+ Mark[k].Nc--;}
+
+if(Mark[k].mark[fam][i][3]==1&&Mark[k].mark[fam][i][1]>0&& Mark[k].mark[fam][i][2]>0)
+ {Mark[k].typed[fam].Nt--;
+ Mark[k].Nt--;
+}
+
+
+if(Mark[k].mark[fam][i][3]==0&&Mark[k].mark[fam][i][1]>0&& Mark[k].mark[fam][i][2]>0)
+ {Mark[k].typed[fam].Nu--;
+ Mark[k].Nu--;
+}
+
+
+
+if(Mark[k].mark[fam][i][1]>0&& Mark[k].mark[fam][i][2]>0)
+ {Mark[k].typed[fam].N--;}
+
+
+
+
+
+ Mark[m].mark[fam][i][1]=0;
+ Mark[m].mark[fam][i][2]=0;
+
+
+
+
+
+
+
+
+
+ }
+
+
+/* OPTION 2 REMOVING UNKNOWN PHENOTYPED INDIVIDUALS */
+
+ if( (Option==2) && (Mark[m].mark[fam][i][3]==0))
+ {
+
+
+
+ if(Mark[k].mark[fam][i][1]>0&& Mark[k].mark[fam][i][2]>0)
+ {
+
+Mark[k].typed[fam].Nu--;
+ Mark[k].Nu--;
+
+ Mark[k].typed[fam].N--;}
+
+
+ Mark[m].mark[fam][i][1]=0;
+ Mark[m].mark[fam][i][2]=0;
+
+ }
+
+
+
+ }
+
+
+
+
+for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {num=famdata[fam].STUDYID[i];
+if (Mark[m].mark[fam][i][1]!=0 && Mark[m].mark[fam][i][2]!=0)
+ {FINALCOUNTED++;
+ FINALTYPED[FINALCOUNTED]=famdata[fam].STUDYID[i];
+GENOTYPED[num]=1;
+D[FINALCOUNTED]=num;
+Place[D[FINALCOUNTED]]=FINALCOUNTED;
+ }
+ else
+ {GENOTYPED[num]=0;
+ }
+
+ }
+
+
+
+
+for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {
+
+
+
+val1=0;
+ if (Mark[m].mark[fam][i][1]!=0 && Mark[m].mark[fam][i][2]!=0)
+ {
+
+
+
+ nb1++;
+ nb2=nb1;
+ if (Storekin[fam][i][i]==-1) {
+ printf("No inbreeding coefficient for individual %d from family %d. Please check...\n\n",i,fam);
+ exit(1);
+ }
+
+ kincoefmatrix[nb1][nb1]=Storekin[fam][i][i]+1;
+
+
+
+ if (Mark[m].mark[fam][i][3]==2)
+ {
+ nbc1++;
+ nbc2=nbc1;
+ kincoefMatrixCase[nbc1][nbc1]=kincoefmatrix[nb2][nb1];
+
+
+
+ for (j=i+1;j<=length;j++)
+ {
+ if (Storekin[fam][i][j]==-1) {
+ printf("No kinship coefficient between individual %d and individual %d from family %d. Please check...\n\n",famdata[fam].descri[i],famdata[fam].descri[j],fam);
+ exit(1);
+ }
+
+ if (Mark[m].mark[fam][j][1]!=0 && Mark[m].mark[fam][j][2]!=0)
+ {
+ nb2++;
+ kincoefmatrix[nb1][nb2]=2*Storekin[fam][i][j];
+ kincoefmatrix[nb2][nb1]=kincoefmatrix[nb1][nb2];
+
+
+
+
+
+ if (Mark[m].mark[fam][j][3]==2)
+ {
+ nbc2++;
+ kincoefMatrixCase[nbc1][nbc2]=kincoefmatrix[nb1][nb2];
+ kincoefMatrixCase[nbc2][nbc1]=kincoefMatrixCase[nbc1][nbc2];
+ }
+ }
+ }
+
+
+ cholaug[tot][M+1]=2;
+
+
+cholaugCase[cases][M+1]=2;
+
+
+
+
+
+ cholaug[tot][M+2]=2;
+ cholaugCase[cases][M+2]=2;
+
+
+ if(famdata[fam].MZ[i][1]!=-10)
+ {cholaug[tot][M+2]=2*famdata[fam].MZ[i][2];
+ cholaugCase[cases][M+2]=2*famdata[fam].MZ[i][2];
+ /* printf("allocated the MZ case\n"); */
+
+}
+
+
+
+
+
+ for (a1=1;a1<=M;a1++)
+
+ cholaug[tot][a1]=0;
+
+ for(a1=1;a1<=M;a1++)
+ {
+ if (Mark[m].mark[fam][i][1]==a1) cholaug[tot][a1]++;
+ if (Mark[m].mark[fam][i][2]==a1) cholaug[tot][a1]++;
+ cholaugCase[cases][a1]=cholaug[tot][a1];
+
+
+ }
+ cases++;
+ tot++;
+
+ }
+
+
+
+
+
+ else if(Mark[m].mark[fam][i][3]==1)
+ {
+ nbt1++;
+ nbt2=nbt1;
+ kincoefmatrixControl[nbt1][nbt1]=kincoefmatrix[nb2][nb1];
+
+
+
+
+
+
+for (j=i+1;j<=length;j++)
+ {
+ if (Mark[m].mark[fam][j][1]!=0 && Mark[m].mark[fam][j][2]!=0)
+ {
+ nb2++;
+ kincoefmatrix[nb1][nb2]=2*Storekin[fam][i][j];
+ kincoefmatrix[nb2][nb1]=kincoefmatrix[nb1][nb2];
+
+
+
+
+
+ if (Mark[m].mark[fam][j][3]==1)
+ {
+ nbt2++;
+ kincoefmatrixControl[nbt1][nbt2]=kincoefmatrix[nb1][nb2];
+ kincoefmatrixControl[nbt2][nbt1]=kincoefmatrixControl[nbt1][nbt2];
+ }
+ }
+ }
+
+ cholaug[tot][M+1]=2;
+ cholaugControl[controls][M+1]=2;
+
+ cholaug[tot][M+2]=0;
+ cholaugControl[controls][M+2]=0;
+
+
+
+if(famdata[fam].MZ[i][1]!=-10)
+ {
+cholaug[tot][M+2]=2*famdata[fam].MZ[i][2];
+ cholaugControl[controls][M+2]=2*famdata[fam].MZ[i][2];
+ /* printf("allocated the MZ control\n"); */
+ }
+
+
+
+
+
+
+
+ for (a1=1;a1<=M;a1++) cholaug[tot][a1]=0;
+ for (a1=1;a1<=M;a1++)
+ {
+ if (Mark[m].mark[fam][i][1]==a1) cholaug[tot][a1]++;
+ if (Mark[m].mark[fam][i][2]==a1) cholaug[tot][a1]++;
+ cholaugControl[controls][a1]=cholaug[tot][a1];
+
+
+
+ }
+ controls++;
+ tot++;
+
+ }
+
+
+
+ else if(Mark[m].mark[fam][i][3]==0)
+ {
+ nbu1++;
+ nbu2=nbu1;
+ kincoefmatrixUnknown[nbu1][nbu1]=kincoefmatrix[nb2][nb1];
+
+
+
+
+
+
+for (j=i+1;j<=length;j++)
+ {
+ if (Mark[m].mark[fam][j][1]!=0 && Mark[m].mark[fam][j][2]!=0)
+ {
+ nb2++;
+ kincoefmatrix[nb1][nb2]=2*Storekin[fam][i][j];
+ kincoefmatrix[nb2][nb1]=kincoefmatrix[nb1][nb2];
+
+
+
+
+
+ if (Mark[m].mark[fam][j][3]==0)
+ {
+ nbu2++;
+ kincoefmatrixUnknown[nbu1][nbu2]=kincoefmatrix[nb1][nb2];
+ kincoefmatrixUnknown[nbu2][nbu1]=kincoefmatrixUnknown[nbu1][nbu2];
+ }
+ }
+ }
+
+ cholaug[tot][M+1]=2;
+ cholaugUnknown[unknown][M+1]=2;
+
+ cholaug[tot][M+2]=0;
+ cholaugUnknown[unknown][M+2]=0;
+
+
+
+if(famdata[fam].MZ[i][1]!=-10)
+ {
+cholaug[tot][M+2]=2*famdata[fam].MZ[i][2];
+ cholaugUnknown[unknown][M+2]=2*famdata[fam].MZ[i][2];
+ /* printf("allocated the MZ control\n"); */
+ }
+
+
+
+
+
+
+
+ for (a1=1;a1<=M;a1++) cholaug[tot][a1]=0;
+ for (a1=1;a1<=M;a1++)
+ {
+ if (Mark[m].mark[fam][i][1]==a1) cholaug[tot][a1]++;
+ if (Mark[m].mark[fam][i][2]==a1) cholaug[tot][a1]++;
+ cholaugUnknown[unknown][a1]=cholaug[tot][a1];
+
+ }
+ unknown++;
+ tot++;
+
+
+
+
+
+ }
+
+
+ }
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ else
+ {
+ follow++;
+ /* MissingVec[follow]=i; */
+ }
+
+
+ }
+
+
+ /*
+ if ((cases-1)!=Mark[m].typed[fam].Nc || (controls-1)!=Mark[m].typed[fam].Nt) {printf("Problems while rereading the data file...\n");
+ exit(1);
+ }
+ if (follow!=miss) {printf("problem with missing data in family %d follow=%d miss=%d\n",fam,follow,miss);
+ exit(1);}
+ */
+
+
+
+ /** This is to get the phenotype vector for MQLS statistic **/
+
+
+ tot=tot--;
+ /*printf("tot is %d and about to get matrix now\n",tot); */
+
+for(i=1;i<=tot;i++)
+ {for(j=1;j<=tot;j++)
+ {if(i==j)
+ {cholaug[i][M+3+j]=1;}
+else
+{cholaug[i][M+3+j]=0;}
+ }
+ }
+
+
+/*for(i=1;i<=tot;i++)
+ {for(j=1;j<=(M+3+tot);j++)
+ {printf("%lf ",cholaug[i][j]);}
+ printf("\n");
+ }
+*/
+
+
+ tot=1;
+ nb1=0;
+ for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {val1=0;
+ if (Mark[m].mark[fam][i][1]!=0 && Mark[m].mark[fam][i][2]!=0)
+ {nb1++;
+
+ if(Missing==1)
+ {val1=famdata[fam].AVEC[i][1];}
+ else
+ {
+if(famdata[fam].MZ[i][1]!=-10)
+ {
+ val1+=famdata[fam].MZ[i][3];
+
+ }
+
+ else
+ {
+if (Mark[m].mark[fam][i][3]==2)
+ {
+ val1+=kincoefmatrix[nb1][nb1]*(1-KP[famdata[fam].SEX[i]]);}
+
+
+if (Mark[m].mark[fam][i][3]==1)
+ {
+ val1+=kincoefmatrix[nb1][nb1]*(-KP[famdata[fam].SEX[i]]);}
+
+ }
+
+
+
+
+ nb2=0;
+ for(j=1;j<=length;j++)
+ {
+if (Mark[m].mark[fam][j][1]!=0 && Mark[m].mark[fam][j][2]!=0)
+ {nb2++;
+ if(j!=i)
+ {
+
+if(famdata[fam].MZ[j][1]!=-10)
+ {
+ val1+=kincoefmatrix[nb1][nb2]*famdata[fam].MZ[j][3];
+
+ }
+
+ else
+ {
+
+
+
+ if (Mark[m].mark[fam][j][3]==2)
+ {val1+=kincoefmatrix[nb1][nb2]*(1-KP[famdata[fam].SEX[j]]); }
+
+ if (Mark[m].mark[fam][j][3]==1)
+ {val1+=kincoefmatrix[nb1][nb2]*(-KP[famdata[fam].SEX[j]]);}
+ }
+ }
+ }
+ }
+
+ }
+
+
+
+ /*
+
+
+ if(tot==1&&fam==2)
+ {val1=2;
+printf("in total\n");}
+
+
+ if(tot==2&&fam==2)
+ {val1=1+(-Kp/(1-Kp));
+printf("in total\n");}
+
+
+ printf("fam is %d and person counter is %d and MQLS val is %f and WQLS val is %f \n",fam,tot,val1,cholaug[tot][M+2]/2);
+
+ */
+
+
+cholaug[tot][M+3]=2*val1;
+
+
+
+
+/*
+ printf("Weight value for individual %d from fam %d using genotyped individuals only is %lf and using all individuals is %lf \n",i,fam,val1,famdata[fam].AVEC[i][1]);
+
+*/
+
+
+
+
+
+/*
+ printf("family is %d, person is %d and affected is %d and value is %.3lf, status is %.2lf and allelecount is %.2lf and total alleles is %.2lf \n",fam,i,Mark[m].mark[fam][i][3],cholaug[tot][M+3],cholaug[tot][M+2],cholaug[tot][1],cholaug[tot][M+1]);
+*/
+
+ tot++;
+ }
+
+ }
+
+ /*
+ printf("\n\n");
+ */
+ }
+
+
+/******************************************************
+Computes the frequency estimates using the quasilikelihood approach
+*****************************************************/
+void alleleFreq(double **cholaug,double *frequency,int size, double *denominator)
+{
+ int i=0, j=0;
+ double pasden=0,numerator=0;
+
+
+
+ for(i=1; i<=size; i++){
+ pasden=pasden+(cholaug[i][M+1])*(cholaug[i][M+1]);
+
+ }
+
+ for(j=1; j<=M; j++)
+ {
+ for(i=1; i<=size; i++)
+ {
+ numerator=numerator+cholaug[i][M+1]*cholaug[i][j];
+ }
+ frequency[j]+=numerator;
+ numerator=0;
+ }
+
+ *denominator+=pasden;
+}
+
+/******************************************************
+Computes the frequency estimates using the naive counting
+*****************************************************/
+void naiveCount(double **cholaug,double *Naive,double *Naivefreq,int size)
+{
+ int i=0, j=0;
+ double sum=0, contC=0;
+
+ for(i=1; i<=M; i++){
+ contC=0;
+ for(j=1; j<=size; j++)
+ { sum+=cholaug[j][i];
+ if (cholaug[j][M+2]==2)
+ contC+=cholaug[j][i];
+
+ }
+ Naive[i]+=contC;
+ Naivefreq[i]+=sum;
+ sum=0;
+
+ }
+
+}
+/******************************************************
+To get from counts to frequencies
+*****************************************************/
+ void getfrequency(double *Naivefreq,double *NaivefreqCase,double *NaivefreqControl,double *NaivefreqUnknown,double *frequency,double *frequencyCase,double *frequencyControl,double *frequencyUnknown,double denominator,double denomcases,double denomcontrols,double denomunknown,int Nall,int Ncase,int Ncontrol,int Nunknown)
+{
+ int i;
+
+ for (i=1;i<=M;i++)
+ {
+
+ if(Nall>0)
+ { Naivefreq[i]/=(2*Nall);}
+
+ if(Ncase>0)
+ {NaivefreqCase[i]/=(2*Ncase);}
+
+ if(Ncontrol>0)
+ {NaivefreqControl[i]/=(2*Ncontrol);}
+ if(Nunknown>0)
+ { NaivefreqUnknown[i]/=(2*Nunknown);}
+
+if(denominator>0)
+ {
+ frequency[i]/=denominator;}
+
+if(denomcases>0)
+ {
+ frequencyCase[i]/=denomcases;
+ }
+
+ if(denomcontrols>0)
+ {
+ frequencyControl[i]/=denomcontrols;}
+
+if(denomunknown>0)
+ {
+frequencyUnknown[i]/=denomunknown;
+ }
+
+ }
+}
+/******************************************************
+Modify the cholaug matrix such as the M-1 first columns are equal to C-t*(Y-mu) instead of C-t*Y
+*****************************************************/
+void modifcholaug(double **cholent,double **cholaug,double **chol,double *frequency,int size)
+{
+
+
+ int i,j,k;
+
+ for (i=1;i<=size;i++)
+ for (j=1;j<=M+3;j++)
+ {
+
+ if (j<M) cholaug[i][j]=cholent[i][j]-2*frequency[j];
+ else cholaug[i][j]=cholent[i][j];
+ for (k=1;k<i;k++)
+ cholaug[i][j]-=cholaug[k][j]*chol[k][i];
+ cholaug[i][j]/=chol[i][i];
+
+ }
+}
+/******************************************************
+Build the freqMatrix (a function of allele frequencies) required for the score computation in the multiallelic case
+*****************************************************/
+int makeFreqMat(double **freqMatrix,double *frequency)
+{
+ int i,j,k=0,l=0,Mpas=M;
+ int *Followfreq;
+ double **transMat,**freqPasMat;
+ double **cholm,**invcholm;
+
+ Followfreq=ivector(1,M-1);
+
+ for (i=1;i<=M-1;i++)
+ {
+ Followfreq[i]=1;
+ if (frequency[i]==0)
+ { Mpas--;
+ Followfreq[i]=0;
+ }
+ }
+
+ if(Mpas==1)
+ {
+ for(i=1;i!=M;i++)
+ for(j=1;j!=M;j++)
+ freqMatrix[i][j]=0;
+ return 0;
+ }
+
+ transMat=dmatrix(1,Mpas-1,1,Mpas-1);
+ cholm=dmatrix(1,Mpas-1,1,Mpas-1);
+ invcholm=dmatrix(1,Mpas-1,1,Mpas-1);
+ freqPasMat=dmatrix(1,Mpas-1,1,Mpas-1);
+
+ for (i=1;i<=Mpas-1;i++)
+ for (j=1;j<=Mpas-1;j++)
+ {
+ transMat[i][j]=0;
+ cholm[i][j]=0;
+ invcholm[i][j]=0;
+ freqPasMat[i][j]=0;
+ }
+
+ for (i=1;i<=M-1;i++)
+ if (Followfreq[i]==1)
+ { k++;
+ transMat[k][k]=frequency[i]*(1-frequency[i]);
+ l=k;
+ for (j=i+1;j<=M-1;j++)
+ if (Followfreq[j]==1)
+ {
+ l++;
+ transMat[k][l]=-frequency[i]*frequency[j];
+ transMat[l][k]=transMat[k][l];
+ }
+ }
+ //cholesky of transMat. cholm=upper triangle
+
+ for (i=1; i<=Mpas-1; i++) {
+ cholm[i][i] = transMat[i][i];
+ for (k=1; k<i; k++)
+ cholm[i][i] -= cholm[k][i]*cholm[k][i];
+ if (cholm[i][i] <= 0) {
+ return(1);
+
+ fprintf(errfile,"\ncholesky of the frequency matrix failed\nERROR: non-positive definite matrix!\n Might be due to missing allele numbers (alleles should be numbered from 1 to M without gaps)\n");
+ }
+
+ cholm[i][i] = sqrt(cholm[i][i]);
+
+ for (j=i+1; j<=Mpas-1; j++) {
+ cholm[i][j] = transMat[i][j];
+ for (k=1; k<i; k++)
+ cholm[i][j] -= cholm[k][i]*cholm[k][j];
+ cholm[i][j] /= cholm[i][i];
+
+ }
+ }
+
+ //inverse of cholm
+
+ for (i=Mpas-1;i>0;i--)
+ {invcholm[i][i]=1/cholm[i][i];
+ for (j=i-1;j>0;j--)
+ {for (k=j+1;k<=i;k++)
+ invcholm[j][i]-=cholm[j][k]*invcholm[k][i];
+ invcholm[j][i]/=cholm[j][j];
+ invcholm[i][j]=0;
+ }
+ }
+
+
+ //inverse of transMat
+
+ for (i=1;i<=Mpas-1;i++)
+ for (j=1;j<=Mpas-1;j++)
+ for (k=1;k<=Mpas-1;k++)
+ {
+ freqPasMat[i][j]+=invcholm[i][k]*invcholm[j][k];
+
+
+ }
+
+ k=0;
+ for (i=1;i<=M-1;i++)
+ { if (Followfreq[i]==1)
+ { k++;
+ freqMatrix[i][i]=freqPasMat[k][k];
+ l=k;
+ for (j=i+1;j<=M-1;j++)
+ {
+ if (Followfreq[j]==1)
+ {
+ l++;
+ freqMatrix[i][j]=freqPasMat[k][l];
+ freqMatrix[j][i]=freqMatrix[i][j];
+ }
+ else {
+ freqMatrix[i][j]=0;
+ freqMatrix[j][i]=0;
+ }
+ }
+ }
+
+ else { freqMatrix[i][i]=0;
+ for (j=i+1;j<=M-1;j++)
+ {
+ freqMatrix[i][j]=0;
+ freqMatrix[j][i]=0;
+ }
+ }
+ }
+/* printf(""); */
+
+
+ /* Free the temp matrices */
+ free_dmatrix( transMat,
+ 1, Mpas - 1,
+ 1, Mpas - 1);
+
+ free_dmatrix( cholm,
+ 1, Mpas - 1,
+ 1, Mpas - 1);
+
+ free_dmatrix( invcholm,
+ 1, Mpas - 1,
+ 1, Mpas - 1);
+
+ free_dmatrix( freqPasMat,
+ 1, Mpas - 1,
+ 1, Mpas - 1);
+
+
+
+ free_ivector(Followfreq,1,M-1);
+
+
+
+
+ return 0;
+}
+/******************************************************
+Computes the information components required for the pseudo-score test
+*****************************************************/
+void comput_info_score(double **cholaug,double **freqMatrix,double *infoQL_rr,double *infoQL_rf,double *infoQL_ff,double *Rvector,int size)
+{
+ int i,j;
+ double info_rr=0,info_rf=0,info=0,info_ff=0;
+
+
+ for (i=1;i<=size;i++)
+ {info_rr+=cholaug[i][M+2]*cholaug[i][M+2];
+ info_rf+=cholaug[i][M+2]*cholaug[i][M+1];
+ info_ff+=cholaug[i][M+1]*cholaug[i][M+1];
+ for (j=1;j<=M-1;j++)
+ Rvector[j]+=cholaug[i][M+2]*cholaug[i][j];
+ }
+
+ *infoQL_rr+=info_rr;
+ *infoQL_rf+=info_rf;
+ *infoQL_ff+=info_ff;
+
+}
+/******************************************************
+Computes the pseudo-score test
+*****************************************************/
+
+void from_info2_score(double **freqMatrix,double infoQL_rr,double infoQL_rf,double infoQL_ff,double *Rvector,double *testval)
+{
+ int i,j;
+ double info=0,score=0;
+
+ info=infoQL_rr - infoQL_rf*infoQL_rf/infoQL_ff;
+
+ for (i=1;i<=M-1;i++)
+ for (j=1;j<=M-1;j++)
+ score+=Rvector[i]*Rvector[j]/info*freqMatrix[i][j]/2;
+
+ *testval=score;
+}
+
+/******************************************************
+Computes the corrected chi2 test
+*****************************************************/
+void from_info2_chi2(double info_rr, double info_rf, double info_ff, double *Naive,double *Naivefreq,double **freqNaive,double *chi2val,int Nall,int Ncase)
+{
+ int i,j;
+ double chi2old=0;
+ double freqpas=0,corrfactor=0;
+
+
+ corrfactor=2/((info_rr-2*Ncase*(double)info_rf/Nall+(double)Ncase/Nall*(double)Ncase/Nall*info_ff));
+
+ for (i=1;i<=M-1;i++)
+ for (j=1;j<=M-1;j++)
+ chi2old+=(Naive[i]-2*Ncase*Naivefreq[i])*(Naive[j]-2*Ncase*Naivefreq[j])*freqNaive[i][j];
+
+ *chi2val=chi2old*corrfactor;
+
+}
+/******************************************************
+Computes the information components required to derive the correction factor for the chi2 test
+*****************************************************/
+void comput_info_chi2(double **kincoefMatrix,double **cholaug,double *info_rr,double *info_rf,double *info_ff,int size)
+{ int i,j;
+ double infopas_rr=0,infopas_rf=0,infopas_ff=0;
+
+ for (i=1;i<=size;i++)
+ { for (j=1;j<=size;j++)
+ {
+ infopas_rr+=cholaug[i][M+2]*kincoefMatrix[i][j]*cholaug[j][M+2];
+ infopas_rf+=cholaug[i][M+2]*kincoefMatrix[i][j]*cholaug[j][M+1];
+ infopas_ff+=cholaug[i][M+1]*kincoefMatrix[i][j]*cholaug[j][M+1];
+ }
+
+ }
+*info_rr+=infopas_rr;
+*info_rf+=infopas_rf;
+*info_ff+=infopas_ff;
+
+}
+/******************************************************
+Computes the information components required for the pseudo-score test for MQLS
+*****************************************************/
+
+
+void comput_info_scoreMQLS(double **cholaug,double **freqMatrix,double *infoQL_rr,double *infoQL_rf,double *infoQL_ff,double *Rvector,int size)
+{
+ int i,j;
+ double info_rr=0,info_rf=0,info=0,info_ff=0;
+
+
+ for (i=1;i<=size;i++)
+ {info_rr+=cholaug[i][M+3]*cholaug[i][M+3];
+ info_rf+=cholaug[i][M+3]*cholaug[i][M+1];
+ info_ff+=cholaug[i][M+1]*cholaug[i][M+1];
+ for (j=1;j<=M-1;j++)
+ Rvector[j]+=cholaug[i][M+3]*cholaug[i][j];
+ }
+
+ *infoQL_rr+=info_rr;
+ *infoQL_rf+=info_rf;
+ *infoQL_ff+=info_ff;
+
+}
+
+
+void vecsrt(double *d, int *M,int n)
+{
+ int k,j,i;
+ double p;
+ int place;
+
+ for (i=1;i<n;i++) {
+ p=d[k=i];
+ for (j=i+1;j<=n;j++)
+ if (d[j] <= p)
+ {p=d[k=j];
+ place=M[k=j];
+ }
+ if (k != i) {
+ d[k]=d[i];
+ d[i]=p;
+ M[k]=M[i];
+ M[i]=place;
+ }
+ }
+}
+
+
+
+
+void get_EMPIRICAL_MATRIX(FILE *errfile)
+{
+
+int all1=0, all2=0,fam=0,famold=1,n=0;
+ char line[MAXLINE];
+ int length=MAXLINE;
+ int Ngenotypes=0;
+ int status=0,indnumber=0,ind=0,m=0,indiv=0,sex=0;
+ int i,j,k,l,num1;
+ int MYCONTINUE=0;
+ double freqest,val1;
+ double *geno;
+ int genovalue;
+char str1[200],str2[200],str3[200],str4[200];
+ FILE *mykinfile;
+
+
+ MARKERCOUNT=0;
+
+
+
+ fgets(line,length,genofile);
+
+ // strncpy(line2,line,MAXLINE);
+
+
+
+
+ Ngenotypes=0;
+
+
+
+n=sscanf(line,"%s %s %s %s %[^\n]",str1,str2,str3,str4,line);
+
+
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ /* n=sscanf(line,"%d %[^\n]",&genovalue,line);*/
+ if (n<2) {
+
+ if(BIGMARKER==0)
+ {
+ printf("No marker to test. Please check first line in marker data file\n\n");
+ exit(1);
+ }
+
+ }
+ else {
+ Ngenotypes++;
+
+ while (n==3)
+ {
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ if (n>=2) {
+ Ngenotypes++;
+
+ }
+ }
+ }
+
+
+
+
+
+ if(Ngenotypes!=NPheno)
+ {printf("Error in Genotype File: The number of individuals in the phenotype fiel and the number of genotypes for each SNP must be the same. There are %d study individuals from the phenotype file but there are %d genotypes for the first marker that was read from the genotype file \n",NPheno,Ngenotypes);
+ exit(1);
+ }
+
+
+
+
+
+geno=dvector(0,NPheno);
+ZMAT=dmatrix(0,NPheno,0,NPheno);
+NMARKERS=imatrix(0,NPheno,0,NPheno);
+ FINALTYPED=ivector(0,NPheno);
+
+
+
+
+ for(i=1;i<=NPheno;i++)
+ {for(j=1;j<=NPheno;j++)
+ {
+
+ ZMAT[i][j]=0;
+ NMARKERS[i][j]=0;
+
+
+
+ }}
+
+
+
+
+
+ rewind(genofile);
+
+
+
+
+
+ MYCONTINUE=1;
+ while(MYCONTINUE==1)
+ {
+
+ fgets(line,length,genofile);
+
+ //strncpy(line2,line,MAXLINE);
+
+
+
+
+
+
+
+
+ Ngenotypes=0;
+
+
+
+n=sscanf(line,"%s %s %s %s %[^\n]",str1,str2,str3,str4,line);
+
+
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ /* n=sscanf(line,"%d %[^\n]",&genovalue,line);*/
+ if (n<2) {
+
+ if(BIGMARKER==0)
+ {
+ printf("No marker to test. Please check first line in marker data file\n\n");
+ exit(1);
+ }
+
+ }
+ else {
+ Ngenotypes++;
+
+
+ if( (all1==1||all1==2) && (all2==1||all2==2))
+ {
+ geno[Ngenotypes]=.5*(4-all1-all2);
+
+
+ }
+
+ else{geno[Ngenotypes]=-9;}
+
+
+ while (n==3)
+ {
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ if (n>=2) {
+ Ngenotypes++;
+
+ if( (all1==1||all1==2) & (all2==1||all2==2) &&Ngenotypes<=NPheno)
+ {
+ geno[Ngenotypes]=.5*(4-all1-all2);
+
+
+ }
+
+ else{geno[Ngenotypes]=-9;}
+
+
+
+
+
+ }
+ }
+ }
+
+
+
+
+
+if(MARKERCOUNT>MAX_SNPS_FOR_MATRIX)
+ {MYCONTINUE=0;}
+
+ if(Ngenotypes!=NPheno)
+ {MYCONTINUE=0;
+
+ if(Ngenotypes>2)
+ {printf("Error in Genotype File: There are %d study individuals from the phenotype file but there are only %d genotypes for marker %d \n",NPheno,Ngenotypes,MARKERCOUNT+1);
+ exit(1);
+ }
+
+
+
+
+ }
+
+
+
+
+
+
+if(Ngenotypes==NPheno&&MARKERCOUNT<=MAX_SNPS_FOR_MATRIX)
+ {
+MYCONTINUE=1;
+ MARKERCOUNT++;
+
+
+
+
+num1=0;
+ freqest=0;
+for(i=1;i<=NPheno;i++)
+ {if(geno[i]>=0)
+ {num1=num1+1;
+ freqest=freqest+geno[i];
+ }}
+ freqest=freqest/(num1);
+
+
+
+ num1=0;
+if(freqest<.99 && freqest>.01)
+ {
+
+for(i=1;i<=NPheno;i++)
+ {
+ for(k=i;k<=NPheno;k++)
+ {if(geno[i]>=0&&geno[k]>=0)
+ {
+ val1=((geno[i]-freqest)*(geno[k]-freqest))/(freqest*(1-freqest));
+
+ZMAT[i][k]+=val1;
+ NMARKERS[i][k]++;
+
+
+ }}}}
+
+
+
+
+
+
+
+
+
+
+ }
+
+
+
+ }
+
+
+
+
+for(i=1;i<=NPheno;i++)
+ {
+ for(k=i;k<=NPheno;k++)
+ {
+ if(NMARKERS[i][k]>0)
+ { ZMAT[i][k]/=NMARKERS[i][k];
+ ZMAT[k][i]=ZMAT[i][k];
+ NMARKERS[k][i]= NMARKERS[i][k];
+ }
+ else{ZMAT[i][k]=-1000;
+ZMAT[k][i]=-1000;
+}
+
+ }
+
+ }
+
+
+
+
+
+
+
+ if(PRINT==1)
+ {
+
+
+
+
+ printf("Printing Empirical Correlation Matrix to a file named 'ROADTRIPS_MATRIX.txt' \n");
+
+if((mykinfile=fopen("ROADTRIPS_MATRIX.txt", "w"))==NULL)
+ {
+ printf("Unable to open ROADTRIPS_MATRIX.txt\n");
+ exit(1);
+ }
+
+for(j=1;j<=NPheno;j++)
+ {for(k=1;k<=NPheno;k++)
+ {fprintf(mykinfile,"%.6lf ",ZMAT[j][k]);
+ }
+ fprintf(mykinfile,"\n");
+ }
+
+ fclose(mykinfile);
+
+ }
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+/* printf("There were %d markers read in \n",MARKERCOUNT); */
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+/*
+
+for(i=1;i<=10;i++)
+ {for(j=1;j<=10;j++)
+ {
+ printf("%.6f ",ZMAT[i][j]);}
+
+ printf("\n");
+}
+
+
+ printf("\n\n");
+for(i=1;i<=10;i++)
+ {for(j=1;j<=10;j++)
+ {
+ printf("%d ",NMARKERS[i][j]);}
+
+ printf("\n");
+ }
+
+
+
+
+*/
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+free_dvector(geno,0,NPheno);
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+}
+
+
+
+
+
+
+
+
+
+
+
+
+void get_FINAL_MATRIX(int finaltyped,double **ESTCOVMAT,int *D,double **ZMAT)
+{
+ int all1=0, all2=0,fam=0,famold=1,n=0;
+ int Ngenotypes=0;
+ int status=0,indnumber=0,ind=0,m=0,indiv=0,sex=0;
+ int i,j,k,l;
+ int MYCONTINUE,genovalue,pers1,pers2,num;
+
+
+
+
+
+
+for(j=1;j<=finaltyped;j++)
+ {for(k=j;k<=finaltyped;k++)
+ {
+
+pers1=D[j];
+pers2=D[k];
+
+ESTCOVMAT[j][k]=2*ZMAT[pers1][pers2];
+ESTCOVMAT[k][j]=2*ZMAT[pers1][pers2];
+
+ }}
+
+
+
+
+
+
+
+}
+
+
+
+
+
+
+void get_FINAL_MATRIX_KINSHIP(int finaltyped,double **ESTCOVMAT,int *D,double **ZMAT)
+{
+ int all1=0, all2=0,fam=0,famold=1,n=0;
+ int Ngenotypes=0;
+ int status=0,indnumber=0,ind=0,m=0,indiv=0,sex=0;
+ int i,j,k,l;
+ int MYCONTINUE,genovalue,pers1,pers2,num;
+ double sum;
+ FILE *mykinfile;
+ char tempname[MAXLEN] = "phenofile";
+
+
+
+
+
+
+ sum=0;
+for(j=1;j<=finaltyped;j++)
+ {for(k=j;k<=finaltyped;k++)
+ {
+
+pers1=D[j];
+pers2=D[k];
+
+ESTCOVMAT[j][k]=2*ZMAT[pers1][pers2];
+ESTCOVMAT[k][j]=2*ZMAT[pers1][pers2];
+
+ if(k==j)
+ {sum+=ZMAT[pers1][pers2];}
+ else
+{sum+=2*ZMAT[pers1][pers2];}
+
+ }}
+
+
+/*
+ if(BIGMARKER==0)
+ {
+ printf("finaltyped is %d \n",finaltyped);
+
+if((mykinfile=fopen("PAIRWISE_KINSHIP.input", "w"))==NULL)
+ {
+ printf("Can't open ROADTRIPS_Software.err .\n");
+ exit(1);
+ }
+
+for(j=1;j<=NPheno;j++)
+ {for(k=1;k<=NPheno;k++)
+ {fprintf(mykinfile,"%.6lf ",ZMAT[j][k]);
+ }
+ fprintf(mykinfile,"\n");
+ }
+
+ fclose(mykinfile);
+
+ }
+
+
+*/
+
+}
+
+
+
+
+
+
+void readsnpnames (char *name,int MARKECOUNT,char **SNPNAME)
+{
+
+ int all1=0, all2=0,fam=0,famold=1,n=0;
+ int indnumber=0,ind=0,nloci;
+ char str1[100];
+
+
+ if((fsnpname=fopen(name, "r"))==NULL)
+ {
+ printf("Can't open MARKER NAME FILE %s\n",name);
+ exit(1);
+ }
+
+
+nloci=0;
+ while((fscanf(fsnpname,"%s ",str1))==1)
+ {nloci++;
+
+ }
+
+ NAMECOUNT=nloci;
+
+ rewind(fsnpname);
+
+
+ printf("HAVE ALL SNP NAMES. TOTAL is %d \n",nloci);
+
+ /*
+ if(nloci!=MARKERCOUNT)
+ {
+ printf("Error in SNP NAME File: There are %d SNPs in the genotype file but there are only %d SNP names in SNP name marker file %d \n",MARKERCOUNT,nloci);
+ exit(1);
+ }
+ */
+
+
+}
+
+
+
+
+void vecsrt2(double *d, int *M,char **NAME,int n)
+{
+ int k,j,i;
+ double p;
+ int place;
+ char tempname[100];
+
+ for (i=1;i<n;i++) {
+ p=d[k=i];
+ for (j=i+1;j<=n;j++)
+ if (d[j] < p)
+ {p=d[k=j];
+ place=M[k=j];
+ strncpy(tempname,NAME[k=j],100);
+}
+ if (k != i) {
+ d[k]=d[i];
+ d[i]=p;
+ M[k]=M[i];
+ M[i]=place;
+ strncpy(NAME[k],NAME[i],100);
+ strncpy(NAME[i],tempname,100);
+}
+ }
+}
+
+
+
+
+void getsnpnamefile (char *name)
+{
+
+ int all1=0, all2=0,fam=0,famold=1,n=0;
+ int indnumber=0,ind=0,nloci;
+ char str1[100];
+
+
+ if((fsnpname=fopen(name, "r"))==NULL)
+ {
+ printf("Can't open MARKER NAME FILE %s\n",name);
+ exit(1);
+ }
+
+
+nloci=0;
+ while((fscanf(fsnpname,"%s ",str1))==1)
+ {nloci++;
+
+ }
+
+ NAMECOUNT=nloci;
+
+ rewind(fsnpname);
+
+
+
+
+
+
+
+}
+
+
+
+
+
+
+void robustvar(double **cholaug,double *ROBUST_11,double *YYvector,double *Y1vector,int size,int *Nstu)
+{
+ int i,j;
+ double info_rr=0,info_rf=0,info=0,info_ff=0,robust_11=0;
+
+
+
+ for (i=1;i<=size;i++)
+ {robust_11+=cholaug[i][M+1]*cholaug[i][M+1];
+ for (j=1;j<=M;j++)
+ { YYvector[j]+=cholaug[i][j]*cholaug[i][j];
+ Y1vector[j]+=cholaug[i][M+1]*cholaug[i][j]; }
+ }
+
+
+
+ *ROBUST_11+=robust_11;
+ *Nstu+=size;
+
+}
+
+
+
+
+
+void WEIGHTS(double **cholaug, double **cholent, double *PART1,double *PART2,double *PART3,int size,int *Nstu)
+{
+ int i,j,k1,l,col,row,m;
+ double info_rr=0,info_rf=0,info=0,info_ff=0,robust_11=0;
+ double **A1,**A2,sum,*V1,*V2W,*V2M,sum1,sum2,sum3,part1=0,part2=0,part3=0;
+
+
+
+
+
+
+
+
+
+
+ for (i=1;i<=size;i++)
+ {part1+=cholaug[i][M+1]*cholaug[i][M+1];
+ part2+=cholaug[i][M+2]*cholaug[i][M+1];
+ part3+=cholaug[i][M+3]*cholaug[i][M+1];
+ col=M+3+i;
+ sum1=0;
+ sum2=0;
+ sum3=0;
+
+for(l=1;l<=size;l++)
+ {sum1=sum1+cholaug[l][col]*cholaug[l][M+1];
+ sum2=sum2+cholaug[l][col]*cholaug[l][M+2];
+sum3=sum3+cholaug[l][col]*cholaug[l][M+3];
+
+
+ }
+ DPVEC[MYCOUNT+i]=sum1;
+ DRVEC[MYCOUNT+i]=sum2;
+AVEC[MYCOUNT+i]=sum3;
+
+
+
+ }
+
+
+
+
+
+
+
+
+ *PART1+=part1;
+ *PART2+=part2;
+ *PART3+=part3;
+
+ /*
+ printf("part1 is %lf and PART1 is %lf \n",part1,*PART1);
+ printf("part2 is %lf and PART2 is %lf \n",part2,*PART2);
+ printf("part3 is %lf and PART3 is %lf \n",part3,*PART3);
+ */
+
+for(k1=1;k1<=size;k1++)
+ {YVEC[MYCOUNT+k1]=cholent[k1][1];
+ DR[MYCOUNT+k1]=cholent[k1][M+2];
+ DP[MYCOUNT+k1]=cholent[k1][M+1];
+ }
+
+
+
+ MYCOUNT+=size;
+
+
+}
+
+
+
+
+
+
+
+
+
+
+
+
+/***** GET ROBUST VARIANCE ***/
+
+void from_info2_scoreROBUST(double **freqMatrix,double infoQL_rr,double infoQL_rf,double infoQL_ff,double *Rvector,double *testval,double ROBUST_11,double *YYvector,double *Y1vector, int Nstu,double *ROBUSTVAR)
+{
+ int i,j;
+ double info=0,score=0;
+
+
+ /* printf("For allele 1, YPHIYvector is %lf, YPHI1vector is %lf, and 1PHI1 vector is %lf,Nstu is %d \n",YYvector[1],Y1vector[1],ROBUST_11,Nstu);
+
+ */
+
+ for(i=1;i<=M-1;i++)
+ {ROBUSTVAR[i]=(1.0/(Nstu-1))*( YYvector[i]-Y1vector[i]*Y1vector[i]/ROBUST_11);
+
+
+ /*
+ printf("i is %d: ROBUSTVAR is %lf and HWE var is %lf \n",i,ROBUSTVAR[i],2.0/freqMatrix[i][i]);
+ */
+
+
+ }
+
+
+
+
+
+ info=infoQL_rr - infoQL_rf*infoQL_rf/infoQL_ff;
+
+ for (i=1;i<=M-1;i++)
+ { for (j=1;j<=M-1;j++)
+ {
+ if(i==j)
+ {score+=Rvector[i]*Rvector[j]/(info*ROBUSTVAR[i]);}
+ else{ score+=Rvector[i]*Rvector[j]/info*freqMatrix[i][j]/2; }
+
+ }}
+
+
+ *testval=score;
+}
+
+
+
+
+
+
+
+
+
+
+
+/******************************************************
+Computes the corrected chi2 test
+*****************************************************/
+
+void from_info2_chi2_ROBUST(double info_rr, double info_rf, double info_ff, double *Naive,double *Naivefreq,double **freqNaive,double *chi2val,int Nall,int Ncase,double ROBUST_11,double *YYvector,double *Y1vector, int Nstu,double *ROBUSTVAR)
+{
+ int i,j;
+ double info=0,score=0;
+ double chi2old=0;
+ double freqpas=0,corrfactor=0;
+
+ /* printf("For allele 1, YPHIYvector is %lf, YPHI1vector is %lf, and 1PHI1 vector is %lf,Nstu is %d \n",YYvector[1],Y1vector[1],ROBUST_11,Nstu);
+ */
+
+ for(i=1;i<=M-1;i++)
+ {ROBUSTVAR[i]=(1.0/(Nstu-1))*( YYvector[i]-Y1vector[i]*Y1vector[i]/ROBUST_11);
+
+ /* printf("i is %d: ROBUSTVAR is %lf and HWE var using Naive freq is %lf \n",i,ROBUSTVAR[i],2.0/freqNaive[i][i]);*/
+ }
+
+
+
+
+ corrfactor=4/((info_rr-2*Ncase*(double)info_rf/Nall+(double)Ncase/Nall*(double)Ncase/Nall*info_ff));
+
+ for (i=1;i<=M-1;i++)
+ {for (j=1;j<=M-1;j++)
+
+ {
+ if(i==j)
+ { chi2old+=(Naive[i]-2*Ncase*Naivefreq[i])*(Naive[j]-2*Ncase*Naivefreq[j])/ROBUSTVAR[i];}
+
+ else{chi2old+=(Naive[i]-2*Ncase*Naivefreq[i])*(Naive[j]-2*Ncase*Naivefreq[j])*freqNaive[i][j]/2;}
+
+ }}
+
+ *chi2val=chi2old*corrfactor;
+
+}
+
+
+
+
+
+void GET_KIN_MATRIX(int fam, int length)
+{
+
+ int i,j,k,l;
+ int MYCONTINUE,genovalue,pers1,pers2,num;
+
+
+
+
+
+
+
+for (i=1;i<=length;i++) //length is famdata[fam].NPheno
+ {
+ KINALLMATRIX[FINALCOUNTED+i][FINALCOUNTED+i]=(Storekin[fam][i][i]+1)*.5;
+
+
+ for (j=i+1;j<=length;j++)
+ {
+ if (Storekin[fam][i][j]==-1) {
+ printf("No kinship coefficient between individual %d and individual %d from family %d. Please check...\n\n",famdata[fam].descri[i],famdata[fam].descri[j],fam);
+ exit(1);
+ }
+
+
+ KINALLMATRIX[FINALCOUNTED+i][FINALCOUNTED+j]=Storekin[fam][i][j];
+ KINALLMATRIX[FINALCOUNTED+j][FINALCOUNTED+i]=Storekin[fam][i][j];
+
+ } }
+
+
+ FINALCOUNTED+=length;
+
+}
+
+
+
+int getgenoline_Linkage(struct MARKER *Mark,struct FAM *famdata,FILE *errfile)
+{
+
+int all1=0, all2=0,fam=0,famold=1,n=0;
+ char line[MAXLINE],line2[MAXLINE];
+ int length=MAXLINE;
+ int Ngenotypes=0;
+ int status=0,indnumber=0,ind=0,m=0,indiv=0,sex=0;
+ int i,j,k,l;
+ int MYCONTINUE,genovalue,mytyped=0,pers1,pers2,num;
+ FILE *ftemp;
+
+
+
+ fgets(line,length,genofile);
+
+strncpy(line2,line,MAXLINE);
+
+
+ MYCONTINUE=0;
+
+ Ngenotypes=0;
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ /* n=sscanf(line,"%d %[^\n]",&genovalue,line);*/
+ if (n<2) {
+
+ if(BIGMARKER==0)
+ {
+ printf("No marker to test. Please check first line in marker data file\n\n");
+ exit(1);
+ }
+
+ }
+ else {
+ Ngenotypes++;
+ printf("%d %d \n",all1,all2);
+ while (n==3)
+ {
+ n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);
+ if (n>=2) {
+ Ngenotypes++;
+
+ }
+ }
+ }
+
+
+
+
+
+
+
+if(Ngenotypes==NPheno)
+ {MYCONTINUE=1;
+
+ m=1;
+
+
+
+Mark[m].Nball=0;
+ Mark[m].Nc=0;
+ Mark[m].Nt=0;
+ Mark[m].Nu=0;
+
+
+ for(i=1;i<=F;i++)
+ {
+ Mark[m].typed[i].N=0;
+ Mark[m].typed[i].Nc=0;
+ Mark[m].typed[i].Nt=0;
+ Mark[m].typed[i].Nu=0;
+
+ }
+
+
+
+
+ num=0;
+for (i=1;i<=F;i++)
+ {for(j=1;j<=famdata[i].N;j++)
+ { n=sscanf(line2,"%d %d %[^\n]",&all1,&all2,line2);
+ num++;
+
+
+ if( ( (all1==1 || all1==2) && (all2==1 ||all2==2)) && (famdata[i].MZ[j][1]==-10||(famdata[i].MZ[j][1]>0&&famdata[i].MZ[j][1]!=2)))
+ {
+
+ mytyped++;
+
+
+
+
+
+
+ /*
+GENOTYPED[num]=1;
+ */
+
+
+
+
+
+
+ /* printf("%d %d %d \n",i,j,FINALTYPED[mytyped]); */
+
+
+ }
+
+
+else{all1=0;
+ all2=0;
+ /* GENOTYPED[num]=0; */
+}
+
+
+
+fam=i;
+ indnumber=j;
+ status=famdata[i].AFFEC[j];
+ ind=famdata[i].descri[j];
+
+
+
+ /* sex=famdata[i].SEX[j]; */
+
+
+
+ Mark[m].mark[fam][indnumber][1]=all1;
+ Mark[m].mark[fam][indnumber][2]=all2;
+ Mark[m].mark[fam][indnumber][3]=status;
+ Mark[m].mark[fam][indnumber][4]=ind;
+ /* Mark[m].mark[fam][indnumber][5]=sex;*/
+ if ( (status==0||status==1) && all1!=0 && all2!=0)
+ {
+
+
+
+ Mark[m].typed[fam].N++;
+
+
+ if(status==1)
+ {Mark[m].typed[fam].Nt++;
+ Mark[m].Nt++;
+ }
+
+ if(status==0)
+ {Mark[m].Nu++;
+ Mark[m].typed[fam].Nu++;
+ }
+ }
+ if (status==2 && all1!=0 && all2!=0)
+ {
+ Mark[m].typed[fam].Nc++;
+ Mark[m].typed[fam].N++;
+ Mark[m].Nc++;
+ }
+ if (all1>Mark[m].Nball) Mark[m].Nball=all1;
+ if (all2>Mark[m].Nball) Mark[m].Nball=all2;
+
+ }
+ }
+
+
+
+ }
+
+/*
+printf("There are %d total typed for marker %d \n",mytyped,BIGMARKER);
+*/
+
+ if(MYCONTINUE==1)
+ {
+ TYPEDNUM=mytyped;
+ /* printf("There are %d total typed for marker %d \n",mytyped,BIGMARKER); */
+ }
+
+
+
+
+
+
+ return(MYCONTINUE);
+
+}
+
+
+int getgenoline_ADDITIVE(struct MARKER *Mark,struct FAM *famdata,FILE *errfile)
+{
+
+int all1=0, all2=0,fam=0,famold=1,n=0;
+ char line[MAXLINE],line2[MAXLINE];
+ int length=MAXLINE;
+ int Ngenotypes=0;
+ int status=0,indnumber=0,ind=0,m=0,indiv=0,sex=0;
+ int i,j,k,l;
+ int MYCONTINUE,genovalue,mytyped=0,pers1,pers2,num;
+
+
+
+
+
+
+ fgets(line,length,genofile);
+
+strncpy(line2,line,MAXLINE);
+
+
+ MYCONTINUE=0;
+
+ Ngenotypes=0;
+ /* n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line); */
+ n=sscanf(line,"%d %[^\n]",&genovalue,line);
+ if (n<1) {
+
+ if(BIGMARKER==0)
+ {
+ printf("No marker to test. Please check first line in marker data file\n\n");
+ exit(1);
+ }
+
+ }
+ else {
+ Ngenotypes++;
+
+ while (n==2)
+ {
+ n=sscanf(line,"%d %[^\n]",&genovalue,line);
+ if (n>=1) {
+ Ngenotypes++;
+ }
+ }
+ }
+
+
+
+
+
+
+
+if(Ngenotypes==NPheno)
+ {MYCONTINUE=1;
+
+ m=1;
+
+
+
+Mark[m].Nball=0;
+ Mark[m].Nc=0;
+ Mark[m].Nt=0;
+ Mark[m].Nu=0;
+
+
+ for(i=1;i<=F;i++)
+ {
+ Mark[m].typed[i].N=0;
+ Mark[m].typed[i].Nc=0;
+ Mark[m].typed[i].Nt=0;
+ Mark[m].typed[i].Nu=0;
+
+ }
+
+
+
+
+ num=0;
+for (i=1;i<=F;i++)
+ {for(j=1;j<=famdata[i].N;j++)
+ { n=sscanf(line2,"%d %[^\n]",&genovalue,line2);
+ num++;
+
+
+ if( (genovalue==0 || genovalue==1 || genovalue==2) && (famdata[i].MZ[j][1]==-10||(famdata[i].MZ[j][1]>0&&famdata[i].MZ[j][1]!=2)))
+ {
+
+ mytyped++;
+
+
+ /*
+GENOTYPED[num]=1;
+ */
+
+
+
+
+
+
+ /* printf("%d %d %d \n",i,j,FINALTYPED[mytyped]); */
+
+if(genovalue==2)
+ {all1=1;
+ all2=1;}
+
+
+if(genovalue==1)
+ {all1=1;
+ all2=2;}
+
+
+if(genovalue==0)
+ {all1=2;
+ all2=2;}
+
+ }
+
+
+else{all1=0;
+ all2=0;
+ /* GENOTYPED[num]=0; */
+}
+
+
+
+fam=i;
+ indnumber=j;
+ status=famdata[i].AFFEC[j];
+ ind=famdata[i].descri[j];
+ /* sex=famdata[i].SEX[j]; */
+
+
+
+ Mark[m].mark[fam][indnumber][1]=all1;
+ Mark[m].mark[fam][indnumber][2]=all2;
+ Mark[m].mark[fam][indnumber][3]=status;
+ Mark[m].mark[fam][indnumber][4]=ind;
+ /* Mark[m].mark[fam][indnumber][5]=sex;*/
+ if ( (status==0||status==1) && all1!=0 && all2!=0)
+ {
+
+
+
+ Mark[m].typed[fam].N++;
+
+
+ if(status==1)
+ {Mark[m].typed[fam].Nt++;
+ Mark[m].Nt++;
+ }
+
+ if(status==0)
+ {Mark[m].Nu++;
+ Mark[m].typed[fam].Nu++;
+ }
+ }
+ if (status==2 && all1!=0 && all2!=0)
+ {
+ Mark[m].typed[fam].Nc++;
+ Mark[m].typed[fam].N++;
+ Mark[m].Nc++;
+ }
+ if (all1>Mark[m].Nball) Mark[m].Nball=all1;
+ if (all2>Mark[m].Nball) Mark[m].Nball=all2;
+
+ }
+ }
+
+
+
+ }
+
+
+
+ if(MYCONTINUE==1)
+ {
+ TYPEDNUM=mytyped;
+ /* printf("There are %d total typed for marker %d \n",mytyped,BIGMARKER); */
+ }
+
+
+
+ return(MYCONTINUE);
+
+}
+
+
+
+void READ_EMPIRICAL_MATRIX(char *name)
+{
+
+
+
+int all1=0, all2=0,fam=0,famold=1,n=0;
+ char line[MAXLINE],line2[MAXLINE];
+ int length=MAXLINE;
+ int Ngenotypes=0;
+ int status=0,indnumber=0,ind=0,m=0,indiv=0,sex=0;
+ int i,j,k,l,num1;
+ int MYCONTINUE=0;
+ double freqest,val1;
+ double *KINVALUES;
+ double value;
+ int ROWCOUNT;
+ FILE *empkinfile;
+
+ if((empkinfile=fopen(name, "r"))==NULL)
+ {
+ printf("Can't open the specified input empirical correlation file %s. Please check this file. \n",name);
+ exit(1);
+ }
+
+
+
+
+ fgets(line,length,empkinfile);
+
+ Ngenotypes=0;
+ /* n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);*/
+ n=sscanf(line,"%lf %[^\n]",&value,line);
+ if (n<1) {
+printf("Error in Genotype File: There is not a single kinship coefficient to be read in \n");
+ exit(1);
+ }
+ else {
+ Ngenotypes++;
+ while (n==2)
+ {
+ n=sscanf(line,"%lf %[^\n]",&value,line);
+ if (n>=1) {
+ Ngenotypes++;
+ }
+ }
+ }
+
+
+
+
+
+
+
+
+
+ if(Ngenotypes!=NPheno)
+ {printf("Error in Empirical Kinship File: The number of individuals in the phenotype file and the number of genotypes Empirical Kinships must be the same. There are %d study individuals from the phenotype file but there are %d kinship coefficients for the first row that was read from the empirical kinship file \n",NPheno,Ngenotypes);
+ exit(1);
+ }
+
+
+
+
+
+KINVALUES=dvector(0,NPheno);
+ZMAT=dmatrix(0,NPheno,0,NPheno);
+FINALTYPED=ivector(0,NPheno);
+
+ rewind(empkinfile);
+
+
+for(i=1;i<=NPheno;i++)
+ {for(j=1;j<=NPheno;j++)
+ {
+
+ ZMAT[i][j]=0;
+
+ }}
+
+
+
+
+ ROWCOUNT=NPheno;
+
+ for(i=1;i<=NPheno;i++)
+ {
+for(j=1;j<=NPheno;j++)
+ {
+ fscanf(empkinfile,"%lf ",ZMAT[i]+j);
+
+
+ }}
+
+
+
+
+
+
+
+
+
+
+
+
+ MYCONTINUE=0;
+ while(MYCONTINUE==1)
+ {
+ printf("ROWCOUNT is %d \n",ROWCOUNT);
+
+ fgets(line,length,empkinfile);
+
+ //strncpy(line2,line,MAXLINE);
+
+
+Ngenotypes=0;
+/* n=sscanf(line,"%d %d %[^\n]",&all1,&all2,line);*/
+n=sscanf(line,"%lf %[^\n]",&value,line);
+ if (n<1) {
+
+ }
+ else {
+ Ngenotypes++;
+ KINVALUES[Ngenotypes]=value;
+ while (n==2)
+ {
+ n=sscanf(line,"%lf %[^\n]",&value,line);
+ if (n>=1) {
+ Ngenotypes++;
+ KINVALUES[Ngenotypes]=value;
+ }
+ }
+ }
+
+
+
+
+
+
+ if(Ngenotypes!=NPheno)
+ {MYCONTINUE=0;
+
+ if(Ngenotypes>2)
+ {printf("Error in Genotype File: There are %d study individuals from the phenotype file but there are only %d genotypes for marker %d \n",NPheno,Ngenotypes,MARKERCOUNT+1);
+ exit(1);
+ }
+
+
+
+
+ }
+
+
+
+
+if(Ngenotypes==NPheno)
+ {
+MYCONTINUE=1;
+ ROWCOUNT++;
+
+ for(i=1;i<=NPheno;i++)
+ {ZMAT[ROWCOUNT][i]=KINVALUES[i];}
+ }
+
+
+
+
+
+
+ }
+
+
+
+ free_dvector(KINVALUES,0,NPheno);
+
+
+ if(ROWCOUNT!=NPheno)
+ {printf("Error in Empirical Kinship File: There are %d study individuals from the phenotype file but there are only %d rows in the Empirical Kinship File. There must by %d rows and %d collumns in this file \n",NPheno,ROWCOUNT,NPheno,NPheno);
+ exit(1);
+ }
+
+ fclose(empkinfile);
+
+
+}
+
+
+
+
+void readkincoefnoinfo(FILE *errfile, struct FAM *famdata,double ***Storekin)
+{
+ double coef=0;
+ int follow=0,j,i,n,famold=0;
+ long int Id1,Id2;
+ int family=0,ind1=0,ind2=0,indold1=0,indold2=0,Idold1=0,Idold2=0;
+ int err_array[N];
+ int test=0,lim=0;
+
+
+ for (i=1;i<=N;i++)
+ err_array[i]=0;
+
+for (follow=1;follow<=F;follow++)
+ for (i=1;i<=famdata[follow].Pheno;i++)
+ for (j=i;j<=famdata[follow].Pheno;j++)
+ {
+ Storekin[follow][i][j]=0;
+ if (i!=j) Storekin[follow][j][i]=0;
+ }
+
+
+
+}
+
+
+
+/* TO RUN THE PROGRAM, USE COMMANDS
+
+
+./MQLS-XM -p MQLS_XM_software_input.pedinfo -g NEW_PEDIGREE_ASSOCIATION_TRANSPOSE_20SNPs.tped -k KINSHIP_PEDIGREE.output -r pedigree_prevalence
+
+
+./MQLS_XM -p example.ped -g example.geno -k example.kinship -r example.prev -n example.SNPnames
+
+gcc -lm -O3 ROADTRIPS_SOURCE_NEW_REVAMPEDMSM2.c -o ROADTRIPS
+
+
+./ROADTRIPS -p example.ped -g example.geno -k example.kinship -r example.prev -n example.SNPnames
+
+
+gcc -lm -O3 NEW_MQLS_TEST6.c -o MQLS
+
+
+
+
+*/
+
diff --git a/ROADTRIPStest.out.ex b/ROADTRIPStest.out.ex
new file mode 100644
index 0000000..35fd075
--- /dev/null
+++ b/ROADTRIPStest.out.ex
@@ -0,0 +1,39271 @@
+******Results of the Case-control Association tests ******
+
+There are 320 individuals from 20 independent families. 80 of the individuals are affected, 240 of the individuals are unaffected, and 0 of the individuals are of unknown phenotype.
+
+There are 160 males and 160 females. The prevalence values used in the RM test statistic for males and females are 0.085625 and 0.085625, respectively.
+****************************************
+
+Analysis of Marker 1: rs1
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.101957 pvalue = 0.0781983 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.018470 pvalue = 0.0823211 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.723952 pvalue = 0.098853 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6050 sd = 0.0528 freq = 0.6596 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.3950 sd = 0.0528 freq = 0.3404 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.6646 freq = 0.0000 freq = 0.6438
+allele 2 : freq = 0.4188 freq = 0.3354 freq = 0.0000 freq = 0.3563
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 2: rs2
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000189 pvalue = 0.989035 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.118748 pvalue = 0.730397 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.584470 pvalue = 0.444565 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2117 sd = 0.0441 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+allele 2 : freq = 0.7883 sd = 0.0441 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.2104 freq = 0.0000 freq = 0.2141
+allele 2 : freq = 0.7750 freq = 0.7896 freq = 0.0000 freq = 0.7859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 3: rs3
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.628546 pvalue = 0.201904 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.670009 pvalue = 0.196257 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.011062 pvalue = 0.314648 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6183 sd = 0.0525 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+allele 2 : freq = 0.3817 sd = 0.0525 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.5417 freq = 0.0000 freq = 0.5578
+allele 2 : freq = 0.3937 freq = 0.4583 freq = 0.0000 freq = 0.4422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 4: rs4
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.034870 pvalue = 0.851869 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.612144 pvalue = 0.204191 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6650 sd = 0.0510 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+allele 2 : freq = 0.3350 sd = 0.0510 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.7042 freq = 0.0000 freq = 0.7016
+allele 2 : freq = 0.3063 freq = 0.2958 freq = 0.0000 freq = 0.2984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 5: rs5
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.279137 pvalue = 0.597268 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.940889 pvalue = 0.332049 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.014446 pvalue = 0.904333 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8717 sd = 0.0361 freq = 0.8712 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.1283 sd = 0.0361 freq = 0.1288 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8562 freq = 0.8896 freq = 0.0000 freq = 0.8812
+allele 2 : freq = 0.1437 freq = 0.1104 freq = 0.0000 freq = 0.1187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 6: rs6
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.134728 pvalue = 0.71358 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001941 pvalue = 0.964858 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.035816 pvalue = 0.849895 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6383 sd = 0.0519 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.3617 sd = 0.0519 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 freq = 0.6521 freq = 0.0000 freq = 0.6516
+allele 2 : freq = 0.3500 freq = 0.3479 freq = 0.0000 freq = 0.3484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 7: rs7
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.975807 pvalue = 0.323236 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.552688 pvalue = 0.212739 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.667303 pvalue = 0.102429 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5167 sd = 0.0540 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+allele 2 : freq = 0.4833 sd = 0.0540 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.5625 freq = 0.0000 freq = 0.5469
+allele 2 : freq = 0.5000 freq = 0.4375 freq = 0.0000 freq = 0.4531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 8: rs8
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.039657 pvalue = 0.842154 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.084971 pvalue = 0.770671 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.473315 pvalue = 0.491466 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4350 sd = 0.0535 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5650 sd = 0.0535 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.4417 freq = 0.0000 freq = 0.4453
+allele 2 : freq = 0.5437 freq = 0.5583 freq = 0.0000 freq = 0.5547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 9: rs9
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.601498 pvalue = 0.205691 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.149077 pvalue = 0.0759699 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.375245 pvalue = 0.240913 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8583 sd = 0.0377 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+allele 2 : freq = 0.1417 sd = 0.0377 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8750 freq = 0.8104 freq = 0.0000 freq = 0.8266
+allele 2 : freq = 0.1250 freq = 0.1896 freq = 0.0000 freq = 0.1734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 10: rs10
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.051915 pvalue = 0.819765 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.023283 pvalue = 0.878723 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000282 pvalue = 0.986591 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8067 sd = 0.0427 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.1933 sd = 0.0427 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7875 freq = 0.0000 freq = 0.7859
+allele 2 : freq = 0.2188 freq = 0.2125 freq = 0.0000 freq = 0.2141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 11: rs11
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.718602 pvalue = 0.396603 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.985522 pvalue = 0.320839 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.160732 pvalue = 0.688483 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8233 sd = 0.0412 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1767 sd = 0.0412 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.8438 freq = 0.0000 freq = 0.8344
+allele 2 : freq = 0.1938 freq = 0.1562 freq = 0.0000 freq = 0.1656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 12: rs12
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.665125 pvalue = 0.414757 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.419130 pvalue = 0.517372 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.171040 pvalue = 0.679189 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3217 sd = 0.0505 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339
+allele 2 : freq = 0.6783 sd = 0.0505 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3563 freq = 0.0000 freq = 0.3484
+allele 2 : freq = 0.6750 freq = 0.6438 freq = 0.0000 freq = 0.6516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 13: rs13
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.649237 pvalue = 0.420386 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.139113 pvalue = 0.709165 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.022688 pvalue = 0.88027 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5133 sd = 0.0540 freq = 0.4904 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.4867 sd = 0.0540 freq = 0.5096 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5312 freq = 0.5125 freq = 0.0000 freq = 0.5172
+allele 2 : freq = 0.4688 freq = 0.4875 freq = 0.0000 freq = 0.4828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 14: rs14
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.595007 pvalue = 0.44049 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.244666 pvalue = 0.264574 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.444057 pvalue = 0.505171 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5900 sd = 0.0531 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+allele 2 : freq = 0.4100 sd = 0.0531 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.6604 freq = 0.0000 freq = 0.6469
+allele 2 : freq = 0.3937 freq = 0.3396 freq = 0.0000 freq = 0.3531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 15: rs15
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.243184 pvalue = 0.621916 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.393730 pvalue = 0.237776 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238
+allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8500 freq = 0.8500 freq = 0.0000 freq = 0.8500
+allele 2 : freq = 0.1500 freq = 0.1500 freq = 0.0000 freq = 0.1500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 16: rs16
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.131096 pvalue = 0.717298 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.290161 pvalue = 0.590118 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.950244 pvalue = 0.162561 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5033 sd = 0.0540 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.4967 sd = 0.0540 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.4792 freq = 0.0000 freq = 0.4859
+allele 2 : freq = 0.4938 freq = 0.5208 freq = 0.0000 freq = 0.5141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 17: rs17
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.815121 pvalue = 0.366611 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.138553 pvalue = 0.285958 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.012729 pvalue = 0.910171 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4050 sd = 0.0530 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+allele 2 : freq = 0.5950 sd = 0.0530 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.3604 freq = 0.0000 freq = 0.3734
+allele 2 : freq = 0.5875 freq = 0.6396 freq = 0.0000 freq = 0.6266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 18: rs18
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.515168 pvalue = 0.218352 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.498513 pvalue = 0.480154 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.387036 pvalue = 0.533862 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1883 sd = 0.0422 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8117 sd = 0.0422 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1625 freq = 0.0000 freq = 0.1688
+allele 2 : freq = 0.8125 freq = 0.8375 freq = 0.0000 freq = 0.8313
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 19: rs19
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.029284 pvalue = 0.864126 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.066726 pvalue = 0.796165 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7633 sd = 0.0459 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+allele 2 : freq = 0.2367 sd = 0.0459 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.7562 freq = 0.0000 freq = 0.7562
+allele 2 : freq = 0.2437 freq = 0.2437 freq = 0.0000 freq = 0.2437
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 20: rs20
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.288826 pvalue = 0.590974 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.391001 pvalue = 0.531774 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.638246 pvalue = 0.424347 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.5437 freq = 0.0000 freq = 0.5516
+allele 2 : freq = 0.4250 freq = 0.4562 freq = 0.0000 freq = 0.4484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 21: rs21
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.092789 pvalue = 0.760661 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001989 pvalue = 0.964427 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003475 pvalue = 0.952995 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3500 sd = 0.0515 freq = 0.3212 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.6500 sd = 0.0515 freq = 0.6788 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.3292 freq = 0.0000 freq = 0.3297
+allele 2 : freq = 0.6687 freq = 0.6708 freq = 0.0000 freq = 0.6703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 22: rs22
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.765091 pvalue = 0.38174 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.933919 pvalue = 0.333847 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.072307 pvalue = 0.788007 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.8021 freq = 0.0000 freq = 0.7922
+allele 2 : freq = 0.2375 freq = 0.1979 freq = 0.0000 freq = 0.2078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 23: rs23
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.495171 pvalue = 0.0615481 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.478737 pvalue = 0.115395 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.729199 pvalue = 0.188513 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7233 sd = 0.0483 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+allele 2 : freq = 0.2767 sd = 0.0483 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7375 freq = 0.6625 freq = 0.0000 freq = 0.6813
+allele 2 : freq = 0.2625 freq = 0.3375 freq = 0.0000 freq = 0.3187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 24: rs24
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.595238 pvalue = 0.440401 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.109916 pvalue = 0.740239 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.082691 pvalue = 0.773683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4417 sd = 0.0536 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.5583 sd = 0.0536 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4667 freq = 0.0000 freq = 0.4625
+allele 2 : freq = 0.5500 freq = 0.5333 freq = 0.0000 freq = 0.5375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 25: rs25
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.245474 pvalue = 0.62028 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.113692 pvalue = 0.735979 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.012413 pvalue = 0.911289 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2333 sd = 0.0457 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+allele 2 : freq = 0.7667 sd = 0.0457 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.2396 freq = 0.0000 freq = 0.2359
+allele 2 : freq = 0.7750 freq = 0.7604 freq = 0.0000 freq = 0.7641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 26: rs26
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.972947 pvalue = 0.160135 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.486215 pvalue = 0.485621 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.100362 pvalue = 0.751395 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5833 sd = 0.0533 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+allele 2 : freq = 0.4167 sd = 0.0533 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.6208 freq = 0.0000 freq = 0.6125
+allele 2 : freq = 0.4125 freq = 0.3792 freq = 0.0000 freq = 0.3875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 27: rs27
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.014760 pvalue = 0.903301 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.194115 pvalue = 0.659513 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.098655 pvalue = 0.294561 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6417 sd = 0.0518 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.3583 sd = 0.0518 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.6479 freq = 0.0000 freq = 0.6531
+allele 2 : freq = 0.3312 freq = 0.3521 freq = 0.0000 freq = 0.3469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 28: rs28
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.012922 pvalue = 0.909497 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.011155 pvalue = 0.915886 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.791930 pvalue = 0.373517 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1817 sd = 0.0416 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+allele 2 : freq = 0.8183 sd = 0.0416 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1938 freq = 0.1896 freq = 0.0000 freq = 0.1906
+allele 2 : freq = 0.8063 freq = 0.8104 freq = 0.0000 freq = 0.8094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 29: rs29
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.688291 pvalue = 0.193826 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.061435 pvalue = 0.302888 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.096608 pvalue = 0.755939 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2562 freq = 0.3042 freq = 0.0000 freq = 0.2922
+allele 2 : freq = 0.7438 freq = 0.6958 freq = 0.0000 freq = 0.7078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 30: rs30
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.030037 pvalue = 0.862405 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.357050 pvalue = 0.550149 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.277075 pvalue = 0.131299 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6150 sd = 0.0526 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+allele 2 : freq = 0.3850 sd = 0.0526 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.5896 freq = 0.0000 freq = 0.5969
+allele 2 : freq = 0.3812 freq = 0.4104 freq = 0.0000 freq = 0.4031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 31: rs31
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.014790 pvalue = 0.903205 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.202589 pvalue = 0.652639 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.214084 pvalue = 0.643585 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.2038 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.7962 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.2000 freq = 0.0000 freq = 0.2047
+allele 2 : freq = 0.7812 freq = 0.8000 freq = 0.0000 freq = 0.7953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 32: rs32
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.846129 pvalue = 0.35765 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.375123 pvalue = 0.240934 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.816160 pvalue = 0.0507604 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2733 sd = 0.0481 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+allele 2 : freq = 0.7267 sd = 0.0481 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2625 freq = 0.2125 freq = 0.0000 freq = 0.2250
+allele 2 : freq = 0.7375 freq = 0.7875 freq = 0.0000 freq = 0.7750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 33: rs33
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.174668 pvalue = 0.278444 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.500194 pvalue = 0.479415 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000756 pvalue = 0.978067 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5017 sd = 0.0540 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+allele 2 : freq = 0.4983 sd = 0.0540 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.4708 freq = 0.0000 freq = 0.4797
+allele 2 : freq = 0.4938 freq = 0.5292 freq = 0.0000 freq = 0.5203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 34: rs34
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.910875 pvalue = 0.339882 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.621134 pvalue = 0.430626 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.102725 pvalue = 0.748584 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8712 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1288 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8938 freq = 0.8667 freq = 0.0000 freq = 0.8734
+allele 2 : freq = 0.1062 freq = 0.1333 freq = 0.0000 freq = 0.1266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 35: rs35
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007475 pvalue = 0.931101 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.070431 pvalue = 0.79071 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.432537 pvalue = 0.510747 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3067 sd = 0.0498 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+allele 2 : freq = 0.6933 sd = 0.0498 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3375 freq = 0.0000 freq = 0.3344
+allele 2 : freq = 0.6750 freq = 0.6625 freq = 0.0000 freq = 0.6656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 36: rs36
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001557 pvalue = 0.968529 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.612144 pvalue = 0.204191 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.6904 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.3096 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6833 freq = 0.0000 freq = 0.6859
+allele 2 : freq = 0.3063 freq = 0.3167 freq = 0.0000 freq = 0.3141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 37: rs37
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.644061 pvalue = 0.422244 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.275304 pvalue = 0.258774 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.185373 pvalue = 0.666796 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6417 sd = 0.0518 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.3583 sd = 0.0518 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.6792 freq = 0.0000 freq = 0.6656
+allele 2 : freq = 0.3750 freq = 0.3208 freq = 0.0000 freq = 0.3344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 38: rs38
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.289286 pvalue = 0.590679 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.394290 pvalue = 0.237682 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.351019 pvalue = 0.553537 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.6125 freq = 0.0000 freq = 0.6266
+allele 2 : freq = 0.3312 freq = 0.3875 freq = 0.0000 freq = 0.3734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 39: rs39
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.058346 pvalue = 0.80913 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027692 pvalue = 0.867834 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000756 pvalue = 0.978067 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5500 sd = 0.0537 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+allele 2 : freq = 0.4500 sd = 0.0537 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.5479 freq = 0.0000 freq = 0.5500
+allele 2 : freq = 0.4437 freq = 0.4521 freq = 0.0000 freq = 0.4500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 40: rs40
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.682782 pvalue = 0.194555 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.826953 pvalue = 0.363155 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.176959 pvalue = 0.673999 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9062 freq = 0.8750 freq = 0.0000 freq = 0.8828
+allele 2 : freq = 0.0938 freq = 0.1250 freq = 0.0000 freq = 0.1172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 41: rs41
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.253593 pvalue = 0.262867 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.687694 pvalue = 0.193905 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.108208 pvalue = 0.0778986 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.2958 freq = 0.0000 freq = 0.2812
+allele 2 : freq = 0.7625 freq = 0.7042 freq = 0.0000 freq = 0.7188
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 42: rs42
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.460924 pvalue = 0.226783 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.349309 pvalue = 0.245399 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.879024 pvalue = 0.170445 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.4667 freq = 0.0000 freq = 0.4813
+allele 2 : freq = 0.4750 freq = 0.5333 freq = 0.0000 freq = 0.5188
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 43: rs43
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.312307 pvalue = 0.251977 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.826953 pvalue = 0.363155 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.231131 pvalue = 0.630687 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8883 sd = 0.0340 freq = 0.8635 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.1117 sd = 0.0340 freq = 0.1365 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9000 freq = 0.8688 freq = 0.0000 freq = 0.8766
+allele 2 : freq = 0.1000 freq = 0.1313 freq = 0.0000 freq = 0.1234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 44: rs44
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.007232 pvalue = 0.315567 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.833912 pvalue = 0.361144 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.192624 pvalue = 0.660741 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5083 sd = 0.0540 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+allele 2 : freq = 0.4917 sd = 0.0540 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5125 freq = 0.4667 freq = 0.0000 freq = 0.4781
+allele 2 : freq = 0.4875 freq = 0.5333 freq = 0.0000 freq = 0.5219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 45: rs45
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.686621 pvalue = 0.407316 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015465 pvalue = 0.901032 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.067724 pvalue = 0.79468 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5483 sd = 0.0538 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+allele 2 : freq = 0.4517 sd = 0.0538 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5563 freq = 0.0000 freq = 0.5578
+allele 2 : freq = 0.4375 freq = 0.4437 freq = 0.0000 freq = 0.4422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 46: rs46
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.208627 pvalue = 0.647845 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.628933 pvalue = 0.427747 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.290135 pvalue = 0.590134 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.6438 freq = 0.0000 freq = 0.6531
+allele 2 : freq = 0.3187 freq = 0.3563 freq = 0.0000 freq = 0.3469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 47: rs47
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.342038 pvalue = 0.558655 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007124 pvalue = 0.932734 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.525799 pvalue = 0.468378 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6300 sd = 0.0521 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+allele 2 : freq = 0.3700 sd = 0.0521 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.6354 freq = 0.0000 freq = 0.6344
+allele 2 : freq = 0.3688 freq = 0.3646 freq = 0.0000 freq = 0.3656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 48: rs48
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.330760 pvalue = 0.0679954 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.516245 pvalue = 0.06077 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.733591 pvalue = 0.391722 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7950 sd = 0.0436 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.2050 sd = 0.0436 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 freq = 0.8458 freq = 0.0000 freq = 0.8281
+allele 2 : freq = 0.2250 freq = 0.1542 freq = 0.0000 freq = 0.1719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 49: rs49
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.189261 pvalue = 0.138976 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.614799 pvalue = 0.0316972 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.325624 pvalue = 0.568247 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5400 sd = 0.0538 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4600 sd = 0.0538 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.6500 freq = 0.0000 freq = 0.6234
+allele 2 : freq = 0.4562 freq = 0.3500 freq = 0.0000 freq = 0.3766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 50: rs50
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.344434 pvalue = 0.0371301 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.392372 pvalue = 0.020225 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.881487 pvalue = 0.0153009 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.4833 freq = 0.0000 freq = 0.5125
+allele 2 : freq = 0.4000 freq = 0.5167 freq = 0.0000 freq = 0.4875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 51: rs51
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.774408 pvalue = 0.378857 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.920777 pvalue = 0.337271 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.000831 pvalue = 0.977005 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0483 sd = 0.0232 freq = 0.0673 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.0600 sd = 0.0168
+allele 2 : freq = 0.9517 sd = 0.0232 freq = 0.9327 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.9400 sd = 0.0168
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0437 freq = 0.0667 freq = 0.0000 freq = 0.0609
+allele 2 : freq = 0.9563 freq = 0.9333 freq = 0.0000 freq = 0.9391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 52: rs52
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.523736 pvalue = 0.469253 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.317306 pvalue = 0.573231 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.138572 pvalue = 0.709705 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2967 sd = 0.0493 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+allele 2 : freq = 0.7033 sd = 0.0493 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.2687 freq = 0.0000 freq = 0.2750
+allele 2 : freq = 0.7063 freq = 0.7312 freq = 0.0000 freq = 0.7250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 53: rs53
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.255068 pvalue = 0.613529 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.128329 pvalue = 0.720171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.746106 pvalue = 0.0974916 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8467 sd = 0.0389 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+allele 2 : freq = 0.1533 sd = 0.0389 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8562 freq = 0.0000 freq = 0.8531
+allele 2 : freq = 0.1562 freq = 0.1437 freq = 0.0000 freq = 0.1469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 54: rs54
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.147793 pvalue = 0.700653 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.066284 pvalue = 0.796826 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.275199 pvalue = 0.599866 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6267 sd = 0.0522 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+allele 2 : freq = 0.3733 sd = 0.0522 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6125 freq = 0.6250 freq = 0.0000 freq = 0.6219
+allele 2 : freq = 0.3875 freq = 0.3750 freq = 0.0000 freq = 0.3781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 55: rs55
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.040562 pvalue = 0.840385 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.006892 pvalue = 0.933838 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.415535 pvalue = 0.519174 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 sd = 0.0539 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+allele 2 : freq = 0.4750 sd = 0.0539 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.5479 freq = 0.0000 freq = 0.5469
+allele 2 : freq = 0.4562 freq = 0.4521 freq = 0.0000 freq = 0.4531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 56: rs56
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.134490 pvalue = 0.713821 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.429761 pvalue = 0.512106 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.159919 pvalue = 0.689231 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.7292 freq = 0.0000 freq = 0.7359
+allele 2 : freq = 0.2437 freq = 0.2708 freq = 0.0000 freq = 0.2641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 57: rs57
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 7.533044 pvalue = 0.00605775 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.971322 pvalue = 0.0145404 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.466864 pvalue = 0.225841 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1450 sd = 0.0380 freq = 0.0615 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192
+allele 2 : freq = 0.8550 sd = 0.0380 freq = 0.9385 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.0771 freq = 0.0000 freq = 0.0938
+allele 2 : freq = 0.8562 freq = 0.9229 freq = 0.0000 freq = 0.9062
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 58: rs58
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.008342 pvalue = 0.927226 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.071606 pvalue = 0.789013 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.146802 pvalue = 0.701611 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.6625 freq = 0.0000 freq = 0.6656
+allele 2 : freq = 0.3250 freq = 0.3375 freq = 0.0000 freq = 0.3344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 59: rs59
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.733593 pvalue = 0.187953 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.443788 pvalue = 0.117991 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.420763 pvalue = 0.0643812 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8283 sd = 0.0407 freq = 0.7692 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.1717 sd = 0.0407 freq = 0.2308 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.7604 freq = 0.0000 freq = 0.7766
+allele 2 : freq = 0.1750 freq = 0.2396 freq = 0.0000 freq = 0.2234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 60: rs60
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.440215 pvalue = 0.230105 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.579405 pvalue = 0.446546 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.558291 pvalue = 0.0592487 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4400 sd = 0.0536 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.5600 sd = 0.0536 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.4188 freq = 0.0000 freq = 0.4281
+allele 2 : freq = 0.5437 freq = 0.5813 freq = 0.0000 freq = 0.5719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 61: rs61
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.540961 pvalue = 0.462035 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.172442 pvalue = 0.677951 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.535522 pvalue = 0.464295 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3133 sd = 0.0501 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+allele 2 : freq = 0.6867 sd = 0.0501 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3125 freq = 0.2938 freq = 0.0000 freq = 0.2984
+allele 2 : freq = 0.6875 freq = 0.7063 freq = 0.0000 freq = 0.7016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 62: rs62
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.215359 pvalue = 0.642599 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.058006 pvalue = 0.809675 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.082076 pvalue = 0.774503 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2150 sd = 0.0444 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+allele 2 : freq = 0.7850 sd = 0.0444 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.2354 freq = 0.0000 freq = 0.2328
+allele 2 : freq = 0.7750 freq = 0.7646 freq = 0.0000 freq = 0.7672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 63: rs63
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.008387 pvalue = 0.31529 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.439885 pvalue = 0.507178 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.679821 pvalue = 0.0171611 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4100 sd = 0.0531 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.5900 sd = 0.0531 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4708 freq = 0.0000 freq = 0.4625
+allele 2 : freq = 0.5625 freq = 0.5292 freq = 0.0000 freq = 0.5375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 64: rs64
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.021143 pvalue = 0.884391 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.133972 pvalue = 0.714349 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.408656 pvalue = 0.522652 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.7917 freq = 0.0000 freq = 0.7953
+allele 2 : freq = 0.1938 freq = 0.2083 freq = 0.0000 freq = 0.2047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 65: rs65
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.224113 pvalue = 0.635924 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.081331 pvalue = 0.775502 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.015786 pvalue = 0.900015 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7283 sd = 0.0480 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+allele 2 : freq = 0.2717 sd = 0.0480 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.7375 freq = 0.0000 freq = 0.7344
+allele 2 : freq = 0.2750 freq = 0.2625 freq = 0.0000 freq = 0.2656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 66: rs66
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.040521 pvalue = 0.840466 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.041103 pvalue = 0.839338 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.241334 pvalue = 0.623244 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9050 sd = 0.0317 freq = 0.8865 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217
+allele 2 : freq = 0.0950 sd = 0.0317 freq = 0.1135 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9000 freq = 0.8938 freq = 0.0000 freq = 0.8953
+allele 2 : freq = 0.1000 freq = 0.1062 freq = 0.0000 freq = 0.1047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 67: rs67
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.346484 pvalue = 0.55611 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.620742 pvalue = 0.430772 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.192239 pvalue = 0.66106 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5417 sd = 0.0538 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+allele 2 : freq = 0.4583 sd = 0.0538 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.5396 freq = 0.0000 freq = 0.5297
+allele 2 : freq = 0.5000 freq = 0.4604 freq = 0.0000 freq = 0.4703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 68: rs68
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.078702 pvalue = 0.779065 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.293062 pvalue = 0.588265 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.118329 pvalue = 0.730854 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5367 sd = 0.0539 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+allele 2 : freq = 0.4633 sd = 0.0539 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.5708 freq = 0.0000 freq = 0.5641
+allele 2 : freq = 0.4562 freq = 0.4292 freq = 0.0000 freq = 0.4359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 69: rs69
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.373844 pvalue = 0.540916 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.379219 pvalue = 0.538022 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.531620 pvalue = 0.465927 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2233 sd = 0.0450 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+allele 2 : freq = 0.7767 sd = 0.0450 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.2000 freq = 0.0000 freq = 0.2062
+allele 2 : freq = 0.7750 freq = 0.8000 freq = 0.0000 freq = 0.7937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 70: rs70
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.981920 pvalue = 0.321725 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.656072 pvalue = 0.103155 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.526349 pvalue = 0.0604007 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4625 freq = 0.3812 freq = 0.0000 freq = 0.4016
+allele 2 : freq = 0.5375 freq = 0.6188 freq = 0.0000 freq = 0.5984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 71: rs71
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.070070 pvalue = 0.791235 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.084708 pvalue = 0.771015 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.668191 pvalue = 0.413683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.7562 freq = 0.0000 freq = 0.7594
+allele 2 : freq = 0.2313 freq = 0.2437 freq = 0.0000 freq = 0.2406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 72: rs72
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.666917 pvalue = 0.414128 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.448645 pvalue = 0.502979 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.224919 pvalue = 0.635317 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7521 freq = 0.0000 freq = 0.7594
+allele 2 : freq = 0.2188 freq = 0.2479 freq = 0.0000 freq = 0.2406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 73: rs73
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.314937 pvalue = 0.128137 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.911484 pvalue = 0.166799 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.633245 pvalue = 0.426168 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6550 sd = 0.0513 freq = 0.6942 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.3450 sd = 0.0513 freq = 0.3058 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.6896 freq = 0.0000 freq = 0.6734
+allele 2 : freq = 0.3750 freq = 0.3104 freq = 0.0000 freq = 0.3266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 74: rs74
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.104620 pvalue = 0.293254 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.818974 pvalue = 0.0931559 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.997178 pvalue = 0.317994 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4233 sd = 0.0534 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+allele 2 : freq = 0.5767 sd = 0.0534 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.3667 freq = 0.0000 freq = 0.3875
+allele 2 : freq = 0.5500 freq = 0.6333 freq = 0.0000 freq = 0.6125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 75: rs75
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.282911 pvalue = 0.130806 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.679990 pvalue = 0.101616 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.024662 pvalue = 0.875212 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1567 sd = 0.0393 freq = 0.2019 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+allele 2 : freq = 0.8433 sd = 0.0393 freq = 0.7981 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.2083 freq = 0.0000 freq = 0.1922
+allele 2 : freq = 0.8562 freq = 0.7917 freq = 0.0000 freq = 0.8078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 76: rs76
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.141769 pvalue = 0.285279 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.489942 pvalue = 0.483953 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.799751 pvalue = 0.371168 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2233 sd = 0.0450 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+allele 2 : freq = 0.7767 sd = 0.0450 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.2562 freq = 0.0000 freq = 0.2484
+allele 2 : freq = 0.7750 freq = 0.7438 freq = 0.0000 freq = 0.7516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 77: rs77
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.157869 pvalue = 0.691126 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.207810 pvalue = 0.648489 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000188 pvalue = 0.989075 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.5021 freq = 0.0000 freq = 0.5078
+allele 2 : freq = 0.4750 freq = 0.4979 freq = 0.0000 freq = 0.4922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 78: rs78
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.572503 pvalue = 0.449266 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.838880 pvalue = 0.359717 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.203518 pvalue = 0.27262 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1717 sd = 0.0407 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+allele 2 : freq = 0.8283 sd = 0.0407 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.1417 freq = 0.0000 freq = 0.1500
+allele 2 : freq = 0.8250 freq = 0.8583 freq = 0.0000 freq = 0.8500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 79: rs79
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.457927 pvalue = 0.22726 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.969370 pvalue = 0.324837 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.207435 pvalue = 0.648785 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7183 sd = 0.0486 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.2817 sd = 0.0486 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.7667 freq = 0.0000 freq = 0.7562
+allele 2 : freq = 0.2750 freq = 0.2333 freq = 0.0000 freq = 0.2437
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 80: rs80
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.794771 pvalue = 0.0945723 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.891946 pvalue = 0.0485182 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.863041 pvalue = 0.090636 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4617 sd = 0.0538 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+allele 2 : freq = 0.5383 sd = 0.0538 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.3833 freq = 0.0000 freq = 0.4078
+allele 2 : freq = 0.5188 freq = 0.6167 freq = 0.0000 freq = 0.5922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 81: rs81
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.094901 pvalue = 0.758037 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.744392 pvalue = 0.388257 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.586997 pvalue = 0.443583 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8317 sd = 0.0404 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.1683 sd = 0.0404 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.8521 freq = 0.0000 freq = 0.8438
+allele 2 : freq = 0.1812 freq = 0.1479 freq = 0.0000 freq = 0.1562
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 82: rs82
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.676462 pvalue = 0.410808 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.200047 pvalue = 0.138007 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.451768 pvalue = 0.501497 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4058 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5942 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.4479 freq = 0.0000 freq = 0.4297
+allele 2 : freq = 0.6250 freq = 0.5521 freq = 0.0000 freq = 0.5703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 83: rs83
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.943211 pvalue = 0.0470609 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.432342 pvalue = 0.0352641 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.735219 pvalue = 0.187746 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.6646 freq = 0.0000 freq = 0.6891
+allele 2 : freq = 0.2375 freq = 0.3354 freq = 0.0000 freq = 0.3109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 84: rs84
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.136428 pvalue = 0.711858 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.086624 pvalue = 0.768513 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000193 pvalue = 0.988915 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4267 sd = 0.0534 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+allele 2 : freq = 0.5733 sd = 0.0534 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4313 freq = 0.4167 freq = 0.0000 freq = 0.4203
+allele 2 : freq = 0.5687 freq = 0.5833 freq = 0.0000 freq = 0.5797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 85: rs85
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.058432 pvalue = 0.808992 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001720 pvalue = 0.966924 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001690 pvalue = 0.967212 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4717 sd = 0.0539 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.5283 sd = 0.0539 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4938 freq = 0.4917 freq = 0.0000 freq = 0.4922
+allele 2 : freq = 0.5062 freq = 0.5083 freq = 0.0000 freq = 0.5078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 86: rs86
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.576324 pvalue = 0.447757 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.016029 pvalue = 0.899251 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.032862 pvalue = 0.856148 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.3688 freq = 0.0000 freq = 0.3672
+allele 2 : freq = 0.6375 freq = 0.6312 freq = 0.0000 freq = 0.6328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 87: rs87
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.087900 pvalue = 0.766865 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.076043 pvalue = 0.782733 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.260360 pvalue = 0.609873 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1783 sd = 0.0413 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.8217 sd = 0.0413 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1979 freq = 0.0000 freq = 0.1953
+allele 2 : freq = 0.8125 freq = 0.8021 freq = 0.0000 freq = 0.8047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 88: rs88
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.414265 pvalue = 0.519813 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.472200 pvalue = 0.224999 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.721564 pvalue = 0.189492 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1667 sd = 0.0403 freq = 0.1654 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.8333 sd = 0.0403 freq = 0.8346 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1812 freq = 0.1354 freq = 0.0000 freq = 0.1469
+allele 2 : freq = 0.8187 freq = 0.8646 freq = 0.0000 freq = 0.8531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 89: rs89
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.814777 pvalue = 0.177936 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.718050 pvalue = 0.396784 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.182633 pvalue = 0.66912 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3667 sd = 0.0521 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.6333 sd = 0.0521 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.3354 freq = 0.0000 freq = 0.3453
+allele 2 : freq = 0.6250 freq = 0.6646 freq = 0.0000 freq = 0.6547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 90: rs90
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.018149 pvalue = 0.312959 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.757089 pvalue = 0.384241 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.691579 pvalue = 0.193393 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4650 sd = 0.0539 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.5350 sd = 0.0539 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.5000 freq = 0.0000 freq = 0.4891
+allele 2 : freq = 0.5437 freq = 0.5000 freq = 0.0000 freq = 0.5109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 91: rs91
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.758121 pvalue = 0.184859 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.447044 pvalue = 0.503742 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.521566 pvalue = 0.0334702 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6367 sd = 0.0519 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+allele 2 : freq = 0.3633 sd = 0.0519 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.5979 freq = 0.0000 freq = 0.6062
+allele 2 : freq = 0.3688 freq = 0.4021 freq = 0.0000 freq = 0.3937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 92: rs92
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.329243 pvalue = 0.0680582 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.289785 pvalue = 0.256088 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.072999 pvalue = 0.787019 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6283 sd = 0.0522 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.3717 sd = 0.0522 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.6771 freq = 0.0000 freq = 0.6641
+allele 2 : freq = 0.3750 freq = 0.3229 freq = 0.0000 freq = 0.3359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 93: rs93
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.187890 pvalue = 0.275756 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.122554 pvalue = 0.726281 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.049666 pvalue = 0.305584 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.7458 freq = 0.0000 freq = 0.7422
+allele 2 : freq = 0.2687 freq = 0.2542 freq = 0.0000 freq = 0.2578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 94: rs94
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.453619 pvalue = 0.500621 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.664681 pvalue = 0.414912 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.028947 pvalue = 0.864901 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3817 sd = 0.0525 freq = 0.3538 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+allele 2 : freq = 0.6183 sd = 0.0525 freq = 0.6462 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3937 freq = 0.3542 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.6062 freq = 0.6458 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 95: rs95
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.005784 pvalue = 0.0453444 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.326612 pvalue = 0.127178 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.086345 pvalue = 0.078952 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5783 sd = 0.0533 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+allele 2 : freq = 0.4217 sd = 0.0533 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.6417 freq = 0.0000 freq = 0.6234
+allele 2 : freq = 0.4313 freq = 0.3583 freq = 0.0000 freq = 0.3766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 96: rs96
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.507040 pvalue = 0.476423 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001717 pvalue = 0.96695 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.267935 pvalue = 0.132076 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.4542 freq = 0.0000 freq = 0.4547
+allele 2 : freq = 0.5437 freq = 0.5458 freq = 0.0000 freq = 0.5453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 97: rs97
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.861726 pvalue = 0.0907101 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.585061 pvalue = 0.444335 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003402 pvalue = 0.953491 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1967 sd = 0.0429 freq = 0.1423 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8033 sd = 0.0429 freq = 0.8577 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.1792 freq = 0.0000 freq = 0.1859
+allele 2 : freq = 0.7937 freq = 0.8208 freq = 0.0000 freq = 0.8141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 98: rs98
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000662 pvalue = 0.979478 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.026170 pvalue = 0.871486 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.153654 pvalue = 0.695068 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8133 sd = 0.0421 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.1867 sd = 0.0421 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.8125 freq = 0.0000 freq = 0.8141
+allele 2 : freq = 0.1812 freq = 0.1875 freq = 0.0000 freq = 0.1859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 99: rs99
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.025920 pvalue = 0.872096 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.088820 pvalue = 0.765683 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.997622 pvalue = 0.317887 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6017 sd = 0.0529 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+allele 2 : freq = 0.3983 sd = 0.0529 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.6042 freq = 0.0000 freq = 0.6078
+allele 2 : freq = 0.3812 freq = 0.3958 freq = 0.0000 freq = 0.3922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 100: rs100
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.421162 pvalue = 0.516358 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.946905 pvalue = 0.330508 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.730147 pvalue = 0.188392 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6900 sd = 0.0500 freq = 0.6673 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.3100 sd = 0.0500 freq = 0.3327 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6479 freq = 0.0000 freq = 0.6594
+allele 2 : freq = 0.3063 freq = 0.3521 freq = 0.0000 freq = 0.3406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 101: rs101
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.068210 pvalue = 0.793961 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.084663 pvalue = 0.771075 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.399162 pvalue = 0.527522 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4646 freq = 0.0000 freq = 0.4609
+allele 2 : freq = 0.5500 freq = 0.5354 freq = 0.0000 freq = 0.5391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 102: rs102
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.905888 pvalue = 0.341208 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.115500 pvalue = 0.290889 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.175376 pvalue = 0.675378 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7767 sd = 0.0450 freq = 0.8192 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.2233 sd = 0.0450 freq = 0.1808 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.8229 freq = 0.0000 freq = 0.8125
+allele 2 : freq = 0.2188 freq = 0.1771 freq = 0.0000 freq = 0.1875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 103: rs103
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.184305 pvalue = 0.6677 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015696 pvalue = 0.900299 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.685468 pvalue = 0.40771 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1483 sd = 0.0384 freq = 0.1250 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+allele 2 : freq = 0.8517 sd = 0.0384 freq = 0.8750 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.1479 freq = 0.0000 freq = 0.1469
+allele 2 : freq = 0.8562 freq = 0.8521 freq = 0.0000 freq = 0.8531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 104: rs104
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000041 pvalue = 0.99488 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.682405 pvalue = 0.40876 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.132451 pvalue = 0.715904 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2950 sd = 0.0493 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+allele 2 : freq = 0.7050 sd = 0.0493 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.3375 freq = 0.0000 freq = 0.3281
+allele 2 : freq = 0.7000 freq = 0.6625 freq = 0.0000 freq = 0.6719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 105: rs105
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000058 pvalue = 0.993931 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001899 pvalue = 0.965239 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.013271 pvalue = 0.908287 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6733 sd = 0.0507 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+allele 2 : freq = 0.3267 sd = 0.0507 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6562 freq = 0.6583 freq = 0.0000 freq = 0.6578
+allele 2 : freq = 0.3438 freq = 0.3417 freq = 0.0000 freq = 0.3422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 106: rs106
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.708519 pvalue = 0.399936 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.098318 pvalue = 0.753857 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000219 pvalue = 0.988191 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7300 sd = 0.0480 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+allele 2 : freq = 0.2700 sd = 0.0480 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.7167 freq = 0.0000 freq = 0.7203
+allele 2 : freq = 0.2687 freq = 0.2833 freq = 0.0000 freq = 0.2797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 107: rs107
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.314197 pvalue = 0.575116 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.722750 pvalue = 0.395243 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.234047 pvalue = 0.628539 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7267 sd = 0.0481 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310
+allele 2 : freq = 0.2733 sd = 0.0481 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.7625 freq = 0.0000 freq = 0.7531
+allele 2 : freq = 0.2750 freq = 0.2375 freq = 0.0000 freq = 0.2469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 108: rs108
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.511812 pvalue = 0.112996 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.027605 pvalue = 0.310722 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.037605 pvalue = 0.846239 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2367 sd = 0.0459 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275
+allele 2 : freq = 0.7633 sd = 0.0459 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2042 freq = 0.0000 freq = 0.2141
+allele 2 : freq = 0.7562 freq = 0.7958 freq = 0.0000 freq = 0.7859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 109: rs109
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.621670 pvalue = 0.202859 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.354605 pvalue = 0.244475 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.656656 pvalue = 0.417743 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5983 sd = 0.0530 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4017 sd = 0.0530 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5938 freq = 0.5354 freq = 0.0000 freq = 0.5500
+allele 2 : freq = 0.4062 freq = 0.4646 freq = 0.0000 freq = 0.4500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 110: rs110
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.554095 pvalue = 0.456649 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.412021 pvalue = 0.520945 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.019993 pvalue = 0.887557 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5850 sd = 0.0532 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.4150 sd = 0.0532 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5938 freq = 0.6250 freq = 0.0000 freq = 0.6172
+allele 2 : freq = 0.4062 freq = 0.3750 freq = 0.0000 freq = 0.3828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 111: rs111
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.028862 pvalue = 0.865098 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.009248 pvalue = 0.923387 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.7688 freq = 0.0000 freq = 0.7688
+allele 2 : freq = 0.2313 freq = 0.2313 freq = 0.0000 freq = 0.2313
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 112: rs112
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.441557 pvalue = 0.229888 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.460253 pvalue = 0.11676 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.544859 pvalue = 0.460426 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.7346 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2654 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7125 freq = 0.0000 freq = 0.7297
+allele 2 : freq = 0.2188 freq = 0.2875 freq = 0.0000 freq = 0.2703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 113: rs113
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.041271 pvalue = 0.839015 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.117968 pvalue = 0.731249 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.004959 pvalue = 0.316113 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8067 sd = 0.0427 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+allele 2 : freq = 0.1933 sd = 0.0427 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8313 freq = 0.8187 freq = 0.0000 freq = 0.8219
+allele 2 : freq = 0.1688 freq = 0.1812 freq = 0.0000 freq = 0.1781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 114: rs114
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.217585 pvalue = 0.136446 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.842310 pvalue = 0.0918122 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.383502 pvalue = 0.122622 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 sd = 0.0495 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.3000 sd = 0.0495 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7063 freq = 0.7792 freq = 0.0000 freq = 0.7609
+allele 2 : freq = 0.2938 freq = 0.2208 freq = 0.0000 freq = 0.2391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 115: rs115
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.037117 pvalue = 0.847228 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.043269 pvalue = 0.835219 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.054610 pvalue = 0.815227 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4300 sd = 0.0535 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+allele 2 : freq = 0.5700 sd = 0.0535 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4625 freq = 0.4521 freq = 0.0000 freq = 0.4547
+allele 2 : freq = 0.5375 freq = 0.5479 freq = 0.0000 freq = 0.5453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 116: rs116
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.026988 pvalue = 0.869511 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027376 pvalue = 0.868585 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.479541 pvalue = 0.488631 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8183 sd = 0.0416 freq = 0.8231 sd = 0.0290 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1817 sd = 0.0416 freq = 0.1769 sd = 0.0290 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.8313 freq = 0.0000 freq = 0.8297
+allele 2 : freq = 0.1750 freq = 0.1688 freq = 0.0000 freq = 0.1703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 117: rs117
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.032303 pvalue = 0.857365 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.664681 pvalue = 0.414912 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.218913 pvalue = 0.63987 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3883 sd = 0.0526 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+allele 2 : freq = 0.6117 sd = 0.0526 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.4146 freq = 0.0000 freq = 0.4047
+allele 2 : freq = 0.6250 freq = 0.5854 freq = 0.0000 freq = 0.5953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 118: rs118
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.136636 pvalue = 0.711649 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.112161 pvalue = 0.737697 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006248 pvalue = 0.936999 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7017 sd = 0.0494 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+allele 2 : freq = 0.2983 sd = 0.0494 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.7104 freq = 0.0000 freq = 0.7141
+allele 2 : freq = 0.2750 freq = 0.2896 freq = 0.0000 freq = 0.2859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 119: rs119
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.040785 pvalue = 0.839953 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.280414 pvalue = 0.59643 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.500141 pvalue = 0.22065 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8600 sd = 0.0375 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+allele 2 : freq = 0.1400 sd = 0.0375 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8562 freq = 0.8375 freq = 0.0000 freq = 0.8422
+allele 2 : freq = 0.1437 freq = 0.1625 freq = 0.0000 freq = 0.1578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 120: rs120
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.071256 pvalue = 0.789516 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007062 pvalue = 0.933028 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 1.172707 pvalue = 0.278846 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9400 sd = 0.0257 freq = 0.9346 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174
+allele 2 : freq = 0.0600 sd = 0.0257 freq = 0.0654 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9437 freq = 0.9458 freq = 0.0000 freq = 0.9453
+allele 2 : freq = 0.0563 freq = 0.0542 freq = 0.0000 freq = 0.0547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 121: rs121
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.175809 pvalue = 0.675 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.231425 pvalue = 0.630469 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.654845 pvalue = 0.418386 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.3500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.6500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3479 freq = 0.0000 freq = 0.3422
+allele 2 : freq = 0.6750 freq = 0.6521 freq = 0.0000 freq = 0.6578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 122: rs122
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.090434 pvalue = 0.763627 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.444872 pvalue = 0.50478 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.616427 pvalue = 0.432378 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4583 sd = 0.0538 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5417 sd = 0.0538 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4167 freq = 0.0000 freq = 0.4250
+allele 2 : freq = 0.5500 freq = 0.5833 freq = 0.0000 freq = 0.5750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 123: rs123
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.099279 pvalue = 0.752696 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.145472 pvalue = 0.7029 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.283139 pvalue = 0.594651 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3883 sd = 0.0526 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6117 sd = 0.0526 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.3875 freq = 0.0000 freq = 0.3922
+allele 2 : freq = 0.5938 freq = 0.6125 freq = 0.0000 freq = 0.6078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 124: rs124
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.603482 pvalue = 0.437252 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.363801 pvalue = 0.546403 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.287906 pvalue = 0.591566 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2567 sd = 0.0472 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+allele 2 : freq = 0.7433 sd = 0.0472 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2708 freq = 0.0000 freq = 0.2641
+allele 2 : freq = 0.7562 freq = 0.7292 freq = 0.0000 freq = 0.7359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 125: rs125
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.013759 pvalue = 0.906624 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001721 pvalue = 0.966909 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.695819 pvalue = 0.192836 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4717 sd = 0.0539 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+allele 2 : freq = 0.5283 sd = 0.0539 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.4708 freq = 0.0000 freq = 0.4703
+allele 2 : freq = 0.5312 freq = 0.5292 freq = 0.0000 freq = 0.5297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 126: rs126
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.083435 pvalue = 0.0433055 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.380773 pvalue = 0.0659611 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.232724 pvalue = 0.0396517 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6350 sd = 0.0520 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+allele 2 : freq = 0.3650 sd = 0.0520 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 freq = 0.5583 freq = 0.0000 freq = 0.5813
+allele 2 : freq = 0.3500 freq = 0.4417 freq = 0.0000 freq = 0.4188
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 127: rs127
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.130602 pvalue = 0.287647 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.493199 pvalue = 0.482504 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.202135 pvalue = 0.653003 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3033 sd = 0.0497 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.6967 sd = 0.0497 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.3208 freq = 0.0000 freq = 0.3125
+allele 2 : freq = 0.7125 freq = 0.6792 freq = 0.0000 freq = 0.6875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 128: rs128
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.370585 pvalue = 0.241711 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.621988 pvalue = 0.43031 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.277625 pvalue = 0.0702305 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.4854 freq = 0.0000 freq = 0.4953
+allele 2 : freq = 0.4750 freq = 0.5146 freq = 0.0000 freq = 0.5047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 129: rs129
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.059609 pvalue = 0.807115 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.035256 pvalue = 0.85106 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.754446 pvalue = 0.385072 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2700 sd = 0.0480 freq = 0.2712 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+allele 2 : freq = 0.7300 sd = 0.0480 freq = 0.7288 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2812 freq = 0.2896 freq = 0.0000 freq = 0.2875
+allele 2 : freq = 0.7188 freq = 0.7104 freq = 0.0000 freq = 0.7125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 130: rs130
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001656 pvalue = 0.967536 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015607 pvalue = 0.900581 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.118329 pvalue = 0.730854 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4600 sd = 0.0538 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5400 sd = 0.0538 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4437 freq = 0.0000 freq = 0.4453
+allele 2 : freq = 0.5500 freq = 0.5563 freq = 0.0000 freq = 0.5547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 131: rs131
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.181830 pvalue = 0.669806 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.329617 pvalue = 0.565885 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.224560 pvalue = 0.268468 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7533 sd = 0.0466 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+allele 2 : freq = 0.2467 sd = 0.0466 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7375 freq = 0.0000 freq = 0.7438
+allele 2 : freq = 0.2375 freq = 0.2625 freq = 0.0000 freq = 0.2562
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 132: rs132
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.064130 pvalue = 0.800084 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001989 pvalue = 0.964427 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.125085 pvalue = 0.723583 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3050 sd = 0.0497 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.6950 sd = 0.0497 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.2979 freq = 0.0000 freq = 0.2984
+allele 2 : freq = 0.7000 freq = 0.7021 freq = 0.0000 freq = 0.7016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 133: rs133
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.282678 pvalue = 0.594951 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.084708 pvalue = 0.771015 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000257 pvalue = 0.987212 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2550 sd = 0.0471 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+allele 2 : freq = 0.7450 sd = 0.0471 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2625 freq = 0.2500 freq = 0.0000 freq = 0.2531
+allele 2 : freq = 0.7375 freq = 0.7500 freq = 0.0000 freq = 0.7469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 134: rs134
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.418456 pvalue = 0.517708 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.424472 pvalue = 0.514714 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.158581 pvalue = 0.28176 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6717 sd = 0.0507 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.3283 sd = 0.0507 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.6438 freq = 0.0000 freq = 0.6516
+allele 2 : freq = 0.3250 freq = 0.3563 freq = 0.0000 freq = 0.3484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 135: rs135
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.326426 pvalue = 0.249442 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.093649 pvalue = 0.295664 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.184775 pvalue = 0.276386 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8021 freq = 0.0000 freq = 0.8125
+allele 2 : freq = 0.1562 freq = 0.1979 freq = 0.0000 freq = 0.1875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 136: rs136
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.953136 pvalue = 0.328922 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.858732 pvalue = 0.354094 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.843795 pvalue = 0.358314 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.5923 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.4077 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5500 freq = 0.5958 freq = 0.0000 freq = 0.5844
+allele 2 : freq = 0.4500 freq = 0.4042 freq = 0.0000 freq = 0.4156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 137: rs137
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.942677 pvalue = 0.33159 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.198906 pvalue = 0.655606 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.055593 pvalue = 0.813601 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.6788 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.3212 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.7104 freq = 0.0000 freq = 0.7156
+allele 2 : freq = 0.2687 freq = 0.2896 freq = 0.0000 freq = 0.2844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 138: rs138
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.718893 pvalue = 0.396507 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.391004 pvalue = 0.238236 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.325624 pvalue = 0.568247 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4200 sd = 0.0533 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+allele 2 : freq = 0.5800 sd = 0.0533 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.3792 freq = 0.0000 freq = 0.3937
+allele 2 : freq = 0.5625 freq = 0.6208 freq = 0.0000 freq = 0.6062
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 139: rs139
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.696473 pvalue = 0.403971 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.585142 pvalue = 0.444304 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.620944 pvalue = 0.430697 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3021 freq = 0.0000 freq = 0.3109
+allele 2 : freq = 0.6625 freq = 0.6979 freq = 0.0000 freq = 0.6891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 140: rs140
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.365716 pvalue = 0.242549 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.352008 pvalue = 0.552979 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.056667 pvalue = 0.811844 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3617 sd = 0.0519 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6383 sd = 0.0519 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3667 freq = 0.0000 freq = 0.3594
+allele 2 : freq = 0.6625 freq = 0.6333 freq = 0.0000 freq = 0.6406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 141: rs141
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.599410 pvalue = 0.106904 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.519566 pvalue = 0.217685 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.932156 pvalue = 0.334303 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321
+allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3563 freq = 0.3000 freq = 0.0000 freq = 0.3141
+allele 2 : freq = 0.6438 freq = 0.7000 freq = 0.0000 freq = 0.6859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 142: rs142
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.058954 pvalue = 0.808157 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.119961 pvalue = 0.729077 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.245049 pvalue = 0.2645 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3617 sd = 0.0519 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+allele 2 : freq = 0.6383 sd = 0.0519 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.3458 freq = 0.0000 freq = 0.3500
+allele 2 : freq = 0.6375 freq = 0.6542 freq = 0.0000 freq = 0.6500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 143: rs143
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.638395 pvalue = 0.424293 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.211880 pvalue = 0.645298 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001721 pvalue = 0.966913 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5267 sd = 0.0539 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.4733 sd = 0.0539 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5312 freq = 0.5542 freq = 0.0000 freq = 0.5484
+allele 2 : freq = 0.4688 freq = 0.4458 freq = 0.0000 freq = 0.4516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 144: rs144
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.829054 pvalue = 0.0925729 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.442272 pvalue = 0.118105 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.481503 pvalue = 0.223539 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8933 sd = 0.0333 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1067 sd = 0.0333 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8292 freq = 0.0000 freq = 0.8438
+allele 2 : freq = 0.1125 freq = 0.1708 freq = 0.0000 freq = 0.1562
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 145: rs145
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.990865 pvalue = 0.0457476 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.330625 pvalue = 0.126851 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.811397 pvalue = 0.367708 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7650 sd = 0.0458 freq = 0.8212 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+allele 2 : freq = 0.2350 sd = 0.0458 freq = 0.1788 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.8146 freq = 0.0000 freq = 0.8000
+allele 2 : freq = 0.2437 freq = 0.1854 freq = 0.0000 freq = 0.2000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 146: rs146
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.228477 pvalue = 0.267703 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.587376 pvalue = 0.207701 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.173307 pvalue = 0.677189 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6650 sd = 0.0510 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+allele 2 : freq = 0.3350 sd = 0.0510 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6562 freq = 0.7146 freq = 0.0000 freq = 0.7000
+allele 2 : freq = 0.3438 freq = 0.2854 freq = 0.0000 freq = 0.3000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 147: rs147
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.116206 pvalue = 0.733186 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.843049 pvalue = 0.358526 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.023011 pvalue = 0.879429 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5600 sd = 0.0536 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+allele 2 : freq = 0.4400 sd = 0.0536 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5167 freq = 0.0000 freq = 0.5281
+allele 2 : freq = 0.4375 freq = 0.4833 freq = 0.0000 freq = 0.4719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 148: rs148
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.665824 pvalue = 0.414511 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.258663 pvalue = 0.61104 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.909191 pvalue = 0.167053 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1577 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8423 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1313 freq = 0.1500 freq = 0.0000 freq = 0.1453
+allele 2 : freq = 0.8688 freq = 0.8500 freq = 0.0000 freq = 0.8547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 149: rs149
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.721183 pvalue = 0.395756 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.895142 pvalue = 0.344088 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.921955 pvalue = 0.336962 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8817 sd = 0.0349 freq = 0.8962 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217
+allele 2 : freq = 0.1183 sd = 0.0349 freq = 0.1038 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8750 freq = 0.9042 freq = 0.0000 freq = 0.8969
+allele 2 : freq = 0.1250 freq = 0.0958 freq = 0.0000 freq = 0.1031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 150: rs150
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.351305 pvalue = 0.553375 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.861744 pvalue = 0.353251 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8423 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1577 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8625 freq = 0.8292 freq = 0.0000 freq = 0.8375
+allele 2 : freq = 0.1375 freq = 0.1708 freq = 0.0000 freq = 0.1625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 151: rs151
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.410052 pvalue = 0.521943 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.248430 pvalue = 0.618183 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.067996 pvalue = 0.794277 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5133 sd = 0.0540 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+allele 2 : freq = 0.4867 sd = 0.0540 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.5312 freq = 0.0000 freq = 0.5250
+allele 2 : freq = 0.4938 freq = 0.4688 freq = 0.0000 freq = 0.4750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 152: rs152
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.979428 pvalue = 0.32234 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.117000 pvalue = 0.145672 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.493121 pvalue = 0.221733 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8450 sd = 0.0391 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.1550 sd = 0.0391 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8938 freq = 0.0000 freq = 0.8812
+allele 2 : freq = 0.1562 freq = 0.1062 freq = 0.0000 freq = 0.1187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 153: rs153
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.019745 pvalue = 0.888252 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.043352 pvalue = 0.835063 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.018933 pvalue = 0.89056 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4283 sd = 0.0534 freq = 0.4346 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5717 sd = 0.0534 freq = 0.5654 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4271 freq = 0.0000 freq = 0.4297
+allele 2 : freq = 0.5625 freq = 0.5729 freq = 0.0000 freq = 0.5703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 154: rs154
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.123632 pvalue = 0.725128 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.062201 pvalue = 0.80305 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.550074 pvalue = 0.458287 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.5437 freq = 0.0000 freq = 0.5469
+allele 2 : freq = 0.4437 freq = 0.4562 freq = 0.0000 freq = 0.4531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 155: rs155
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.625710 pvalue = 0.202298 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.620619 pvalue = 0.105483 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.648553 pvalue = 0.00992364 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4333 sd = 0.0535 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+allele 2 : freq = 0.5667 sd = 0.0535 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.5062 freq = 0.0000 freq = 0.4859
+allele 2 : freq = 0.5750 freq = 0.4938 freq = 0.0000 freq = 0.5141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 156: rs156
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.476640 pvalue = 0.489948 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.354427 pvalue = 0.551618 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006718 pvalue = 0.934676 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2400 sd = 0.0461 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+allele 2 : freq = 0.7600 sd = 0.0461 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.2250 freq = 0.0000 freq = 0.2313
+allele 2 : freq = 0.7500 freq = 0.7750 freq = 0.0000 freq = 0.7688
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 157: rs157
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.238737 pvalue = 0.134591 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.254849 pvalue = 0.613681 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.045070 pvalue = 0.831875 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2200 sd = 0.0447 freq = 0.2750 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+allele 2 : freq = 0.7800 sd = 0.0447 freq = 0.7250 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2125 freq = 0.2354 freq = 0.0000 freq = 0.2297
+allele 2 : freq = 0.7875 freq = 0.7646 freq = 0.0000 freq = 0.7703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 158: rs158
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.118739 pvalue = 0.145506 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.559421 pvalue = 0.21175 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.459515 pvalue = 0.497851 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2562 freq = 0.3146 freq = 0.0000 freq = 0.3000
+allele 2 : freq = 0.7438 freq = 0.6854 freq = 0.0000 freq = 0.7000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 159: rs159
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.185909 pvalue = 0.276156 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.514053 pvalue = 0.47339 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.002989 pvalue = 0.956401 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8365 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1635 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8417 freq = 0.0000 freq = 0.8484
+allele 2 : freq = 0.1313 freq = 0.1583 freq = 0.0000 freq = 0.1516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 160: rs160
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.339008 pvalue = 0.560402 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.068353 pvalue = 0.79375 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.408656 pvalue = 0.522652 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7650 sd = 0.0458 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+allele 2 : freq = 0.2350 sd = 0.0458 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7917 freq = 0.0000 freq = 0.7891
+allele 2 : freq = 0.2188 freq = 0.2083 freq = 0.0000 freq = 0.2109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 161: rs161
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.005035 pvalue = 0.943431 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015179 pvalue = 0.901946 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.026516 pvalue = 0.870647 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1217 sd = 0.0353 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238
+allele 2 : freq = 0.8783 sd = 0.0353 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1313 freq = 0.1271 freq = 0.0000 freq = 0.1281
+allele 2 : freq = 0.8688 freq = 0.8729 freq = 0.0000 freq = 0.8719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 162: rs162
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.033875 pvalue = 0.853973 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.112069 pvalue = 0.737801 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.027530 pvalue = 0.868219 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6217 sd = 0.0524 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.3783 sd = 0.0524 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.6042 freq = 0.0000 freq = 0.6000
+allele 2 : freq = 0.4125 freq = 0.3958 freq = 0.0000 freq = 0.4000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 163: rs163
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.612650 pvalue = 0.433792 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.017186 pvalue = 0.313188 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.320948 pvalue = 0.571038 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2550 sd = 0.0471 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+allele 2 : freq = 0.7450 sd = 0.0471 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.1958 freq = 0.0000 freq = 0.2062
+allele 2 : freq = 0.7625 freq = 0.8042 freq = 0.0000 freq = 0.7937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 164: rs164
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.185257 pvalue = 0.666893 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.085803 pvalue = 0.769583 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.009368 pvalue = 0.922895 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4354 freq = 0.0000 freq = 0.4391
+allele 2 : freq = 0.5500 freq = 0.5646 freq = 0.0000 freq = 0.5609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 165: rs165
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.088562 pvalue = 0.766014 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.254058 pvalue = 0.262779 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.355245 pvalue = 0.0368952 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6850 sd = 0.0502 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+allele 2 : freq = 0.3150 sd = 0.0502 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.7458 freq = 0.0000 freq = 0.7328
+allele 2 : freq = 0.3063 freq = 0.2542 freq = 0.0000 freq = 0.2672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 166: rs166
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007888 pvalue = 0.92923 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.074318 pvalue = 0.78515 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.981790 pvalue = 0.321757 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8150 sd = 0.0419 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+allele 2 : freq = 0.1850 sd = 0.0419 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.8146 freq = 0.0000 freq = 0.8172
+allele 2 : freq = 0.1750 freq = 0.1854 freq = 0.0000 freq = 0.1828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 167: rs167
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.073754 pvalue = 0.785947 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.033078 pvalue = 0.855682 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.385619 pvalue = 0.534611 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.1375 freq = 0.0000 freq = 0.1391
+allele 2 : freq = 0.8562 freq = 0.8625 freq = 0.0000 freq = 0.8609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 168: rs168
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.749491 pvalue = 0.386637 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.891151 pvalue = 0.345166 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.157601 pvalue = 0.691375 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3350 sd = 0.0510 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+allele 2 : freq = 0.6650 sd = 0.0510 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3833 freq = 0.0000 freq = 0.3719
+allele 2 : freq = 0.6625 freq = 0.6167 freq = 0.0000 freq = 0.6281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 169: rs169
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.044061 pvalue = 0.83374 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.603547 pvalue = 0.437228 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.637792 pvalue = 0.424512 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339
+allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.4000 freq = 0.0000 freq = 0.3906
+allele 2 : freq = 0.6375 freq = 0.6000 freq = 0.0000 freq = 0.6094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 170: rs170
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.017964 pvalue = 0.893379 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.018222 pvalue = 0.892619 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.849736 pvalue = 0.356627 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 freq = 0.6937 freq = 0.0000 freq = 0.6953
+allele 2 : freq = 0.3000 freq = 0.3063 freq = 0.0000 freq = 0.3047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 171: rs171
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.669095 pvalue = 0.19638 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.711590 pvalue = 0.190779 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001750 pvalue = 0.966631 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5517 sd = 0.0537 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+allele 2 : freq = 0.4483 sd = 0.0537 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.6083 freq = 0.0000 freq = 0.5922
+allele 2 : freq = 0.4562 freq = 0.3917 freq = 0.0000 freq = 0.4078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 172: rs172
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.065490 pvalue = 0.79802 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.519031 pvalue = 0.471255 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.550788 pvalue = 0.457996 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4150 sd = 0.0532 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.5850 sd = 0.0532 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3937 freq = 0.4292 freq = 0.0000 freq = 0.4203
+allele 2 : freq = 0.6062 freq = 0.5708 freq = 0.0000 freq = 0.5797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 173: rs173
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.108963 pvalue = 0.741328 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.004064 pvalue = 0.949168 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.074991 pvalue = 0.784204 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8833 sd = 0.0347 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230
+allele 2 : freq = 0.1167 sd = 0.0347 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8938 freq = 0.8958 freq = 0.0000 freq = 0.8953
+allele 2 : freq = 0.1062 freq = 0.1042 freq = 0.0000 freq = 0.1047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 174: rs174
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.616532 pvalue = 0.432339 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.855637 pvalue = 0.354962 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.967731 pvalue = 0.0849409 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5650 sd = 0.0535 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+allele 2 : freq = 0.4350 sd = 0.0535 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.6021 freq = 0.0000 freq = 0.5906
+allele 2 : freq = 0.4437 freq = 0.3979 freq = 0.0000 freq = 0.4094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 175: rs175
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000154 pvalue = 0.990108 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.096646 pvalue = 0.755892 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.310952 pvalue = 0.577097 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3067 sd = 0.0498 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+allele 2 : freq = 0.6933 sd = 0.0498 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3396 freq = 0.0000 freq = 0.3359
+allele 2 : freq = 0.6750 freq = 0.6604 freq = 0.0000 freq = 0.6641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 176: rs176
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.194771 pvalue = 0.13848 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.420400 pvalue = 0.233338 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.007658 pvalue = 0.930266 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9283 sd = 0.0279 freq = 0.8885 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221
+allele 2 : freq = 0.0717 sd = 0.0279 freq = 0.1115 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9313 freq = 0.8938 freq = 0.0000 freq = 0.9031
+allele 2 : freq = 0.0688 freq = 0.1062 freq = 0.0000 freq = 0.0969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 177: rs177
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.585220 pvalue = 0.444274 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.025099 pvalue = 0.874121 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.010961 pvalue = 0.916618 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8417 sd = 0.0394 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.1583 sd = 0.0394 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8375 freq = 0.0000 freq = 0.8391
+allele 2 : freq = 0.1562 freq = 0.1625 freq = 0.0000 freq = 0.1609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 178: rs178
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.311653 pvalue = 0.576668 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.939518 pvalue = 0.332402 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.102575 pvalue = 0.748761 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3533 sd = 0.0516 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+allele 2 : freq = 0.6467 sd = 0.0516 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.2979 freq = 0.0000 freq = 0.3094
+allele 2 : freq = 0.6562 freq = 0.7021 freq = 0.0000 freq = 0.6906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 179: rs179
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.972790 pvalue = 0.0462411 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.822243 pvalue = 0.177047 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.165005 pvalue = 0.0130302 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7188 freq = 0.0000 freq = 0.7344
+allele 2 : freq = 0.2188 freq = 0.2812 freq = 0.0000 freq = 0.2656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 180: rs180
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.259590 pvalue = 0.610402 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.782566 pvalue = 0.376357 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.133499 pvalue = 0.714831 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.6458 freq = 0.0000 freq = 0.6562
+allele 2 : freq = 0.3125 freq = 0.3542 freq = 0.0000 freq = 0.3438
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 181: rs181
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.558715 pvalue = 0.454778 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.700907 pvalue = 0.402479 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.012244 pvalue = 0.911892 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1483 sd = 0.0384 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+allele 2 : freq = 0.8517 sd = 0.0384 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.1750 freq = 0.0000 freq = 0.1672
+allele 2 : freq = 0.8562 freq = 0.8250 freq = 0.0000 freq = 0.8328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 182: rs182
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.175221 pvalue = 0.278331 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.210532 pvalue = 0.271227 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.455170 pvalue = 0.2277 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7400 sd = 0.0474 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+allele 2 : freq = 0.2600 sd = 0.0474 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7438 freq = 0.7896 freq = 0.0000 freq = 0.7781
+allele 2 : freq = 0.2562 freq = 0.2104 freq = 0.0000 freq = 0.2219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 183: rs183
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.398068 pvalue = 0.0652728 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.407367 pvalue = 0.235494 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.248894 pvalue = 0.617855 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8767 sd = 0.0355 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.1233 sd = 0.0355 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8417 freq = 0.0000 freq = 0.8531
+allele 2 : freq = 0.1125 freq = 0.1583 freq = 0.0000 freq = 0.1469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 184: rs184
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.971922 pvalue = 0.324201 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.268391 pvalue = 0.132037 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.703757 pvalue = 0.401524 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3817 sd = 0.0525 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340
+allele 2 : freq = 0.6183 sd = 0.0525 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3937 freq = 0.3208 freq = 0.0000 freq = 0.3391
+allele 2 : freq = 0.6062 freq = 0.6792 freq = 0.0000 freq = 0.6609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 185: rs185
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001744 pvalue = 0.966688 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.249702 pvalue = 0.617285 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.014420 pvalue = 0.904418 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6917 sd = 0.0499 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.3083 sd = 0.0499 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6708 freq = 0.0000 freq = 0.6766
+allele 2 : freq = 0.3063 freq = 0.3292 freq = 0.0000 freq = 0.3234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 186: rs186
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.404288 pvalue = 0.524883 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.017339 pvalue = 0.895239 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.659621 pvalue = 0.416694 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 sd = 0.0523 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.6250 sd = 0.0523 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3688 freq = 0.3625 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.6312 freq = 0.6375 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 187: rs187
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.248948 pvalue = 0.133705 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.748834 pvalue = 0.186023 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.338953 pvalue = 0.126174 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7375 freq = 0.7917 freq = 0.0000 freq = 0.7781
+allele 2 : freq = 0.2625 freq = 0.2083 freq = 0.0000 freq = 0.2219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 188: rs188
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.275981 pvalue = 0.599348 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.584519 pvalue = 0.444546 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.671240 pvalue = 0.0306718 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3933 sd = 0.0528 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.6067 sd = 0.0528 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.3688 freq = 0.0000 freq = 0.3781
+allele 2 : freq = 0.5938 freq = 0.6312 freq = 0.0000 freq = 0.6219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 189: rs189
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.181422 pvalue = 0.670154 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.030825 pvalue = 0.860632 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.733559 pvalue = 0.0982601 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6350 sd = 0.0520 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+allele 2 : freq = 0.3650 sd = 0.0520 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.6292 freq = 0.0000 freq = 0.6312
+allele 2 : freq = 0.3625 freq = 0.3708 freq = 0.0000 freq = 0.3688
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 190: rs190
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.993245 pvalue = 0.318951 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.859713 pvalue = 0.172658 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.713183 pvalue = 0.190573 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9062 freq = 0.8625 freq = 0.0000 freq = 0.8734
+allele 2 : freq = 0.0938 freq = 0.1375 freq = 0.0000 freq = 0.1266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 191: rs191
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.015000 pvalue = 0.902522 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.061828 pvalue = 0.80363 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.036751 pvalue = 0.847972 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4933 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+allele 2 : freq = 0.5067 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5125 freq = 0.5000 freq = 0.0000 freq = 0.5031
+allele 2 : freq = 0.4875 freq = 0.5000 freq = 0.0000 freq = 0.4969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 192: rs192
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.036535 pvalue = 0.848415 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.344229 pvalue = 0.557398 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.385371 pvalue = 0.239188 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5767 sd = 0.0534 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+allele 2 : freq = 0.4233 sd = 0.0534 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.6042 freq = 0.0000 freq = 0.5969
+allele 2 : freq = 0.4250 freq = 0.3958 freq = 0.0000 freq = 0.4031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 193: rs193
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.609525 pvalue = 0.204559 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.609078 pvalue = 0.204622 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.287780 pvalue = 0.130396 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8733 sd = 0.0359 freq = 0.8288 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1267 sd = 0.0359 freq = 0.1712 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8208 freq = 0.0000 freq = 0.8328
+allele 2 : freq = 0.1313 freq = 0.1792 freq = 0.0000 freq = 0.1672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 194: rs194
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.046658 pvalue = 0.828985 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.114450 pvalue = 0.735133 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.098238 pvalue = 0.294653 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.4058 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.5942 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3937 freq = 0.4104 freq = 0.0000 freq = 0.4062
+allele 2 : freq = 0.6062 freq = 0.5896 freq = 0.0000 freq = 0.5938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 195: rs195
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.071708 pvalue = 0.150053 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.510400 pvalue = 0.219078 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.063530 pvalue = 0.801001 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4267 sd = 0.0534 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.5733 sd = 0.0534 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.3958 freq = 0.0000 freq = 0.4109
+allele 2 : freq = 0.5437 freq = 0.6042 freq = 0.0000 freq = 0.5891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 196: rs196
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.182461 pvalue = 0.139591 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.792017 pvalue = 0.373491 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.880202 pvalue = 0.348146 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6633 sd = 0.0510 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.3367 sd = 0.0510 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.6312 freq = 0.0000 freq = 0.6422
+allele 2 : freq = 0.3250 freq = 0.3688 freq = 0.0000 freq = 0.3578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 197: rs197
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.347146 pvalue = 0.125513 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.469775 pvalue = 0.116055 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.789232 pvalue = 0.0948997 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5500 freq = 0.6271 freq = 0.0000 freq = 0.6078
+allele 2 : freq = 0.4500 freq = 0.3729 freq = 0.0000 freq = 0.3922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 198: rs198
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.754866 pvalue = 0.38494 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.950061 pvalue = 0.329704 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.033137 pvalue = 0.855554 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6450 sd = 0.0517 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.3550 sd = 0.0517 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.5896 freq = 0.0000 freq = 0.6016
+allele 2 : freq = 0.3625 freq = 0.4104 freq = 0.0000 freq = 0.3984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 199: rs199
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.177327 pvalue = 0.67368 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.145472 pvalue = 0.7029 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.518441 pvalue = 0.217856 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4100 sd = 0.0531 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.5900 sd = 0.0531 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.3937 freq = 0.0000 freq = 0.3984
+allele 2 : freq = 0.5875 freq = 0.6062 freq = 0.0000 freq = 0.6016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 200: rs200
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.403165 pvalue = 0.525459 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.089117 pvalue = 0.765302 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.031524 pvalue = 0.859076 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8233 sd = 0.0412 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+allele 2 : freq = 0.1767 sd = 0.0412 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8479 freq = 0.0000 freq = 0.8453
+allele 2 : freq = 0.1625 freq = 0.1521 freq = 0.0000 freq = 0.1547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 201: rs201
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.421310 pvalue = 0.516284 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.101119 pvalue = 0.750491 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.167990 pvalue = 0.279815 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6883 sd = 0.0500 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.3117 sd = 0.0500 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.6896 freq = 0.0000 freq = 0.6859
+allele 2 : freq = 0.3250 freq = 0.3104 freq = 0.0000 freq = 0.3141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 202: rs202
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.396618 pvalue = 0.237291 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.933322 pvalue = 0.164395 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.620308 pvalue = 0.430933 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1417 sd = 0.0377 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221
+allele 2 : freq = 0.8583 sd = 0.0377 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1375 freq = 0.0938 freq = 0.0000 freq = 0.1047
+allele 2 : freq = 0.8625 freq = 0.9062 freq = 0.0000 freq = 0.8953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 203: rs203
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.210292 pvalue = 0.271274 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.280573 pvalue = 0.596326 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.553300 pvalue = 0.456973 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0783 sd = 0.0290 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221
+allele 2 : freq = 0.9217 sd = 0.0290 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0750 freq = 0.0917 freq = 0.0000 freq = 0.0875
+allele 2 : freq = 0.9250 freq = 0.9083 freq = 0.0000 freq = 0.9125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 204: rs204
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.114226 pvalue = 0.735384 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.008923 pvalue = 0.924743 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.515342 pvalue = 0.472835 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310
+allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2479 freq = 0.0000 freq = 0.2469
+allele 2 : freq = 0.7562 freq = 0.7521 freq = 0.0000 freq = 0.7531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 205: rs205
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.449687 pvalue = 0.228578 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.674883 pvalue = 0.195606 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.325086 pvalue = 0.568567 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1417 sd = 0.0377 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+allele 2 : freq = 0.8583 sd = 0.0377 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.1938 freq = 0.0000 freq = 0.1812
+allele 2 : freq = 0.8562 freq = 0.8063 freq = 0.0000 freq = 0.8187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 206: rs206
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.073784 pvalue = 0.785905 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.128329 pvalue = 0.720171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.374009 pvalue = 0.540827 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1400 sd = 0.0375 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8600 sd = 0.0375 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1562 freq = 0.1688 freq = 0.0000 freq = 0.1656
+allele 2 : freq = 0.8438 freq = 0.8313 freq = 0.0000 freq = 0.8344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 207: rs207
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.039915 pvalue = 0.841647 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.017902 pvalue = 0.893563 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.026277 pvalue = 0.871227 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7067 sd = 0.0492 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.2933 sd = 0.0492 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6875 freq = 0.0000 freq = 0.6891
+allele 2 : freq = 0.3063 freq = 0.3125 freq = 0.0000 freq = 0.3109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 208: rs208
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.019996 pvalue = 0.88755 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.040687 pvalue = 0.840142 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.199161 pvalue = 0.138086 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7896 freq = 0.0000 freq = 0.7875
+allele 2 : freq = 0.2188 freq = 0.2104 freq = 0.0000 freq = 0.2125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 209: rs209
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001646 pvalue = 0.967634 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.473893 pvalue = 0.491202 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.552111 pvalue = 0.457456 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7133 sd = 0.0488 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+allele 2 : freq = 0.2867 sd = 0.0488 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.7562 freq = 0.0000 freq = 0.7484
+allele 2 : freq = 0.2750 freq = 0.2437 freq = 0.0000 freq = 0.2516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 210: rs210
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.073893 pvalue = 0.300068 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.577818 pvalue = 0.108371 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.042564 pvalue = 0.836549 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.2687 freq = 0.0000 freq = 0.2875
+allele 2 : freq = 0.6562 freq = 0.7312 freq = 0.0000 freq = 0.7125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 211: rs211
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.457151 pvalue = 0.116991 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.252642 pvalue = 0.263049 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.438068 pvalue = 0.118422 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5867 sd = 0.0532 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+allele 2 : freq = 0.4133 sd = 0.0532 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.5312 freq = 0.0000 freq = 0.5453
+allele 2 : freq = 0.4125 freq = 0.4688 freq = 0.0000 freq = 0.4547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 212: rs212
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.009836 pvalue = 0.920999 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.174984 pvalue = 0.67572 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.687760 pvalue = 0.406927 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1933 sd = 0.0427 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+allele 2 : freq = 0.8067 sd = 0.0427 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.2229 freq = 0.0000 freq = 0.2188
+allele 2 : freq = 0.7937 freq = 0.7771 freq = 0.0000 freq = 0.7812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 213: rs213
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.251046 pvalue = 0.61634 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.695113 pvalue = 0.404431 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.436054 pvalue = 0.230779 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4617 sd = 0.0538 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5383 sd = 0.0538 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4313 freq = 0.4729 freq = 0.0000 freq = 0.4625
+allele 2 : freq = 0.5687 freq = 0.5271 freq = 0.0000 freq = 0.5375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 214: rs214
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.432925 pvalue = 0.231288 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.583745 pvalue = 0.208222 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.607890 pvalue = 0.435584 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0933 sd = 0.0314 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186
+allele 2 : freq = 0.9067 sd = 0.0314 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1000 freq = 0.0667 freq = 0.0000 freq = 0.0750
+allele 2 : freq = 0.9000 freq = 0.9333 freq = 0.0000 freq = 0.9250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 215: rs215
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.495564 pvalue = 0.481456 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.304173 pvalue = 0.581278 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.513603 pvalue = 0.112868 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1938 freq = 0.1729 freq = 0.0000 freq = 0.1781
+allele 2 : freq = 0.8063 freq = 0.8271 freq = 0.0000 freq = 0.8219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 216: rs216
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.171720 pvalue = 0.678587 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.114176 pvalue = 0.735439 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.916709 pvalue = 0.16622 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217
+allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9062 freq = 0.8958 freq = 0.0000 freq = 0.8984
+allele 2 : freq = 0.0938 freq = 0.1042 freq = 0.0000 freq = 0.1016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 217: rs217
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.003186 pvalue = 0.95499 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.062527 pvalue = 0.802545 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.311232 pvalue = 0.128442 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2133 sd = 0.0442 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+allele 2 : freq = 0.7867 sd = 0.0442 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.2083 freq = 0.0000 freq = 0.2109
+allele 2 : freq = 0.7812 freq = 0.7917 freq = 0.0000 freq = 0.7891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 218: rs218
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.017339 pvalue = 0.89524 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.362942 pvalue = 0.546877 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.427794 pvalue = 0.513074 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6333 sd = 0.0521 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340
+allele 2 : freq = 0.3667 sd = 0.0521 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.6021 freq = 0.0000 freq = 0.6094
+allele 2 : freq = 0.3688 freq = 0.3979 freq = 0.0000 freq = 0.3906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 219: rs219
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.383849 pvalue = 0.239447 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.651253 pvalue = 0.198789 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.132451 pvalue = 0.715904 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.6979 freq = 0.0000 freq = 0.7125
+allele 2 : freq = 0.2437 freq = 0.3021 freq = 0.0000 freq = 0.2875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 220: rs220
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.221852 pvalue = 0.637632 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.387036 pvalue = 0.533862 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1250 freq = 0.1250 freq = 0.0000 freq = 0.1250
+allele 2 : freq = 0.8750 freq = 0.8750 freq = 0.0000 freq = 0.8750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 221: rs221
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.183065 pvalue = 0.668752 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.268243 pvalue = 0.604513 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.593048 pvalue = 0.441243 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1783 sd = 0.0413 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+allele 2 : freq = 0.8217 sd = 0.0413 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.2083 freq = 0.0000 freq = 0.2031
+allele 2 : freq = 0.8125 freq = 0.7917 freq = 0.0000 freq = 0.7969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 222: rs222
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.659322 pvalue = 0.416799 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.115461 pvalue = 0.734011 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.038605 pvalue = 0.844233 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5850 sd = 0.0532 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+allele 2 : freq = 0.4150 sd = 0.0532 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.5854 freq = 0.0000 freq = 0.5813
+allele 2 : freq = 0.4313 freq = 0.4146 freq = 0.0000 freq = 0.4188
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 223: rs223
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.363098 pvalue = 0.546791 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.409559 pvalue = 0.522193 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.076465 pvalue = 0.782146 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2467 sd = 0.0466 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+allele 2 : freq = 0.7533 sd = 0.0466 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.2229 freq = 0.0000 freq = 0.2297
+allele 2 : freq = 0.7500 freq = 0.7771 freq = 0.0000 freq = 0.7703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 224: rs224
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.663307 pvalue = 0.197157 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.114311 pvalue = 0.0776073 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 10.374715 pvalue = 0.00127753 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0483 sd = 0.0232 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174
+allele 2 : freq = 0.9517 sd = 0.0232 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0437 freq = 0.0875 freq = 0.0000 freq = 0.0766
+allele 2 : freq = 0.9563 freq = 0.9125 freq = 0.0000 freq = 0.9234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 225: rs225
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.755063 pvalue = 0.384878 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.516815 pvalue = 0.472204 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.122026 pvalue = 0.726847 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 sd = 0.0534 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+allele 2 : freq = 0.4250 sd = 0.0534 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5979 freq = 0.0000 freq = 0.5891
+allele 2 : freq = 0.4375 freq = 0.4021 freq = 0.0000 freq = 0.4109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 226: rs226
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.225087 pvalue = 0.635191 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.873171 pvalue = 0.350079 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.806772 pvalue = 0.369076 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.6458 freq = 0.0000 freq = 0.6344
+allele 2 : freq = 0.4000 freq = 0.3542 freq = 0.0000 freq = 0.3656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 227: rs227
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.096663 pvalue = 0.755872 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.627469 pvalue = 0.428285 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.791930 pvalue = 0.373517 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8017 sd = 0.0431 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.1983 sd = 0.0431 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8125 freq = 0.7812 freq = 0.0000 freq = 0.7891
+allele 2 : freq = 0.1875 freq = 0.2188 freq = 0.0000 freq = 0.2109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 228: rs228
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 9.120176 pvalue = 0.00252806 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 6.524756 pvalue = 0.0106383 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.775847 pvalue = 0.0162479 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.3404 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.6596 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.3583 freq = 0.0000 freq = 0.3891
+allele 2 : freq = 0.5188 freq = 0.6417 freq = 0.0000 freq = 0.6109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 229: rs229
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.936594 pvalue = 0.333155 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.555032 pvalue = 0.212394 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.950934 pvalue = 0.329482 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4883 sd = 0.0540 freq = 0.4481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+allele 2 : freq = 0.5117 sd = 0.0540 freq = 0.5519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4938 freq = 0.4313 freq = 0.0000 freq = 0.4469
+allele 2 : freq = 0.5062 freq = 0.5687 freq = 0.0000 freq = 0.5531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 230: rs230
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.899426 pvalue = 0.168143 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.079561 pvalue = 0.298796 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.596690 pvalue = 0.439844 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9267 sd = 0.0282 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.0733 sd = 0.0282 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9250 freq = 0.8917 freq = 0.0000 freq = 0.9000
+allele 2 : freq = 0.0750 freq = 0.1083 freq = 0.0000 freq = 0.1000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 231: rs231
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.231512 pvalue = 0.630405 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.339232 pvalue = 0.560273 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.613941 pvalue = 0.433308 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5333 freq = 0.0000 freq = 0.5406
+allele 2 : freq = 0.4375 freq = 0.4667 freq = 0.0000 freq = 0.4594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 232: rs232
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.006434 pvalue = 0.936069 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.109502 pvalue = 0.740711 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.175677 pvalue = 0.675115 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8383 sd = 0.0398 freq = 0.8288 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1617 sd = 0.0398 freq = 0.1712 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8313 freq = 0.8438 freq = 0.0000 freq = 0.8406
+allele 2 : freq = 0.1688 freq = 0.1562 freq = 0.0000 freq = 0.1594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 233: rs233
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.069792 pvalue = 0.791641 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.122554 pvalue = 0.726281 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001092 pvalue = 0.973635 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7729 freq = 0.0000 freq = 0.7766
+allele 2 : freq = 0.2125 freq = 0.2271 freq = 0.0000 freq = 0.2234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 234: rs234
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.069181 pvalue = 0.792533 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.176548 pvalue = 0.674357 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.811875 pvalue = 0.0282643 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9200 sd = 0.0293 freq = 0.9346 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174
+allele 2 : freq = 0.0800 sd = 0.0293 freq = 0.0654 sd = 0.0188 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9313 freq = 0.9417 freq = 0.0000 freq = 0.9391
+allele 2 : freq = 0.0688 freq = 0.0583 freq = 0.0000 freq = 0.0609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 235: rs235
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000104 pvalue = 0.991849 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.174627 pvalue = 0.676032 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.369107 pvalue = 0.543491 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4117 sd = 0.0532 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5883 sd = 0.0532 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4437 freq = 0.4646 freq = 0.0000 freq = 0.4594
+allele 2 : freq = 0.5563 freq = 0.5354 freq = 0.0000 freq = 0.5406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 236: rs236
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.023469 pvalue = 0.878244 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003277 pvalue = 0.954351 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.051518 pvalue = 0.820443 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1717 sd = 0.0407 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+allele 2 : freq = 0.8283 sd = 0.0407 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1625 freq = 0.1646 freq = 0.0000 freq = 0.1641
+allele 2 : freq = 0.8375 freq = 0.8354 freq = 0.0000 freq = 0.8359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 237: rs237
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.301221 pvalue = 0.583118 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.121183 pvalue = 0.727755 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.082691 pvalue = 0.773683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8562 freq = 0.0000 freq = 0.8594
+allele 2 : freq = 0.1313 freq = 0.1437 freq = 0.0000 freq = 0.1406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 238: rs238
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.021485 pvalue = 0.883465 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.421704 pvalue = 0.516088 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.055710 pvalue = 0.81341 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8767 sd = 0.0355 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.1233 sd = 0.0355 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.9083 freq = 0.0000 freq = 0.9031
+allele 2 : freq = 0.1125 freq = 0.0917 freq = 0.0000 freq = 0.0969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 239: rs239
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.820180 pvalue = 0.093086 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.856147 pvalue = 0.17307 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.939634 pvalue = 0.163708 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6650 sd = 0.0510 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+allele 2 : freq = 0.3350 sd = 0.0510 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.6208 freq = 0.0000 freq = 0.6375
+allele 2 : freq = 0.3125 freq = 0.3792 freq = 0.0000 freq = 0.3625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 240: rs240
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.078706 pvalue = 0.779059 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.009845 pvalue = 0.920961 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.241849 pvalue = 0.622874 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7817 sd = 0.0446 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.2183 sd = 0.0446 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7667 freq = 0.0000 freq = 0.7656
+allele 2 : freq = 0.2375 freq = 0.2333 freq = 0.0000 freq = 0.2344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 241: rs241
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.312392 pvalue = 0.251962 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.118512 pvalue = 0.730654 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.194286 pvalue = 0.659373 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4117 sd = 0.0532 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340
+allele 2 : freq = 0.5883 sd = 0.0532 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.4083 freq = 0.0000 freq = 0.4125
+allele 2 : freq = 0.5750 freq = 0.5917 freq = 0.0000 freq = 0.5875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 242: rs242
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.390521 pvalue = 0.532026 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.351842 pvalue = 0.553072 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.731444 pvalue = 0.392415 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2000 freq = 0.1771 freq = 0.0000 freq = 0.1828
+allele 2 : freq = 0.8000 freq = 0.8229 freq = 0.0000 freq = 0.8172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 243: rs243
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.027024 pvalue = 0.869424 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.059335 pvalue = 0.80755 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.269705 pvalue = 0.259822 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9300 sd = 0.0276 freq = 0.9308 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.9300 sd = 0.0180
+allele 2 : freq = 0.0700 sd = 0.0276 freq = 0.0692 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.0700 sd = 0.0180
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9375 freq = 0.9437 freq = 0.0000 freq = 0.9422
+allele 2 : freq = 0.0625 freq = 0.0563 freq = 0.0000 freq = 0.0578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 244: rs244
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001429 pvalue = 0.969845 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.013465 pvalue = 0.907623 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.009188 pvalue = 0.923637 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1533 sd = 0.0389 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+allele 2 : freq = 0.8467 sd = 0.0389 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 freq = 0.1458 freq = 0.0000 freq = 0.1469
+allele 2 : freq = 0.8500 freq = 0.8542 freq = 0.0000 freq = 0.8531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 245: rs245
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.884776 pvalue = 0.346897 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.195562 pvalue = 0.138409 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.887279 pvalue = 0.0892816 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3200 sd = 0.0504 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+allele 2 : freq = 0.6800 sd = 0.0504 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3187 freq = 0.3896 freq = 0.0000 freq = 0.3719
+allele 2 : freq = 0.6813 freq = 0.6104 freq = 0.0000 freq = 0.6281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 246: rs246
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.950525 pvalue = 0.0147129 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.495905 pvalue = 0.0190611 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.023913 pvalue = 0.0820453 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6883 sd = 0.0500 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+allele 2 : freq = 0.3117 sd = 0.0500 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.7646 freq = 0.0000 freq = 0.7391
+allele 2 : freq = 0.3375 freq = 0.2354 freq = 0.0000 freq = 0.2609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 247: rs247
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.134806 pvalue = 0.7135 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.087243 pvalue = 0.767711 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.085726 pvalue = 0.769683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.7688 freq = 0.0000 freq = 0.7656
+allele 2 : freq = 0.2437 freq = 0.2313 freq = 0.0000 freq = 0.2344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 248: rs248
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.860469 pvalue = 0.090781 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.251640 pvalue = 0.26324 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.111399 pvalue = 0.291778 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5950 sd = 0.0530 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.4050 sd = 0.0530 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.5188 freq = 0.0000 freq = 0.5328
+allele 2 : freq = 0.4250 freq = 0.4813 freq = 0.0000 freq = 0.4672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 249: rs249
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.243673 pvalue = 0.621566 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.357050 pvalue = 0.550149 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.337327 pvalue = 0.247506 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6183 sd = 0.0525 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+allele 2 : freq = 0.3817 sd = 0.0525 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.6083 freq = 0.0000 freq = 0.6156
+allele 2 : freq = 0.3625 freq = 0.3917 freq = 0.0000 freq = 0.3844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 250: rs250
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.687280 pvalue = 0.19396 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.254651 pvalue = 0.262666 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.810301 pvalue = 0.0282901 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5833 sd = 0.0533 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+allele 2 : freq = 0.4167 sd = 0.0533 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.5250 freq = 0.0000 freq = 0.5391
+allele 2 : freq = 0.4188 freq = 0.4750 freq = 0.0000 freq = 0.4609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 251: rs251
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.787329 pvalue = 0.374909 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.712420 pvalue = 0.398641 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.471810 pvalue = 0.22506 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6217 sd = 0.0524 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+allele 2 : freq = 0.3783 sd = 0.0524 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.5896 freq = 0.0000 freq = 0.6000
+allele 2 : freq = 0.3688 freq = 0.4104 freq = 0.0000 freq = 0.4000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 252: rs252
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 6.549328 pvalue = 0.0104924 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.019003 pvalue = 0.082294 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 11.013602 pvalue = 0.000904457 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.5729 freq = 0.0000 freq = 0.5516
+allele 2 : freq = 0.5125 freq = 0.4271 freq = 0.0000 freq = 0.4484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 253: rs253
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.894603 pvalue = 0.168684 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.528554 pvalue = 0.111803 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.132289 pvalue = 0.0767559 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 sd = 0.0539 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.4750 sd = 0.0539 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5188 freq = 0.5979 freq = 0.0000 freq = 0.5781
+allele 2 : freq = 0.4813 freq = 0.4021 freq = 0.0000 freq = 0.4219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 254: rs254
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.280431 pvalue = 0.0701105 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.950325 pvalue = 0.0468623 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.956687 pvalue = 0.328023 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3467 sd = 0.0514 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.6533 sd = 0.0514 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.4292 freq = 0.0000 freq = 0.4047
+allele 2 : freq = 0.6687 freq = 0.5708 freq = 0.0000 freq = 0.5953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 255: rs255
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.096153 pvalue = 0.756496 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.142948 pvalue = 0.28503 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.871587 pvalue = 0.350516 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9200 sd = 0.0293 freq = 0.9173 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192
+allele 2 : freq = 0.0800 sd = 0.0293 freq = 0.0827 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9187 freq = 0.8896 freq = 0.0000 freq = 0.8969
+allele 2 : freq = 0.0813 freq = 0.1104 freq = 0.0000 freq = 0.1031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 256: rs256
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.745679 pvalue = 0.0529442 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.785263 pvalue = 0.0951351 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2917 sd = 0.0491 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+allele 2 : freq = 0.7083 sd = 0.0491 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.3750 freq = 0.0000 freq = 0.3547
+allele 2 : freq = 0.7063 freq = 0.6250 freq = 0.0000 freq = 0.6453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 257: rs257
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.088410 pvalue = 0.766209 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.832992 pvalue = 0.361409 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.300644 pvalue = 0.583479 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5333 sd = 0.0539 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+allele 2 : freq = 0.4667 sd = 0.0539 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.4792 freq = 0.0000 freq = 0.4906
+allele 2 : freq = 0.4750 freq = 0.5208 freq = 0.0000 freq = 0.5094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 258: rs258
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.072785 pvalue = 0.787325 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.021811 pvalue = 0.882591 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.288134 pvalue = 0.591419 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7750 freq = 0.0000 freq = 0.7766
+allele 2 : freq = 0.2188 freq = 0.2250 freq = 0.0000 freq = 0.2234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 259: rs259
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.343900 pvalue = 0.557587 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.005831 pvalue = 0.93913 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.123068 pvalue = 0.289259 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1017 sd = 0.0326 freq = 0.0808 sd = 0.0207 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192
+allele 2 : freq = 0.8983 sd = 0.0326 freq = 0.9192 sd = 0.0207 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1000 freq = 0.1021 freq = 0.0000 freq = 0.1016
+allele 2 : freq = 0.9000 freq = 0.8979 freq = 0.0000 freq = 0.8984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 260: rs260
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.896549 pvalue = 0.0483854 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.504035 pvalue = 0.113555 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.927697 pvalue = 0.335462 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6333 sd = 0.0521 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+allele 2 : freq = 0.3667 sd = 0.0521 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.5583 freq = 0.0000 freq = 0.5781
+allele 2 : freq = 0.3625 freq = 0.4417 freq = 0.0000 freq = 0.4219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 261: rs261
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.018346 pvalue = 0.0823274 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.422738 pvalue = 0.0354631 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.560012 pvalue = 0.454255 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1300 sd = 0.0363 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+allele 2 : freq = 0.8700 sd = 0.0363 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1313 freq = 0.2125 freq = 0.0000 freq = 0.1922
+allele 2 : freq = 0.8688 freq = 0.7875 freq = 0.0000 freq = 0.8078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 262: rs262
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001810 pvalue = 0.966061 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.071606 pvalue = 0.789013 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.017590 pvalue = 0.894488 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6783 sd = 0.0505 freq = 0.6885 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.3217 sd = 0.0505 freq = 0.3115 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.7000 freq = 0.0000 freq = 0.6969
+allele 2 : freq = 0.3125 freq = 0.3000 freq = 0.0000 freq = 0.3031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 263: rs263
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.514488 pvalue = 0.218456 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.698620 pvalue = 0.100435 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.208936 pvalue = 0.271543 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3650 sd = 0.0520 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+allele 2 : freq = 0.6350 sd = 0.0520 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3688 freq = 0.4500 freq = 0.0000 freq = 0.4297
+allele 2 : freq = 0.6312 freq = 0.5500 freq = 0.0000 freq = 0.5703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 264: rs264
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.158560 pvalue = 0.0755298 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.772167 pvalue = 0.0521121 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.199730 pvalue = 0.138035 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3067 sd = 0.0498 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339
+allele 2 : freq = 0.6933 sd = 0.0498 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.3875 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.7063 freq = 0.6125 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 265: rs265
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.011249 pvalue = 0.915533 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.336518 pvalue = 0.561846 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.291352 pvalue = 0.255799 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4917 sd = 0.0540 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.5083 sd = 0.0540 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.5292 freq = 0.0000 freq = 0.5219
+allele 2 : freq = 0.5000 freq = 0.4708 freq = 0.0000 freq = 0.4781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 266: rs266
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.835783 pvalue = 0.360606 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.523202 pvalue = 0.469479 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.273339 pvalue = 0.601101 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3400 sd = 0.0512 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.6600 sd = 0.0512 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3042 freq = 0.0000 freq = 0.3125
+allele 2 : freq = 0.6625 freq = 0.6958 freq = 0.0000 freq = 0.6875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 267: rs267
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.969695 pvalue = 0.16048 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.552688 pvalue = 0.212739 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.846073 pvalue = 0.174241 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5533 sd = 0.0537 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+allele 2 : freq = 0.4467 sd = 0.0537 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.4625 freq = 0.0000 freq = 0.4781
+allele 2 : freq = 0.4750 freq = 0.5375 freq = 0.0000 freq = 0.5219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 268: rs268
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.097941 pvalue = 0.754315 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.114176 pvalue = 0.735439 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.363497 pvalue = 0.546571 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8883 sd = 0.0340 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217
+allele 2 : freq = 0.1117 sd = 0.0340 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8979 freq = 0.0000 freq = 0.8953
+allele 2 : freq = 0.1125 freq = 0.1021 freq = 0.0000 freq = 0.1047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 269: rs269
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.333575 pvalue = 0.24817 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.255496 pvalue = 0.133141 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.371689 pvalue = 0.542085 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6483 sd = 0.0516 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+allele 2 : freq = 0.3517 sd = 0.0516 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.5958 freq = 0.0000 freq = 0.6141
+allele 2 : freq = 0.3312 freq = 0.4042 freq = 0.0000 freq = 0.3859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 270: rs270
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.025071 pvalue = 0.87419 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.029299 pvalue = 0.86409 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.124955 pvalue = 0.723721 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3717 sd = 0.0522 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+allele 2 : freq = 0.6283 sd = 0.0522 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.3542 freq = 0.0000 freq = 0.3563
+allele 2 : freq = 0.6375 freq = 0.6458 freq = 0.0000 freq = 0.6438
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 271: rs271
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.019633 pvalue = 0.888568 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.186280 pvalue = 0.666031 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003254 pvalue = 0.95451 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339
+allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.3229 freq = 0.0000 freq = 0.3281
+allele 2 : freq = 0.6562 freq = 0.6771 freq = 0.0000 freq = 0.6719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 272: rs272
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 7.243173 pvalue = 0.00711711 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 7.253290 pvalue = 0.00707712 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.873119 pvalue = 0.0490653 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1400 sd = 0.0375 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+allele 2 : freq = 0.8600 sd = 0.0375 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1125 freq = 0.2208 freq = 0.0000 freq = 0.1938
+allele 2 : freq = 0.8875 freq = 0.7792 freq = 0.0000 freq = 0.8063
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 273: rs273
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.945759 pvalue = 0.0469896 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.482967 pvalue = 0.115085 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.987878 pvalue = 0.0255255 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4267 sd = 0.0534 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+allele 2 : freq = 0.5733 sd = 0.0534 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4313 freq = 0.5104 freq = 0.0000 freq = 0.4906
+allele 2 : freq = 0.5687 freq = 0.4896 freq = 0.0000 freq = 0.5094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 274: rs274
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.725854 pvalue = 0.188941 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.907506 pvalue = 0.167241 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.301615 pvalue = 0.253918 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1267 sd = 0.0359 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212
+allele 2 : freq = 0.8733 sd = 0.0359 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1313 freq = 0.0896 freq = 0.0000 freq = 0.1000
+allele 2 : freq = 0.8688 freq = 0.9104 freq = 0.0000 freq = 0.9000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 275: rs275
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.447793 pvalue = 0.228882 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.727552 pvalue = 0.188724 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.081997 pvalue = 0.0136566 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6867 sd = 0.0501 freq = 0.7538 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+allele 2 : freq = 0.3133 sd = 0.0501 freq = 0.2462 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.7521 freq = 0.0000 freq = 0.7375
+allele 2 : freq = 0.3063 freq = 0.2479 freq = 0.0000 freq = 0.2625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 276: rs276
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.115387 pvalue = 0.734092 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.265427 pvalue = 0.606416 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.121183 pvalue = 0.145274 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.8577 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.1423 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8562 freq = 0.0000 freq = 0.8516
+allele 2 : freq = 0.1625 freq = 0.1437 freq = 0.0000 freq = 0.1484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 277: rs277
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.012862 pvalue = 0.909706 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.121183 pvalue = 0.727755 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.082691 pvalue = 0.773683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 sd = 0.0386 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+allele 2 : freq = 0.8500 sd = 0.0386 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 freq = 0.1375 freq = 0.0000 freq = 0.1406
+allele 2 : freq = 0.8500 freq = 0.8625 freq = 0.0000 freq = 0.8594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 278: rs278
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.030846 pvalue = 0.30996 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.780713 pvalue = 0.182062 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.800823 pvalue = 0.179613 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1717 sd = 0.0407 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+allele 2 : freq = 0.8283 sd = 0.0407 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.1271 freq = 0.0000 freq = 0.1391
+allele 2 : freq = 0.8250 freq = 0.8729 freq = 0.0000 freq = 0.8609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 279: rs279
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.277129 pvalue = 0.258434 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.572782 pvalue = 0.449156 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006948 pvalue = 0.933568 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.4000 freq = 0.0000 freq = 0.3906
+allele 2 : freq = 0.6375 freq = 0.6000 freq = 0.0000 freq = 0.6094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 280: rs280
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.532938 pvalue = 0.0601611 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.243227 pvalue = 0.134201 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.124955 pvalue = 0.723721 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5650 sd = 0.0535 freq = 0.6346 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.4350 sd = 0.0535 freq = 0.3654 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.6167 freq = 0.0000 freq = 0.5984
+allele 2 : freq = 0.4562 freq = 0.3833 freq = 0.0000 freq = 0.4016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 281: rs281
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.031370 pvalue = 0.859418 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003924 pvalue = 0.950052 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.524811 pvalue = 0.468797 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8850 sd = 0.0345 freq = 0.8769 sd = 0.0250 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+allele 2 : freq = 0.1150 sd = 0.0345 freq = 0.1231 sd = 0.0250 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8812 freq = 0.8792 freq = 0.0000 freq = 0.8797
+allele 2 : freq = 0.1187 freq = 0.1208 freq = 0.0000 freq = 0.1203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 282: rs282
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001875 pvalue = 0.965465 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.061532 pvalue = 0.80409 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.812880 pvalue = 0.36727 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7917 freq = 0.0000 freq = 0.7891
+allele 2 : freq = 0.2188 freq = 0.2083 freq = 0.0000 freq = 0.2109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 283: rs283
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.124753 pvalue = 0.288897 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.648085 pvalue = 0.19922 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.044984 pvalue = 0.832034 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6167 sd = 0.0525 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.3833 sd = 0.0525 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.6500 freq = 0.0000 freq = 0.6344
+allele 2 : freq = 0.4125 freq = 0.3500 freq = 0.0000 freq = 0.3656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 284: rs284
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.012972 pvalue = 0.909321 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.277424 pvalue = 0.598394 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.353579 pvalue = 0.552094 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3167 sd = 0.0502 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.6833 sd = 0.0502 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3187 freq = 0.2938 freq = 0.0000 freq = 0.3000
+allele 2 : freq = 0.6813 freq = 0.7063 freq = 0.0000 freq = 0.7000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 285: rs285
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.024962 pvalue = 0.311345 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.566613 pvalue = 0.2107 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.052065 pvalue = 0.819509 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6467 sd = 0.0516 freq = 0.6385 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339
+allele 2 : freq = 0.3533 sd = 0.0516 freq = 0.3615 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.6146 freq = 0.0000 freq = 0.6297
+allele 2 : freq = 0.3250 freq = 0.3854 freq = 0.0000 freq = 0.3703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 286: rs286
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.054819 pvalue = 0.81488 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.031157 pvalue = 0.85989 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.122461 pvalue = 0.726381 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8617 sd = 0.0373 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+allele 2 : freq = 0.1383 sd = 0.0373 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8625 freq = 0.8562 freq = 0.0000 freq = 0.8578
+allele 2 : freq = 0.1375 freq = 0.1437 freq = 0.0000 freq = 0.1422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 287: rs287
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.075574 pvalue = 0.149674 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.019712 pvalue = 0.155269 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.220509 pvalue = 0.638652 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.3083 freq = 0.0000 freq = 0.3250
+allele 2 : freq = 0.6250 freq = 0.6917 freq = 0.0000 freq = 0.6750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 288: rs288
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.907315 pvalue = 0.340828 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.484731 pvalue = 0.486287 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.147006 pvalue = 0.701413 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8083 sd = 0.0425 freq = 0.8500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1917 sd = 0.0425 freq = 0.1500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.8438 freq = 0.0000 freq = 0.8375
+allele 2 : freq = 0.1812 freq = 0.1562 freq = 0.0000 freq = 0.1625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 289: rs289
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.638764 pvalue = 0.424159 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.280751 pvalue = 0.59621 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.711580 pvalue = 0.39892 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7646 freq = 0.0000 freq = 0.7703
+allele 2 : freq = 0.2125 freq = 0.2354 freq = 0.0000 freq = 0.2297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 290: rs290
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.073448 pvalue = 0.149882 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.049710 pvalue = 0.305574 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.002857 pvalue = 0.957371 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7983 sd = 0.0433 freq = 0.8212 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.2017 sd = 0.0433 freq = 0.1788 sd = 0.0291 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.8083 freq = 0.0000 freq = 0.7984
+allele 2 : freq = 0.2313 freq = 0.1917 freq = 0.0000 freq = 0.2016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 291: rs291
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.006196 pvalue = 0.937259 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.093133 pvalue = 0.760231 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.326510 pvalue = 0.567721 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7800 sd = 0.0447 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2200 sd = 0.0447 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7688 freq = 0.0000 freq = 0.7719
+allele 2 : freq = 0.2188 freq = 0.2313 freq = 0.0000 freq = 0.2281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 292: rs292
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000025 pvalue = 0.996006 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.146496 pvalue = 0.701906 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.024991 pvalue = 0.874389 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2271 freq = 0.0000 freq = 0.2313
+allele 2 : freq = 0.7562 freq = 0.7729 freq = 0.0000 freq = 0.7688
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 293: rs293
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.295609 pvalue = 0.586648 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.891151 pvalue = 0.345166 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.218913 pvalue = 0.63987 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6317 sd = 0.0521 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+allele 2 : freq = 0.3683 sd = 0.0521 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6438 freq = 0.5979 freq = 0.0000 freq = 0.6094
+allele 2 : freq = 0.3563 freq = 0.4021 freq = 0.0000 freq = 0.3906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 294: rs294
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001921 pvalue = 0.965044 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.004217 pvalue = 0.948223 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.203040 pvalue = 0.652278 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8900 sd = 0.0338 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.1100 sd = 0.0338 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8896 freq = 0.0000 freq = 0.8891
+allele 2 : freq = 0.1125 freq = 0.1104 freq = 0.0000 freq = 0.1109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 295: rs295
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.230138 pvalue = 0.631421 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.307865 pvalue = 0.578994 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.216590 pvalue = 0.641651 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.3896 freq = 0.0000 freq = 0.3828
+allele 2 : freq = 0.6375 freq = 0.6104 freq = 0.0000 freq = 0.6172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 296: rs296
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.949726 pvalue = 0.162616 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.230812 pvalue = 0.135283 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.016575 pvalue = 0.897561 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8865 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1135 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8500 freq = 0.8979 freq = 0.0000 freq = 0.8859
+allele 2 : freq = 0.1500 freq = 0.1021 freq = 0.0000 freq = 0.1141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 297: rs297
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007237 pvalue = 0.932203 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.005240 pvalue = 0.942291 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.252313 pvalue = 0.615451 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0833 sd = 0.0299 freq = 0.0827 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202
+allele 2 : freq = 0.9167 sd = 0.0299 freq = 0.9173 sd = 0.0209 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0938 freq = 0.0958 freq = 0.0000 freq = 0.0953
+allele 2 : freq = 0.9062 freq = 0.9042 freq = 0.0000 freq = 0.9047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 298: rs298
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.568362 pvalue = 0.450911 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.360879 pvalue = 0.548018 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.564670 pvalue = 0.452385 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.3750 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.6250 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3667 freq = 0.0000 freq = 0.3594
+allele 2 : freq = 0.6625 freq = 0.6333 freq = 0.0000 freq = 0.6406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 299: rs299
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.193225 pvalue = 0.27468 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.123002 pvalue = 0.289273 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.852174 pvalue = 0.355938 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8033 sd = 0.0429 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.1967 sd = 0.0429 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7937 freq = 0.7479 freq = 0.0000 freq = 0.7594
+allele 2 : freq = 0.2062 freq = 0.2521 freq = 0.0000 freq = 0.2406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 300: rs300
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.917892 pvalue = 0.166089 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.557623 pvalue = 0.45522 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.018790 pvalue = 0.89097 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4667 sd = 0.0539 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+allele 2 : freq = 0.5333 sd = 0.0539 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.4938 freq = 0.0000 freq = 0.4844
+allele 2 : freq = 0.5437 freq = 0.5062 freq = 0.0000 freq = 0.5156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 301: rs301
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.298041 pvalue = 0.129537 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.198287 pvalue = 0.0404648 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.473736 pvalue = 0.224757 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1150 sd = 0.0345 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207
+allele 2 : freq = 0.8850 sd = 0.0345 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1250 freq = 0.0646 freq = 0.0000 freq = 0.0797
+allele 2 : freq = 0.8750 freq = 0.9354 freq = 0.0000 freq = 0.9203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 302: rs302
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.289451 pvalue = 0.590573 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.837580 pvalue = 0.36009 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.067185 pvalue = 0.795481 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.3750 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.6687 freq = 0.6250 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 303: rs303
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.761233 pvalue = 0.184471 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.670604 pvalue = 0.0553801 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.396394 pvalue = 0.237328 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.4375 freq = 0.0000 freq = 0.4141
+allele 2 : freq = 0.6562 freq = 0.5625 freq = 0.0000 freq = 0.5859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 304: rs304
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.765913 pvalue = 0.183889 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.306426 pvalue = 0.0690094 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.059142 pvalue = 0.807857 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 sd = 0.0495 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3000 sd = 0.0495 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.6000 freq = 0.0000 freq = 0.6219
+allele 2 : freq = 0.3125 freq = 0.4000 freq = 0.0000 freq = 0.3781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 305: rs305
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.272614 pvalue = 0.0387313 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.959766 pvalue = 0.161538 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.982185 pvalue = 0.0841856 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6517 sd = 0.0515 freq = 0.7154 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+allele 2 : freq = 0.3483 sd = 0.0515 freq = 0.2846 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6438 freq = 0.7063 freq = 0.0000 freq = 0.6906
+allele 2 : freq = 0.3563 freq = 0.2938 freq = 0.0000 freq = 0.3094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 306: rs306
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.879955 pvalue = 0.0488659 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.252166 pvalue = 0.133428 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.148747 pvalue = 0.699736 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3600 sd = 0.0518 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.6400 sd = 0.0518 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3563 freq = 0.4313 freq = 0.0000 freq = 0.4125
+allele 2 : freq = 0.6438 freq = 0.5687 freq = 0.0000 freq = 0.5875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 307: rs307
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.445833 pvalue = 0.504321 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.921432 pvalue = 0.337099 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.924070 pvalue = 0.0872675 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.5333 freq = 0.0000 freq = 0.5453
+allele 2 : freq = 0.4188 freq = 0.4667 freq = 0.0000 freq = 0.4547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 308: rs308
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.402738 pvalue = 0.525679 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.228901 pvalue = 0.63234 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7267 sd = 0.0481 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+allele 2 : freq = 0.2733 sd = 0.0481 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.7458 freq = 0.0000 freq = 0.7406
+allele 2 : freq = 0.2750 freq = 0.2542 freq = 0.0000 freq = 0.2594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 309: rs309
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.075513 pvalue = 0.783472 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.379551 pvalue = 0.537844 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5033 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.4967 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.4979 freq = 0.0000 freq = 0.4953
+allele 2 : freq = 0.5125 freq = 0.5021 freq = 0.0000 freq = 0.5047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 310: rs310
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.014533 pvalue = 0.904045 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.209720 pvalue = 0.646987 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.060462 pvalue = 0.805767 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1683 sd = 0.0404 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+allele 2 : freq = 0.8317 sd = 0.0404 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1562 freq = 0.1729 freq = 0.0000 freq = 0.1688
+allele 2 : freq = 0.8438 freq = 0.8271 freq = 0.0000 freq = 0.8313
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 311: rs311
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.729570 pvalue = 0.393023 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.243161 pvalue = 0.264863 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.424801 pvalue = 0.232615 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7150 sd = 0.0488 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.2850 sd = 0.0488 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.6604 freq = 0.0000 freq = 0.6734
+allele 2 : freq = 0.2875 freq = 0.3396 freq = 0.0000 freq = 0.3266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 312: rs312
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.761815 pvalue = 0.382761 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.048219 pvalue = 0.826192 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.5875 freq = 0.0000 freq = 0.5875
+allele 2 : freq = 0.4125 freq = 0.4125 freq = 0.0000 freq = 0.4125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 313: rs313
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.104266 pvalue = 0.74677 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.067478 pvalue = 0.795045 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.222856 pvalue = 0.636872 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6462 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3538 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.6438 freq = 0.0000 freq = 0.6406
+allele 2 : freq = 0.3688 freq = 0.3563 freq = 0.0000 freq = 0.3594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 314: rs314
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.874447 pvalue = 0.349727 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.640501 pvalue = 0.42353 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.607471 pvalue = 0.435742 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5500 freq = 0.5896 freq = 0.0000 freq = 0.5797
+allele 2 : freq = 0.4500 freq = 0.4104 freq = 0.0000 freq = 0.4203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 315: rs315
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.138100 pvalue = 0.710177 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.119219 pvalue = 0.729883 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.593048 pvalue = 0.441243 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6462 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339
+allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3538 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.6417 freq = 0.0000 freq = 0.6375
+allele 2 : freq = 0.3750 freq = 0.3583 freq = 0.0000 freq = 0.3625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 316: rs316
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.413892 pvalue = 0.520001 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.407309 pvalue = 0.523339 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.036751 pvalue = 0.847972 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8650 sd = 0.0369 freq = 0.8500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1350 sd = 0.0369 freq = 0.1500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8458 freq = 0.0000 freq = 0.8516
+allele 2 : freq = 0.1313 freq = 0.1542 freq = 0.0000 freq = 0.1484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 317: rs317
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.022566 pvalue = 0.311911 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.510907 pvalue = 0.474746 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.114214 pvalue = 0.0425243 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3717 sd = 0.0522 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+allele 2 : freq = 0.6283 sd = 0.0522 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3688 freq = 0.4042 freq = 0.0000 freq = 0.3953
+allele 2 : freq = 0.6312 freq = 0.5958 freq = 0.0000 freq = 0.6047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 318: rs318
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.645616 pvalue = 0.421684 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.119219 pvalue = 0.729883 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.468582 pvalue = 0.49364 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8733 sd = 0.0359 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212
+allele 2 : freq = 0.1267 sd = 0.0359 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8750 freq = 0.8854 freq = 0.0000 freq = 0.8828
+allele 2 : freq = 0.1250 freq = 0.1146 freq = 0.0000 freq = 0.1172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 319: rs319
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.298495 pvalue = 0.584828 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.404090 pvalue = 0.524984 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.028235 pvalue = 0.866556 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3783 sd = 0.0524 freq = 0.3712 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6217 sd = 0.0524 freq = 0.6288 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.4062 freq = 0.0000 freq = 0.3984
+allele 2 : freq = 0.6250 freq = 0.5938 freq = 0.0000 freq = 0.6016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 320: rs320
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.109032 pvalue = 0.741249 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.159762 pvalue = 0.689375 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.310952 pvalue = 0.577097 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3317 sd = 0.0509 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+allele 2 : freq = 0.6683 sd = 0.0509 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.3125 freq = 0.0000 freq = 0.3172
+allele 2 : freq = 0.6687 freq = 0.6875 freq = 0.0000 freq = 0.6828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 321: rs321
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001038 pvalue = 0.974301 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.034063 pvalue = 0.853574 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.253118 pvalue = 0.614888 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2700 sd = 0.0480 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+allele 2 : freq = 0.7300 sd = 0.0480 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2750 freq = 0.2667 freq = 0.0000 freq = 0.2687
+allele 2 : freq = 0.7250 freq = 0.7333 freq = 0.0000 freq = 0.7312
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 322: rs322
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.095715 pvalue = 0.295208 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.277347 pvalue = 0.258393 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.005578 pvalue = 0.940463 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6717 sd = 0.0507 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+allele 2 : freq = 0.3283 sd = 0.0507 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.7146 freq = 0.0000 freq = 0.7016
+allele 2 : freq = 0.3375 freq = 0.2854 freq = 0.0000 freq = 0.2984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 323: rs323
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.142551 pvalue = 0.705758 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.109916 pvalue = 0.740239 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.816783 pvalue = 0.366122 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4883 sd = 0.0540 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.5117 sd = 0.0540 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.4896 freq = 0.0000 freq = 0.4938
+allele 2 : freq = 0.4938 freq = 0.5104 freq = 0.0000 freq = 0.5062
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 324: rs324
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.355794 pvalue = 0.550851 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.017608 pvalue = 0.894435 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.005340 pvalue = 0.941746 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7233 sd = 0.0483 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.2767 sd = 0.0483 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7063 freq = 0.7000 freq = 0.0000 freq = 0.7016
+allele 2 : freq = 0.2938 freq = 0.3000 freq = 0.0000 freq = 0.2984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 325: rs325
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.038433 pvalue = 0.844577 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007097 pvalue = 0.932863 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.922247 pvalue = 0.336886 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4167 sd = 0.0533 freq = 0.4019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+allele 2 : freq = 0.5833 sd = 0.0533 freq = 0.5981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4000 freq = 0.4042 freq = 0.0000 freq = 0.4031
+allele 2 : freq = 0.6000 freq = 0.5958 freq = 0.0000 freq = 0.5969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 326: rs326
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.451614 pvalue = 0.228269 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.912635 pvalue = 0.339416 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.846073 pvalue = 0.174241 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4683 sd = 0.0539 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+allele 2 : freq = 0.5317 sd = 0.0539 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.5292 freq = 0.0000 freq = 0.5172
+allele 2 : freq = 0.5188 freq = 0.4708 freq = 0.0000 freq = 0.4828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 327: rs327
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.287027 pvalue = 0.13046 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.249745 pvalue = 0.263601 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.834924 pvalue = 0.360853 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8083 sd = 0.0425 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+allele 2 : freq = 0.1917 sd = 0.0425 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.8458 freq = 0.0000 freq = 0.8359
+allele 2 : freq = 0.1938 freq = 0.1542 freq = 0.0000 freq = 0.1641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 328: rs328
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.532790 pvalue = 0.215694 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.741638 pvalue = 0.389137 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006248 pvalue = 0.936999 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3033 sd = 0.0497 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.6967 sd = 0.0497 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.2625 freq = 0.0000 freq = 0.2719
+allele 2 : freq = 0.7000 freq = 0.7375 freq = 0.0000 freq = 0.7281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 329: rs329
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.192577 pvalue = 0.27481 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.292501 pvalue = 0.588622 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.965973 pvalue = 0.160876 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3950 sd = 0.0528 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+allele 2 : freq = 0.6050 sd = 0.0528 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4000 freq = 0.4271 freq = 0.0000 freq = 0.4203
+allele 2 : freq = 0.6000 freq = 0.5729 freq = 0.0000 freq = 0.5797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 330: rs330
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007071 pvalue = 0.932985 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.027756 pvalue = 0.867683 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0617 sd = 0.0260 freq = 0.0596 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174
+allele 2 : freq = 0.9383 sd = 0.0260 freq = 0.9404 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0625 freq = 0.0625 freq = 0.0000 freq = 0.0625
+allele 2 : freq = 0.9375 freq = 0.9375 freq = 0.0000 freq = 0.9375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 331: rs331
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.034481 pvalue = 0.852686 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002353 pvalue = 0.961312 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.004110 pvalue = 0.948881 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2333 freq = 0.0000 freq = 0.2328
+allele 2 : freq = 0.7688 freq = 0.7667 freq = 0.0000 freq = 0.7672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 332: rs332
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.789013 pvalue = 0.374399 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.994183 pvalue = 0.157904 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.499820 pvalue = 0.479579 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6083 sd = 0.0527 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.3917 sd = 0.0527 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.6687 freq = 0.0000 freq = 0.6516
+allele 2 : freq = 0.4000 freq = 0.3312 freq = 0.0000 freq = 0.3484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 333: rs333
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.682876 pvalue = 0.408598 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.139071 pvalue = 0.709206 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.050636 pvalue = 0.0441547 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5500 sd = 0.0537 freq = 0.4885 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.4500 sd = 0.0537 freq = 0.5115 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.5188 freq = 0.0000 freq = 0.5234
+allele 2 : freq = 0.4625 freq = 0.4813 freq = 0.0000 freq = 0.4766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 334: rs334
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.120003 pvalue = 0.145386 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.066607 pvalue = 0.301713 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.326443 pvalue = 0.249439 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7150 sd = 0.0488 freq = 0.6385 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340
+allele 2 : freq = 0.2850 sd = 0.0488 freq = 0.3615 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 freq = 0.6500 freq = 0.0000 freq = 0.6625
+allele 2 : freq = 0.3000 freq = 0.3500 freq = 0.0000 freq = 0.3375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 335: rs335
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.466707 pvalue = 0.494506 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386398 pvalue = 0.534199 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000349 pvalue = 0.985103 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1812 freq = 0.1583 freq = 0.0000 freq = 0.1641
+allele 2 : freq = 0.8187 freq = 0.8417 freq = 0.0000 freq = 0.8359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 336: rs336
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.731663 pvalue = 0.392345 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.189094 pvalue = 0.275512 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.292103 pvalue = 0.588876 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0717 sd = 0.0279 freq = 0.0442 sd = 0.0156 freq = 0.0000 sd = 0.0000 freq = 0.0550 sd = 0.0161
+allele 2 : freq = 0.9283 sd = 0.0279 freq = 0.9558 sd = 0.0156 freq = 0.0000 sd = 0.0000 freq = 0.9450 sd = 0.0161
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0688 freq = 0.0437 freq = 0.0000 freq = 0.0500
+allele 2 : freq = 0.9313 freq = 0.9563 freq = 0.0000 freq = 0.9500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 337: rs337
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.105994 pvalue = 0.744752 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.006873 pvalue = 0.933927 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.285342 pvalue = 0.593221 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5200 sd = 0.0540 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+allele 2 : freq = 0.4800 sd = 0.0540 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4938 freq = 0.4896 freq = 0.0000 freq = 0.4906
+allele 2 : freq = 0.5062 freq = 0.5104 freq = 0.0000 freq = 0.5094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 338: rs338
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.077293 pvalue = 0.781 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.637792 pvalue = 0.424512 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8733 sd = 0.0359 freq = 0.8942 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212
+allele 2 : freq = 0.1267 sd = 0.0359 freq = 0.1058 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8812 freq = 0.0000 freq = 0.8828
+allele 2 : freq = 0.1125 freq = 0.1187 freq = 0.0000 freq = 0.1172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 339: rs339
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001754 pvalue = 0.966598 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.069356 pvalue = 0.792277 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.017037 pvalue = 0.896149 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3217 sd = 0.0505 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.6783 sd = 0.0505 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3500 freq = 0.0000 freq = 0.3469
+allele 2 : freq = 0.6625 freq = 0.6500 freq = 0.0000 freq = 0.6531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 340: rs340
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.015218 pvalue = 0.313656 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.255923 pvalue = 0.133104 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.183040 pvalue = 0.668774 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.1646 freq = 0.0000 freq = 0.1797
+allele 2 : freq = 0.7750 freq = 0.8354 freq = 0.0000 freq = 0.8203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 341: rs341
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.089737 pvalue = 0.764512 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.192277 pvalue = 0.661029 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8683 sd = 0.0365 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+allele 2 : freq = 0.1317 sd = 0.0365 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8833 freq = 0.0000 freq = 0.8797
+allele 2 : freq = 0.1313 freq = 0.1167 freq = 0.0000 freq = 0.1203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 342: rs342
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.534020 pvalue = 0.464922 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.303517 pvalue = 0.581686 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.044909 pvalue = 0.306683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.3896 freq = 0.0000 freq = 0.3828
+allele 2 : freq = 0.6375 freq = 0.6104 freq = 0.0000 freq = 0.6172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 343: rs343
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 6.751576 pvalue = 0.00936649 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 6.141648 pvalue = 0.0132034 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.732041 pvalue = 0.0983535 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2033 sd = 0.0435 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+allele 2 : freq = 0.7967 sd = 0.0435 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.3000 freq = 0.0000 freq = 0.2719
+allele 2 : freq = 0.8125 freq = 0.7000 freq = 0.0000 freq = 0.7281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 344: rs344
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.107393 pvalue = 0.743132 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.770104 pvalue = 0.380185 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.320491 pvalue = 0.571313 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.5923 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.4077 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.6062 freq = 0.0000 freq = 0.5953
+allele 2 : freq = 0.4375 freq = 0.3937 freq = 0.0000 freq = 0.4047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 345: rs345
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.010749 pvalue = 0.917424 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.917337 pvalue = 0.338175 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.681573 pvalue = 0.409046 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4517 sd = 0.0538 freq = 0.4731 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5483 sd = 0.0538 freq = 0.5269 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4625 freq = 0.5104 freq = 0.0000 freq = 0.4984
+allele 2 : freq = 0.5375 freq = 0.4896 freq = 0.0000 freq = 0.5016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 346: rs346
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.822205 pvalue = 0.364536 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.556730 pvalue = 0.455581 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.945699 pvalue = 0.330817 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5383 sd = 0.0538 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.4617 sd = 0.0538 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.4875 freq = 0.0000 freq = 0.4969
+allele 2 : freq = 0.4750 freq = 0.5125 freq = 0.0000 freq = 0.5031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 347: rs347
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.418562 pvalue = 0.517656 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.654364 pvalue = 0.418557 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.810605 pvalue = 0.367941 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6333 sd = 0.0521 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+allele 2 : freq = 0.3667 sd = 0.0521 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.5979 freq = 0.0000 freq = 0.6078
+allele 2 : freq = 0.3625 freq = 0.4021 freq = 0.0000 freq = 0.3922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 348: rs348
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.276512 pvalue = 0.598997 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.045102 pvalue = 0.831817 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.381326 pvalue = 0.536895 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.4354 freq = 0.0000 freq = 0.4328
+allele 2 : freq = 0.5750 freq = 0.5646 freq = 0.0000 freq = 0.5672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 349: rs349
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.064575 pvalue = 0.799405 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.194671 pvalue = 0.659057 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001328 pvalue = 0.970926 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8267 sd = 0.0409 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1733 sd = 0.0409 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.8417 freq = 0.0000 freq = 0.8375
+allele 2 : freq = 0.1750 freq = 0.1583 freq = 0.0000 freq = 0.1625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 350: rs350
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.682755 pvalue = 0.40864 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.568885 pvalue = 0.450702 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.800823 pvalue = 0.179613 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8950 sd = 0.0331 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1050 sd = 0.0331 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8750 freq = 0.8479 freq = 0.0000 freq = 0.8547
+allele 2 : freq = 0.1250 freq = 0.1521 freq = 0.0000 freq = 0.1453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 351: rs351
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.271386 pvalue = 0.602403 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.397658 pvalue = 0.528301 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.749114 pvalue = 0.386757 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2633 sd = 0.0476 freq = 0.2308 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+allele 2 : freq = 0.7367 sd = 0.0476 freq = 0.7692 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2562 freq = 0.2292 freq = 0.0000 freq = 0.2359
+allele 2 : freq = 0.7438 freq = 0.7708 freq = 0.0000 freq = 0.7641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 352: rs352
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.165648 pvalue = 0.684009 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.074292 pvalue = 0.785188 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.164249 pvalue = 0.685275 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6950 sd = 0.0497 freq = 0.7038 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.3050 sd = 0.0497 freq = 0.2962 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.7000 freq = 0.0000 freq = 0.6969
+allele 2 : freq = 0.3125 freq = 0.3000 freq = 0.0000 freq = 0.3031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 353: rs353
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.040730 pvalue = 0.84006 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.047482 pvalue = 0.827504 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.029860 pvalue = 0.862809 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6617 sd = 0.0511 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+allele 2 : freq = 0.3383 sd = 0.0511 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.6521 freq = 0.0000 freq = 0.6547
+allele 2 : freq = 0.3375 freq = 0.3479 freq = 0.0000 freq = 0.3453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 354: rs354
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.311645 pvalue = 0.252097 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.962704 pvalue = 0.326507 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.808060 pvalue = 0.368694 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.6854 freq = 0.0000 freq = 0.6969
+allele 2 : freq = 0.2687 freq = 0.3146 freq = 0.0000 freq = 0.3031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 355: rs355
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.516246 pvalue = 0.472448 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.063873 pvalue = 0.800477 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.604102 pvalue = 0.205323 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.6019 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.3981 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.6500 freq = 0.0000 freq = 0.6469
+allele 2 : freq = 0.3625 freq = 0.3500 freq = 0.0000 freq = 0.3531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 356: rs356
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.569419 pvalue = 0.45049 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.521863 pvalue = 0.217338 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000848 pvalue = 0.976772 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 freq = 0.7083 freq = 0.0000 freq = 0.6937
+allele 2 : freq = 0.3500 freq = 0.2917 freq = 0.0000 freq = 0.3063
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 357: rs357
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001435 pvalue = 0.969781 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007956 pvalue = 0.928925 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.055593 pvalue = 0.813601 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6783 sd = 0.0505 freq = 0.6942 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.3217 sd = 0.0505 freq = 0.3058 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.6771 freq = 0.0000 freq = 0.6781
+allele 2 : freq = 0.3187 freq = 0.3229 freq = 0.0000 freq = 0.3219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 358: rs358
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.295178 pvalue = 0.255096 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.118104 pvalue = 0.290327 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.306030 pvalue = 0.580127 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.6750 freq = 0.0000 freq = 0.6625
+allele 2 : freq = 0.3750 freq = 0.3250 freq = 0.0000 freq = 0.3375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 359: rs359
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.021057 pvalue = 0.0821899 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.425668 pvalue = 0.0641903 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.354761 pvalue = 0.244448 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 sd = 0.0410 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8250 sd = 0.0410 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1229 freq = 0.0000 freq = 0.1391
+allele 2 : freq = 0.8125 freq = 0.8771 freq = 0.0000 freq = 0.8609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 360: rs360
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.342455 pvalue = 0.558416 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.012773 pvalue = 0.910015 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.068335 pvalue = 0.793777 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1783 sd = 0.0413 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8217 sd = 0.0413 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1917 freq = 0.0000 freq = 0.1906
+allele 2 : freq = 0.8125 freq = 0.8083 freq = 0.0000 freq = 0.8094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 361: rs361
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.581854 pvalue = 0.445586 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.054774 pvalue = 0.30441 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.803273 pvalue = 0.0284057 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3783 sd = 0.0524 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+allele 2 : freq = 0.6217 sd = 0.0524 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4000 freq = 0.3500 freq = 0.0000 freq = 0.3625
+allele 2 : freq = 0.6000 freq = 0.6500 freq = 0.0000 freq = 0.6375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 362: rs362
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.989740 pvalue = 0.319806 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.241626 pvalue = 0.265158 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.072901 pvalue = 0.78716 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8917 sd = 0.0336 freq = 0.9115 sd = 0.0216 freq = 0.0000 sd = 0.0000 freq = 0.9150 sd = 0.0197
+allele 2 : freq = 0.1083 sd = 0.0336 freq = 0.0885 sd = 0.0216 freq = 0.0000 sd = 0.0000 freq = 0.0850 sd = 0.0197
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8938 freq = 0.9250 freq = 0.0000 freq = 0.9172
+allele 2 : freq = 0.1062 freq = 0.0750 freq = 0.0000 freq = 0.0828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 363: rs363
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.074416 pvalue = 0.785012 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.152362 pvalue = 0.696288 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9383 sd = 0.0260 freq = 0.9423 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.9450 sd = 0.0161
+allele 2 : freq = 0.0617 sd = 0.0260 freq = 0.0577 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.0550 sd = 0.0161
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9375 freq = 0.9375 freq = 0.0000 freq = 0.9375
+allele 2 : freq = 0.0625 freq = 0.0625 freq = 0.0000 freq = 0.0625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 364: rs364
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.563048 pvalue = 0.453035 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.070431 pvalue = 0.79071 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.768954 pvalue = 0.380541 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3533 sd = 0.0516 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+allele 2 : freq = 0.6467 sd = 0.0516 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.3500 freq = 0.0000 freq = 0.3531
+allele 2 : freq = 0.6375 freq = 0.6500 freq = 0.0000 freq = 0.6469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 365: rs365
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.010104 pvalue = 0.919934 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.250825 pvalue = 0.616495 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006846 pvalue = 0.934057 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.5312 freq = 0.0000 freq = 0.5375
+allele 2 : freq = 0.4437 freq = 0.4688 freq = 0.0000 freq = 0.4625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 366: rs366
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.894811 pvalue = 0.344177 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.126195 pvalue = 0.288588 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.781899 pvalue = 0.376561 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3017 sd = 0.0496 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+allele 2 : freq = 0.6983 sd = 0.0496 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3125 freq = 0.2646 freq = 0.0000 freq = 0.2766
+allele 2 : freq = 0.6875 freq = 0.7354 freq = 0.0000 freq = 0.7234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 367: rs367
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.360003 pvalue = 0.548504 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.061958 pvalue = 0.803427 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.018790 pvalue = 0.89097 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.5437 freq = 0.0000 freq = 0.5469
+allele 2 : freq = 0.4437 freq = 0.4562 freq = 0.0000 freq = 0.4531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 368: rs368
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.020196 pvalue = 0.886991 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.250241 pvalue = 0.616906 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.436054 pvalue = 0.230779 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5600 sd = 0.0536 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+allele 2 : freq = 0.4400 sd = 0.0536 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.5813 freq = 0.0000 freq = 0.5750
+allele 2 : freq = 0.4437 freq = 0.4188 freq = 0.0000 freq = 0.4250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 369: rs369
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.123195 pvalue = 0.725595 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.158470 pvalue = 0.690569 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.085439 pvalue = 0.770057 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3617 sd = 0.0519 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+allele 2 : freq = 0.6383 sd = 0.0519 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3187 freq = 0.0000 freq = 0.3234
+allele 2 : freq = 0.6625 freq = 0.6813 freq = 0.0000 freq = 0.6766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 370: rs370
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.275883 pvalue = 0.599412 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.043195 pvalue = 0.835358 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.068099 pvalue = 0.794125 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5125 freq = 0.5229 freq = 0.0000 freq = 0.5203
+allele 2 : freq = 0.4875 freq = 0.4771 freq = 0.0000 freq = 0.4797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 371: rs371
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.426061 pvalue = 0.119332 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.945750 pvalue = 0.163046 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.565398 pvalue = 0.0589956 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2417 sd = 0.0462 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+allele 2 : freq = 0.7583 sd = 0.0462 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.3083 freq = 0.0000 freq = 0.2922
+allele 2 : freq = 0.7562 freq = 0.6917 freq = 0.0000 freq = 0.7078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 372: rs372
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.118533 pvalue = 0.290235 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.909619 pvalue = 0.340216 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.868077 pvalue = 0.351488 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.4771 freq = 0.0000 freq = 0.4891
+allele 2 : freq = 0.4750 freq = 0.5229 freq = 0.0000 freq = 0.5109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 373: rs373
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.489858 pvalue = 0.0340965 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.465726 pvalue = 0.0345814 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.023403 pvalue = 0.0820711 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.4731 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.5269 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.4750 freq = 0.0000 freq = 0.5016
+allele 2 : freq = 0.4188 freq = 0.5250 freq = 0.0000 freq = 0.4984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 374: rs374
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.181143 pvalue = 0.670392 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.265427 pvalue = 0.606416 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.489779 pvalue = 0.484026 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1517 sd = 0.0387 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+allele 2 : freq = 0.8483 sd = 0.0387 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.1625 freq = 0.0000 freq = 0.1578
+allele 2 : freq = 0.8562 freq = 0.8375 freq = 0.0000 freq = 0.8422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 375: rs375
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 8.807605 pvalue = 0.00299978 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 7.935256 pvalue = 0.00484808 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.284271 pvalue = 0.0215189 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5117 sd = 0.0540 freq = 0.3596 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+allele 2 : freq = 0.4883 sd = 0.0540 freq = 0.6404 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.3625 freq = 0.0000 freq = 0.3969
+allele 2 : freq = 0.5000 freq = 0.6375 freq = 0.0000 freq = 0.6031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 376: rs376
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.693880 pvalue = 0.100734 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.355333 pvalue = 0.244348 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.113292 pvalue = 0.736427 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1917 sd = 0.0425 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+allele 2 : freq = 0.8083 sd = 0.0425 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.2250 freq = 0.0000 freq = 0.2125
+allele 2 : freq = 0.8250 freq = 0.7750 freq = 0.0000 freq = 0.7875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 377: rs377
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.114368 pvalue = 0.291134 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.556775 pvalue = 0.455563 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.916234 pvalue = 0.338466 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3483 sd = 0.0515 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.6517 sd = 0.0515 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3812 freq = 0.3458 freq = 0.0000 freq = 0.3547
+allele 2 : freq = 0.6188 freq = 0.6542 freq = 0.0000 freq = 0.6453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 378: rs378
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.304930 pvalue = 0.580808 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.919249 pvalue = 0.337672 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.162570 pvalue = 0.686801 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3567 sd = 0.0517 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+allele 2 : freq = 0.6433 sd = 0.0517 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.3771 freq = 0.0000 freq = 0.3656
+allele 2 : freq = 0.6687 freq = 0.6229 freq = 0.0000 freq = 0.6344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 379: rs379
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.134110 pvalue = 0.714208 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.225889 pvalue = 0.634589 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.059865 pvalue = 0.303246 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 freq = 0.8187 freq = 0.0000 freq = 0.8141
+allele 2 : freq = 0.2000 freq = 0.1812 freq = 0.0000 freq = 0.1859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 380: rs380
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.787906 pvalue = 0.181181 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.870294 pvalue = 0.171441 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 7.057036 pvalue = 0.00789545 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.4750 freq = 0.0000 freq = 0.4922
+allele 2 : freq = 0.4562 freq = 0.5250 freq = 0.0000 freq = 0.5078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 381: rs381
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000002 pvalue = 0.998833 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.168002 pvalue = 0.279812 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.044211 pvalue = 0.013952 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5188 freq = 0.4646 freq = 0.0000 freq = 0.4781
+allele 2 : freq = 0.4813 freq = 0.5354 freq = 0.0000 freq = 0.5219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 382: rs382
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.523206 pvalue = 0.469477 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.578275 pvalue = 0.446989 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.221960 pvalue = 0.637551 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0317 sd = 0.0189 freq = 0.0481 sd = 0.0162 freq = 0.0000 sd = 0.0000 freq = 0.0500 sd = 0.0154
+allele 2 : freq = 0.9683 sd = 0.0189 freq = 0.9519 sd = 0.0162 freq = 0.0000 sd = 0.0000 freq = 0.9500 sd = 0.0154
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0375 freq = 0.0542 freq = 0.0000 freq = 0.0500
+allele 2 : freq = 0.9625 freq = 0.9458 freq = 0.0000 freq = 0.9500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 383: rs383
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.661516 pvalue = 0.197399 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.663837 pvalue = 0.197086 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.967394 pvalue = 0.325331 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7367 sd = 0.0476 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.2633 sd = 0.0476 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.7854 freq = 0.0000 freq = 0.7719
+allele 2 : freq = 0.2687 freq = 0.2146 freq = 0.0000 freq = 0.2281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 384: rs384
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.965986 pvalue = 0.325683 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.546342 pvalue = 0.213676 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.604892 pvalue = 0.436717 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7100 sd = 0.0490 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+allele 2 : freq = 0.2900 sd = 0.0490 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.6542 freq = 0.0000 freq = 0.6687
+allele 2 : freq = 0.2875 freq = 0.3458 freq = 0.0000 freq = 0.3312
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 385: rs385
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.382460 pvalue = 0.536289 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.254296 pvalue = 0.614066 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.159919 pvalue = 0.689231 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.2167 freq = 0.0000 freq = 0.2219
+allele 2 : freq = 0.7625 freq = 0.7833 freq = 0.0000 freq = 0.7781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 386: rs386
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.606054 pvalue = 0.436277 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.009281 pvalue = 0.923252 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.184671 pvalue = 0.667389 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7733 sd = 0.0452 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2267 sd = 0.0452 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7937 freq = 0.7896 freq = 0.0000 freq = 0.7906
+allele 2 : freq = 0.2062 freq = 0.2104 freq = 0.0000 freq = 0.2094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 387: rs387
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.042954 pvalue = 0.307135 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.233669 pvalue = 0.628816 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.117145 pvalue = 0.732151 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8617 sd = 0.0373 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212
+allele 2 : freq = 0.1383 sd = 0.0373 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8833 freq = 0.0000 freq = 0.8797
+allele 2 : freq = 0.1313 freq = 0.1167 freq = 0.0000 freq = 0.1203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 388: rs388
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.160605 pvalue = 0.28134 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.579876 pvalue = 0.446361 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000219 pvalue = 0.988191 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6600 sd = 0.0512 freq = 0.6827 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+allele 2 : freq = 0.3400 sd = 0.0512 freq = 0.3173 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6438 freq = 0.6792 freq = 0.0000 freq = 0.6703
+allele 2 : freq = 0.3563 freq = 0.3208 freq = 0.0000 freq = 0.3297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 389: rs389
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.160064 pvalue = 0.281452 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.914465 pvalue = 0.338933 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.454382 pvalue = 0.500261 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8750 sd = 0.0357 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230
+allele 2 : freq = 0.1250 sd = 0.0357 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8500 freq = 0.8812 freq = 0.0000 freq = 0.8734
+allele 2 : freq = 0.1500 freq = 0.1187 freq = 0.0000 freq = 0.1266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 390: rs390
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.248105 pvalue = 0.618413 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.112069 pvalue = 0.737801 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.055251 pvalue = 0.814166 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.5750 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.4250 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.6229 freq = 0.0000 freq = 0.6188
+allele 2 : freq = 0.3937 freq = 0.3771 freq = 0.0000 freq = 0.3812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 391: rs391
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.072785 pvalue = 0.787325 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.021811 pvalue = 0.882591 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.017068 pvalue = 0.313216 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1867 sd = 0.0421 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+allele 2 : freq = 0.8133 sd = 0.0421 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.2250 freq = 0.0000 freq = 0.2234
+allele 2 : freq = 0.7812 freq = 0.7750 freq = 0.0000 freq = 0.7766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 392: rs392
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.836821 pvalue = 0.360308 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.018760 pvalue = 0.891057 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.153842 pvalue = 0.69489 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.7154 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321
+allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.2846 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7688 freq = 0.0000 freq = 0.7672
+allele 2 : freq = 0.2375 freq = 0.2313 freq = 0.0000 freq = 0.2328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 393: rs393
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.703818 pvalue = 0.401504 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.440591 pvalue = 0.506837 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.568405 pvalue = 0.450894 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4967 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+allele 2 : freq = 0.5033 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5125 freq = 0.4792 freq = 0.0000 freq = 0.4875
+allele 2 : freq = 0.4875 freq = 0.5208 freq = 0.0000 freq = 0.5125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 394: rs394
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.366305 pvalue = 0.545025 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.033078 pvalue = 0.855682 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006420 pvalue = 0.936136 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8900 sd = 0.0338 freq = 0.8750 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.1100 sd = 0.0338 freq = 0.1250 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8812 freq = 0.0000 freq = 0.8828
+allele 2 : freq = 0.1125 freq = 0.1187 freq = 0.0000 freq = 0.1172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 395: rs395
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.293295 pvalue = 0.588117 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.429761 pvalue = 0.512106 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.722133 pvalue = 0.395445 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.7958 freq = 0.0000 freq = 0.7891
+allele 2 : freq = 0.2313 freq = 0.2042 freq = 0.0000 freq = 0.2109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 396: rs396
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.177202 pvalue = 0.673789 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.013108 pvalue = 0.908851 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.516611 pvalue = 0.472291 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 sd = 0.0410 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+allele 2 : freq = 0.8250 sd = 0.0410 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.1792 freq = 0.0000 freq = 0.1781
+allele 2 : freq = 0.8250 freq = 0.8208 freq = 0.0000 freq = 0.8219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 397: rs397
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.752273 pvalue = 0.385758 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.259786 pvalue = 0.610267 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003151 pvalue = 0.955232 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5767 sd = 0.0534 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+allele 2 : freq = 0.4233 sd = 0.0534 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.5938 freq = 0.0000 freq = 0.5875
+allele 2 : freq = 0.4313 freq = 0.4062 freq = 0.0000 freq = 0.4125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 398: rs398
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.893661 pvalue = 0.344487 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.252642 pvalue = 0.263049 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.624648 pvalue = 0.0569296 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4400 sd = 0.0536 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.5600 sd = 0.0536 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.5062 freq = 0.0000 freq = 0.4922
+allele 2 : freq = 0.5500 freq = 0.4938 freq = 0.0000 freq = 0.5078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 399: rs399
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.275078 pvalue = 0.131468 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.138763 pvalue = 0.285914 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.052881 pvalue = 0.818124 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.7104 freq = 0.0000 freq = 0.6984
+allele 2 : freq = 0.3375 freq = 0.2896 freq = 0.0000 freq = 0.3016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 400: rs400
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.239150 pvalue = 0.624821 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.023701 pvalue = 0.877648 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.014088 pvalue = 0.905517 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.7625 freq = 0.0000 freq = 0.7641
+allele 2 : freq = 0.2313 freq = 0.2375 freq = 0.0000 freq = 0.2359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 401: rs401
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 6.032616 pvalue = 0.0140439 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.238076 pvalue = 0.0719451 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.781899 pvalue = 0.376561 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6283 sd = 0.0522 freq = 0.7269 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.3717 sd = 0.0522 freq = 0.2731 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.7000 freq = 0.0000 freq = 0.6797
+allele 2 : freq = 0.3812 freq = 0.3000 freq = 0.0000 freq = 0.3203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 402: rs402
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.125227 pvalue = 0.288796 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.803363 pvalue = 0.37009 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.518140 pvalue = 0.0607005 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.6250 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.3750 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.6188 freq = 0.0000 freq = 0.6078
+allele 2 : freq = 0.4250 freq = 0.3812 freq = 0.0000 freq = 0.3922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 403: rs403
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.088036 pvalue = 0.76669 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.022152 pvalue = 0.881684 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.107488 pvalue = 0.743022 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7833 sd = 0.0445 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.2167 sd = 0.0445 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7812 freq = 0.0000 freq = 0.7828
+allele 2 : freq = 0.2125 freq = 0.2188 freq = 0.0000 freq = 0.2172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 404: rs404
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.524487 pvalue = 0.468934 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.061902 pvalue = 0.803514 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.099311 pvalue = 0.752658 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5400 sd = 0.0538 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.4600 sd = 0.0538 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5188 freq = 0.5062 freq = 0.0000 freq = 0.5094
+allele 2 : freq = 0.4813 freq = 0.4938 freq = 0.0000 freq = 0.4906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 405: rs405
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.939561 pvalue = 0.332391 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.650999 pvalue = 0.419756 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.298603 pvalue = 0.0693388 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7500 freq = 0.7833 freq = 0.0000 freq = 0.7750
+allele 2 : freq = 0.2500 freq = 0.2167 freq = 0.0000 freq = 0.2250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 406: rs406
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.401856 pvalue = 0.121191 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.305326 pvalue = 0.0690557 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.499101 pvalue = 0.113911 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6967 sd = 0.0497 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+allele 2 : freq = 0.3033 sd = 0.0497 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 freq = 0.7792 freq = 0.0000 freq = 0.7594
+allele 2 : freq = 0.3000 freq = 0.2208 freq = 0.0000 freq = 0.2406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 407: rs407
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.811601 pvalue = 0.367647 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.770623 pvalue = 0.380024 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.666091 pvalue = 0.196783 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6933 sd = 0.0498 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+allele 2 : freq = 0.3067 sd = 0.0498 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 freq = 0.6583 freq = 0.0000 freq = 0.6687
+allele 2 : freq = 0.3000 freq = 0.3417 freq = 0.0000 freq = 0.3312
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 408: rs408
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.556279 pvalue = 0.455763 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.908254 pvalue = 0.340578 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.140454 pvalue = 0.285556 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.4904 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.5096 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5312 freq = 0.4833 freq = 0.0000 freq = 0.4953
+allele 2 : freq = 0.4688 freq = 0.5167 freq = 0.0000 freq = 0.5047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 409: rs409
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.421521 pvalue = 0.516179 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.116981 pvalue = 0.732332 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.051087 pvalue = 0.821182 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7635 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2365 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7375 freq = 0.7521 freq = 0.0000 freq = 0.7484
+allele 2 : freq = 0.2625 freq = 0.2479 freq = 0.0000 freq = 0.2516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 410: rs410
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.058883 pvalue = 0.80827 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.212891 pvalue = 0.644511 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.601219 pvalue = 0.205731 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6967 sd = 0.0497 freq = 0.7288 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.3033 sd = 0.0497 freq = 0.2712 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.7042 freq = 0.0000 freq = 0.7094
+allele 2 : freq = 0.2750 freq = 0.2958 freq = 0.0000 freq = 0.2906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 411: rs411
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.702219 pvalue = 0.402039 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.492104 pvalue = 0.22189 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.427313 pvalue = 0.232203 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2125 freq = 0.2646 freq = 0.0000 freq = 0.2516
+allele 2 : freq = 0.7875 freq = 0.7354 freq = 0.0000 freq = 0.7484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 412: rs412
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.034556 pvalue = 0.85253 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.404090 pvalue = 0.524984 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.433140 pvalue = 0.510452 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6067 sd = 0.0528 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.3933 sd = 0.0528 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.6375 freq = 0.0000 freq = 0.6297
+allele 2 : freq = 0.3937 freq = 0.3625 freq = 0.0000 freq = 0.3703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 413: rs413
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.362410 pvalue = 0.547171 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.205980 pvalue = 0.649937 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.199161 pvalue = 0.138086 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7600 sd = 0.0461 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2400 sd = 0.0461 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7812 freq = 0.0000 freq = 0.7766
+allele 2 : freq = 0.2375 freq = 0.2188 freq = 0.0000 freq = 0.2234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 414: rs414
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.175138 pvalue = 0.675586 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.052482 pvalue = 0.818799 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.464125 pvalue = 0.495702 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0650 sd = 0.0266 freq = 0.0904 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.0800 sd = 0.0192
+allele 2 : freq = 0.9350 sd = 0.0266 freq = 0.9096 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.9200 sd = 0.0192
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0688 freq = 0.0750 freq = 0.0000 freq = 0.0734
+allele 2 : freq = 0.9313 freq = 0.9250 freq = 0.0000 freq = 0.9266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 415: rs415
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.350931 pvalue = 0.553586 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.616896 pvalue = 0.203525 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.190935 pvalue = 0.66214 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.8333 freq = 0.0000 freq = 0.8203
+allele 2 : freq = 0.2188 freq = 0.1667 freq = 0.0000 freq = 0.1797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 416: rs416
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.005403 pvalue = 0.0829873 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.907408 pvalue = 0.0881735 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.737062 pvalue = 0.390604 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1017 sd = 0.0326 freq = 0.0577 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.0700 sd = 0.0180
+allele 2 : freq = 0.8983 sd = 0.0326 freq = 0.9423 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.9300 sd = 0.0180
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1062 freq = 0.0625 freq = 0.0000 freq = 0.0734
+allele 2 : freq = 0.8938 freq = 0.9375 freq = 0.0000 freq = 0.9266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 417: rs417
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.718511 pvalue = 0.396633 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.319878 pvalue = 0.250614 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.584865 pvalue = 0.10789 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0900 sd = 0.0309 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217
+allele 2 : freq = 0.9100 sd = 0.0309 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0875 freq = 0.1229 freq = 0.0000 freq = 0.1141
+allele 2 : freq = 0.9125 freq = 0.8771 freq = 0.0000 freq = 0.8859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 418: rs418
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.571973 pvalue = 0.209921 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.637457 pvalue = 0.104371 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.001421 pvalue = 0.316967 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2933 sd = 0.0492 freq = 0.3500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.7067 sd = 0.0492 freq = 0.6500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.3708 freq = 0.0000 freq = 0.3516
+allele 2 : freq = 0.7063 freq = 0.6292 freq = 0.0000 freq = 0.6484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 419: rs419
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.031243 pvalue = 0.859699 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.045780 pvalue = 0.830576 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.279540 pvalue = 0.257985 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.6208 freq = 0.0000 freq = 0.6234
+allele 2 : freq = 0.3688 freq = 0.3792 freq = 0.0000 freq = 0.3766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 420: rs420
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.181144 pvalue = 0.0228333 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.852666 pvalue = 0.049667 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.077175 pvalue = 0.149517 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1133 sd = 0.0342 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+allele 2 : freq = 0.8867 sd = 0.0342 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1000 freq = 0.1750 freq = 0.0000 freq = 0.1562
+allele 2 : freq = 0.9000 freq = 0.8250 freq = 0.0000 freq = 0.8438
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 421: rs421
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.402260 pvalue = 0.525925 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.252642 pvalue = 0.263049 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.121876 pvalue = 0.0772478 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5308 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4692 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5312 freq = 0.4750 freq = 0.0000 freq = 0.4891
+allele 2 : freq = 0.4688 freq = 0.5250 freq = 0.0000 freq = 0.5109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 422: rs422
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.234940 pvalue = 0.627885 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.284022 pvalue = 0.594077 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000861 pvalue = 0.976586 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6483 sd = 0.0516 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+allele 2 : freq = 0.3517 sd = 0.0516 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.6875 freq = 0.0000 freq = 0.6813
+allele 2 : freq = 0.3375 freq = 0.3125 freq = 0.0000 freq = 0.3187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 423: rs423
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000755 pvalue = 0.978075 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.132074 pvalue = 0.716291 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.519107 pvalue = 0.471223 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3183 sd = 0.0503 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+allele 2 : freq = 0.6817 sd = 0.0503 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.3167 freq = 0.0000 freq = 0.3125
+allele 2 : freq = 0.7000 freq = 0.6833 freq = 0.0000 freq = 0.6875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 424: rs424
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.171403 pvalue = 0.279113 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.651288 pvalue = 0.198784 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000188 pvalue = 0.989072 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5150 sd = 0.0540 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.4850 sd = 0.0540 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.4604 freq = 0.0000 freq = 0.4766
+allele 2 : freq = 0.4750 freq = 0.5396 freq = 0.0000 freq = 0.5234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 425: rs425
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.895455 pvalue = 0.344003 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.443929 pvalue = 0.505232 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.231924 pvalue = 0.630101 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3950 sd = 0.0528 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.6050 sd = 0.0528 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.4396 freq = 0.0000 freq = 0.4313
+allele 2 : freq = 0.5938 freq = 0.5604 freq = 0.0000 freq = 0.5687
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 426: rs426
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.310472 pvalue = 0.577391 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.028036 pvalue = 0.867024 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.229912 pvalue = 0.631589 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8267 sd = 0.0409 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1733 sd = 0.0409 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8125 freq = 0.8187 freq = 0.0000 freq = 0.8172
+allele 2 : freq = 0.1875 freq = 0.1812 freq = 0.0000 freq = 0.1828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 427: rs427
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.365492 pvalue = 0.545472 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.499338 pvalue = 0.479791 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.490652 pvalue = 0.483636 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5417 sd = 0.0538 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4583 sd = 0.0538 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5271 freq = 0.0000 freq = 0.5359
+allele 2 : freq = 0.4375 freq = 0.4729 freq = 0.0000 freq = 0.4641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 428: rs428
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.328214 pvalue = 0.566712 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.303139 pvalue = 0.581921 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.827405 pvalue = 0.363024 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9000 sd = 0.0324 freq = 0.9308 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186
+allele 2 : freq = 0.1000 sd = 0.0324 freq = 0.0692 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9125 freq = 0.9271 freq = 0.0000 freq = 0.9234
+allele 2 : freq = 0.0875 freq = 0.0729 freq = 0.0000 freq = 0.0766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 429: rs429
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.012790 pvalue = 0.909956 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.089254 pvalue = 0.765128 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3050 sd = 0.0497 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.6950 sd = 0.0497 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3063 freq = 0.3063 freq = 0.0000 freq = 0.3063
+allele 2 : freq = 0.6937 freq = 0.6937 freq = 0.0000 freq = 0.6937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 430: rs430
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.012324 pvalue = 0.911607 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007004 pvalue = 0.933302 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.163137 pvalue = 0.280816 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.4292 freq = 0.0000 freq = 0.4281
+allele 2 : freq = 0.5750 freq = 0.5708 freq = 0.0000 freq = 0.5719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 431: rs431
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.193891 pvalue = 0.659698 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.404090 pvalue = 0.524984 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.350793 pvalue = 0.245139 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3812 freq = 0.4125 freq = 0.0000 freq = 0.4047
+allele 2 : freq = 0.6188 freq = 0.5875 freq = 0.0000 freq = 0.5953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 432: rs432
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.121396 pvalue = 0.727525 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002259 pvalue = 0.96209 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.948139 pvalue = 0.330193 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.2396 freq = 0.0000 freq = 0.2391
+allele 2 : freq = 0.7625 freq = 0.7604 freq = 0.0000 freq = 0.7609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 433: rs433
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.128417 pvalue = 0.720079 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002178 pvalue = 0.962781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.439577 pvalue = 0.507326 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2433 sd = 0.0463 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+allele 2 : freq = 0.7567 sd = 0.0463 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.2479 freq = 0.0000 freq = 0.2484
+allele 2 : freq = 0.7500 freq = 0.7521 freq = 0.0000 freq = 0.7516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 434: rs434
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.523012 pvalue = 0.46956 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.766362 pvalue = 0.381345 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.012143 pvalue = 0.912256 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4417 sd = 0.0536 freq = 0.4327 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5583 sd = 0.0536 freq = 0.5673 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4188 freq = 0.4625 freq = 0.0000 freq = 0.4516
+allele 2 : freq = 0.5813 freq = 0.5375 freq = 0.0000 freq = 0.5484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 435: rs435
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.202733 pvalue = 0.652523 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.611166 pvalue = 0.434349 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.031539 pvalue = 0.859044 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 freq = 0.7417 freq = 0.0000 freq = 0.7500
+allele 2 : freq = 0.2250 freq = 0.2583 freq = 0.0000 freq = 0.2500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 436: rs436
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.216030 pvalue = 0.0223796 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 7.116378 pvalue = 0.00763829 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.272963 pvalue = 0.259212 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8517 sd = 0.0384 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275
+allele 2 : freq = 0.1483 sd = 0.0384 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8812 freq = 0.7771 freq = 0.0000 freq = 0.8031
+allele 2 : freq = 0.1187 freq = 0.2229 freq = 0.0000 freq = 0.1969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 437: rs437
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.692970 pvalue = 0.405156 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.174366 pvalue = 0.67626 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.094010 pvalue = 0.75914 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2533 sd = 0.0470 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+allele 2 : freq = 0.7467 sd = 0.0470 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.2562 freq = 0.0000 freq = 0.2516
+allele 2 : freq = 0.7625 freq = 0.7438 freq = 0.0000 freq = 0.7484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 438: rs438
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.726948 pvalue = 0.393874 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.008875 pvalue = 0.315173 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.230484 pvalue = 0.135311 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321
+allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.7271 freq = 0.0000 freq = 0.7156
+allele 2 : freq = 0.3187 freq = 0.2729 freq = 0.0000 freq = 0.2844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 439: rs439
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.883765 pvalue = 0.347172 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.676519 pvalue = 0.195388 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.468582 pvalue = 0.49364 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2133 sd = 0.0442 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+allele 2 : freq = 0.7867 sd = 0.0442 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.1729 freq = 0.0000 freq = 0.1859
+allele 2 : freq = 0.7750 freq = 0.8271 freq = 0.0000 freq = 0.8141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 440: rs440
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.597378 pvalue = 0.43958 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.933919 pvalue = 0.333847 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.762759 pvalue = 0.184281 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 sd = 0.0410 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+allele 2 : freq = 0.8250 sd = 0.0410 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.2271 freq = 0.0000 freq = 0.2172
+allele 2 : freq = 0.8125 freq = 0.7729 freq = 0.0000 freq = 0.7828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 441: rs441
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.492200 pvalue = 0.482948 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.459845 pvalue = 0.497696 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.153753 pvalue = 0.694974 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1633 sd = 0.0399 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8367 sd = 0.0399 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1812 freq = 0.1562 freq = 0.0000 freq = 0.1625
+allele 2 : freq = 0.8187 freq = 0.8438 freq = 0.0000 freq = 0.8375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 442: rs442
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.465742 pvalue = 0.494952 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.563041 pvalue = 0.453037 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.641777 pvalue = 0.104087 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5933 sd = 0.0531 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+allele 2 : freq = 0.4067 sd = 0.0531 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.5437 freq = 0.0000 freq = 0.5531
+allele 2 : freq = 0.4188 freq = 0.4562 freq = 0.0000 freq = 0.4469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 443: rs443
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.146319 pvalue = 0.702078 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.493199 pvalue = 0.482504 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.202135 pvalue = 0.653003 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6450 sd = 0.0517 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+allele 2 : freq = 0.3550 sd = 0.0517 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6562 freq = 0.6896 freq = 0.0000 freq = 0.6813
+allele 2 : freq = 0.3438 freq = 0.3104 freq = 0.0000 freq = 0.3187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 444: rs444
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.003350 pvalue = 0.953842 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.109971 pvalue = 0.740177 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.243131 pvalue = 0.621953 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4833 sd = 0.0540 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.5167 sd = 0.0540 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 freq = 0.4583 freq = 0.0000 freq = 0.4625
+allele 2 : freq = 0.5250 freq = 0.5417 freq = 0.0000 freq = 0.5375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 445: rs445
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.031501 pvalue = 0.859128 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.090040 pvalue = 0.764127 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.629144 pvalue = 0.427669 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.1938 freq = 0.0000 freq = 0.1969
+allele 2 : freq = 0.7937 freq = 0.8063 freq = 0.0000 freq = 0.8031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 446: rs446
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.343259 pvalue = 0.24646 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.998839 pvalue = 0.317592 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.681573 pvalue = 0.409046 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6117 sd = 0.0526 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+allele 2 : freq = 0.3883 sd = 0.0526 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.5500 freq = 0.0000 freq = 0.5625
+allele 2 : freq = 0.4000 freq = 0.4500 freq = 0.0000 freq = 0.4375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 447: rs447
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.655568 pvalue = 0.198203 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.629234 pvalue = 0.201809 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.800823 pvalue = 0.179613 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8800 sd = 0.0351 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1200 sd = 0.0351 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8417 freq = 0.0000 freq = 0.8531
+allele 2 : freq = 0.1125 freq = 0.1583 freq = 0.0000 freq = 0.1469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 448: rs448
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.035236 pvalue = 0.851101 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.870400 pvalue = 0.0902225 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.4562 freq = 0.0000 freq = 0.4562
+allele 2 : freq = 0.5437 freq = 0.5437 freq = 0.0000 freq = 0.5437
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 449: rs449
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.790283 pvalue = 0.016115 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.073779 pvalue = 0.0435537 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.288403 pvalue = 0.130344 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6850 sd = 0.0502 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.3150 sd = 0.0502 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.7667 freq = 0.0000 freq = 0.7453
+allele 2 : freq = 0.3187 freq = 0.2333 freq = 0.0000 freq = 0.2547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 450: rs450
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.065286 pvalue = 0.798329 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.056480 pvalue = 0.812149 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.544859 pvalue = 0.460426 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7700 sd = 0.0455 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+allele 2 : freq = 0.2300 sd = 0.0455 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7729 freq = 0.0000 freq = 0.7703
+allele 2 : freq = 0.2375 freq = 0.2271 freq = 0.0000 freq = 0.2297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 451: rs451
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.170864 pvalue = 0.0411248 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.822847 pvalue = 0.0280849 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.720563 pvalue = 0.395959 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.5327 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.4673 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.5354 freq = 0.0000 freq = 0.5078
+allele 2 : freq = 0.5750 freq = 0.4646 freq = 0.0000 freq = 0.4922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 452: rs452
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.200599 pvalue = 0.654238 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.020076 pvalue = 0.887324 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.406719 pvalue = 0.235602 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2750 sd = 0.0482 freq = 0.2692 sd = 0.0337 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310
+allele 2 : freq = 0.7250 sd = 0.0482 freq = 0.7308 sd = 0.0337 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2812 freq = 0.2750 freq = 0.0000 freq = 0.2766
+allele 2 : freq = 0.7188 freq = 0.7250 freq = 0.0000 freq = 0.7234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 453: rs453
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.278902 pvalue = 0.597422 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.443784 pvalue = 0.505302 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.699642 pvalue = 0.402904 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6683 sd = 0.0509 freq = 0.6827 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+allele 2 : freq = 0.3317 sd = 0.0509 freq = 0.3173 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.6937 freq = 0.0000 freq = 0.6859
+allele 2 : freq = 0.3375 freq = 0.3063 freq = 0.0000 freq = 0.3141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 454: rs454
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.037289 pvalue = 0.308453 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.458375 pvalue = 0.227189 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.118329 pvalue = 0.730854 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.4271 freq = 0.0000 freq = 0.4422
+allele 2 : freq = 0.5125 freq = 0.5729 freq = 0.0000 freq = 0.5578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 455: rs455
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.945941 pvalue = 0.0860935 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.390639 pvalue = 0.122064 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.510176 pvalue = 0.219112 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.4396 freq = 0.0000 freq = 0.4203
+allele 2 : freq = 0.6375 freq = 0.5604 freq = 0.0000 freq = 0.5797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 456: rs456
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.713060 pvalue = 0.190589 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.393102 pvalue = 0.237882 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.761317 pvalue = 0.0965687 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2450 sd = 0.0465 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+allele 2 : freq = 0.7550 sd = 0.0465 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.2021 freq = 0.0000 freq = 0.2141
+allele 2 : freq = 0.7500 freq = 0.7979 freq = 0.0000 freq = 0.7859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 457: rs457
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.023268 pvalue = 0.878763 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.070143 pvalue = 0.791128 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.275692 pvalue = 0.599539 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1050 sd = 0.0331 freq = 0.1000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221
+allele 2 : freq = 0.8950 sd = 0.0331 freq = 0.9000 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1125 freq = 0.1042 freq = 0.0000 freq = 0.1062
+allele 2 : freq = 0.8875 freq = 0.8958 freq = 0.0000 freq = 0.8938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 458: rs458
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.104511 pvalue = 0.042769 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.583574 pvalue = 0.0181297 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.050141 pvalue = 0.305475 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2817 sd = 0.0486 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+allele 2 : freq = 0.7183 sd = 0.0486 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.1938 freq = 0.0000 freq = 0.2188
+allele 2 : freq = 0.7063 freq = 0.8063 freq = 0.0000 freq = 0.7812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 459: rs459
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.227985 pvalue = 0.633022 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.011631 pvalue = 0.914116 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001270 pvalue = 0.971573 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8479 freq = 0.0000 freq = 0.8469
+allele 2 : freq = 0.1562 freq = 0.1521 freq = 0.0000 freq = 0.1531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 460: rs460
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.079753 pvalue = 0.777632 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.265427 pvalue = 0.606416 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.606003 pvalue = 0.205055 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8500 freq = 0.8313 freq = 0.0000 freq = 0.8359
+allele 2 : freq = 0.1500 freq = 0.1688 freq = 0.0000 freq = 0.1641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 461: rs461
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.215856 pvalue = 0.0400479 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.905171 pvalue = 0.0481377 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.597151 pvalue = 0.107056 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3383 sd = 0.0511 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+allele 2 : freq = 0.6617 sd = 0.0511 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.4292 freq = 0.0000 freq = 0.4047
+allele 2 : freq = 0.6687 freq = 0.5708 freq = 0.0000 freq = 0.5953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 462: rs462
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.640334 pvalue = 0.20028 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.403557 pvalue = 0.12106 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.767043 pvalue = 0.381133 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1833 sd = 0.0418 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+allele 2 : freq = 0.8167 sd = 0.0418 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1812 freq = 0.2458 freq = 0.0000 freq = 0.2297
+allele 2 : freq = 0.8187 freq = 0.7542 freq = 0.0000 freq = 0.7703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 463: rs463
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.821793 pvalue = 0.364656 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.556451 pvalue = 0.455694 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.697716 pvalue = 0.403552 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 sd = 0.0537 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.5500 sd = 0.0537 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4875 freq = 0.0000 freq = 0.4781
+allele 2 : freq = 0.5500 freq = 0.5125 freq = 0.0000 freq = 0.5219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 464: rs464
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.390306 pvalue = 0.532139 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386585 pvalue = 0.5341 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.582281 pvalue = 0.445419 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.3146 freq = 0.0000 freq = 0.3219
+allele 2 : freq = 0.6562 freq = 0.6854 freq = 0.0000 freq = 0.6781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 465: rs465
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.629075 pvalue = 0.201831 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.687747 pvalue = 0.193898 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.564313 pvalue = 0.452528 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9467 sd = 0.0243 freq = 0.9231 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.9300 sd = 0.0180
+allele 2 : freq = 0.0533 sd = 0.0243 freq = 0.0769 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.0700 sd = 0.0180
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9563 freq = 0.9229 freq = 0.0000 freq = 0.9313
+allele 2 : freq = 0.0437 freq = 0.0771 freq = 0.0000 freq = 0.0688
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 466: rs466
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.497382 pvalue = 0.480653 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.250241 pvalue = 0.616906 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.437134 pvalue = 0.508509 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.4375 freq = 0.0000 freq = 0.4313
+allele 2 : freq = 0.5875 freq = 0.5625 freq = 0.0000 freq = 0.5687
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 467: rs467
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000359 pvalue = 0.984892 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.062706 pvalue = 0.802269 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.128556 pvalue = 0.719934 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4383 sd = 0.0536 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+allele 2 : freq = 0.5617 sd = 0.0536 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4437 freq = 0.4562 freq = 0.0000 freq = 0.4531
+allele 2 : freq = 0.5563 freq = 0.5437 freq = 0.0000 freq = 0.5469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 468: rs468
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.099689 pvalue = 0.294334 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.086114 pvalue = 0.297334 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.851690 pvalue = 0.356075 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5050 sd = 0.0540 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.4950 sd = 0.0540 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.4354 freq = 0.0000 freq = 0.4484
+allele 2 : freq = 0.5125 freq = 0.5646 freq = 0.0000 freq = 0.5516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 469: rs469
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.224508 pvalue = 0.268478 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.209424 pvalue = 0.647219 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.333331 pvalue = 0.563704 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5125 freq = 0.4896 freq = 0.0000 freq = 0.4953
+allele 2 : freq = 0.4875 freq = 0.5104 freq = 0.0000 freq = 0.5047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 470: rs470
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.920887 pvalue = 0.165759 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.486758 pvalue = 0.22272 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.168667 pvalue = 0.140848 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3433 sd = 0.0513 freq = 0.4250 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+allele 2 : freq = 0.6567 sd = 0.0513 freq = 0.5750 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3563 freq = 0.4167 freq = 0.0000 freq = 0.4016
+allele 2 : freq = 0.6438 freq = 0.5833 freq = 0.0000 freq = 0.5984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 471: rs471
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.017107 pvalue = 0.895939 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.043657 pvalue = 0.834494 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003050 pvalue = 0.955954 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.5583 freq = 0.0000 freq = 0.5609
+allele 2 : freq = 0.4313 freq = 0.4417 freq = 0.0000 freq = 0.4391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 472: rs472
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.165666 pvalue = 0.683992 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.133972 pvalue = 0.714349 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.890740 pvalue = 0.0270011 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.2019 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.7981 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1812 freq = 0.1958 freq = 0.0000 freq = 0.1922
+allele 2 : freq = 0.8187 freq = 0.8042 freq = 0.0000 freq = 0.8078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 473: rs473
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.805915 pvalue = 0.369331 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.237895 pvalue = 0.265877 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.719741 pvalue = 0.396229 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3433 sd = 0.0513 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+allele 2 : freq = 0.6567 sd = 0.0513 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.3979 freq = 0.0000 freq = 0.3844
+allele 2 : freq = 0.6562 freq = 0.6021 freq = 0.0000 freq = 0.6156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 474: rs474
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.387785 pvalue = 0.122287 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.092595 pvalue = 0.148015 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.115065 pvalue = 0.73445 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2400 sd = 0.0461 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+allele 2 : freq = 0.7600 sd = 0.0461 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2125 freq = 0.2771 freq = 0.0000 freq = 0.2609
+allele 2 : freq = 0.7875 freq = 0.7229 freq = 0.0000 freq = 0.7391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 475: rs475
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.822566 pvalue = 0.177008 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.548467 pvalue = 0.213362 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.191858 pvalue = 0.274955 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4350 sd = 0.0535 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+allele 2 : freq = 0.5650 sd = 0.0535 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.3646 freq = 0.0000 freq = 0.3797
+allele 2 : freq = 0.5750 freq = 0.6354 freq = 0.0000 freq = 0.6203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 476: rs476
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.002917 pvalue = 0.956931 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.152791 pvalue = 0.695882 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.504616 pvalue = 0.477479 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7667 sd = 0.0457 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+allele 2 : freq = 0.2333 sd = 0.0457 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.7854 freq = 0.0000 freq = 0.7812
+allele 2 : freq = 0.2313 freq = 0.2146 freq = 0.0000 freq = 0.2188
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 477: rs477
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.989584 pvalue = 0.319844 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.450022 pvalue = 0.228524 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.675654 pvalue = 0.101893 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2783 sd = 0.0484 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.7217 sd = 0.0484 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2812 freq = 0.3375 freq = 0.0000 freq = 0.3234
+allele 2 : freq = 0.7188 freq = 0.6625 freq = 0.0000 freq = 0.6766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 478: rs478
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.129906 pvalue = 0.0421317 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.124584 pvalue = 0.0422644 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.718457 pvalue = 0.189892 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8117 sd = 0.0422 freq = 0.7346 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310
+allele 2 : freq = 0.1883 sd = 0.0422 freq = 0.2654 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8125 freq = 0.7229 freq = 0.0000 freq = 0.7453
+allele 2 : freq = 0.1875 freq = 0.2771 freq = 0.0000 freq = 0.2547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 479: rs479
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.070477 pvalue = 0.790644 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.046860 pvalue = 0.82862 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.149185 pvalue = 0.699316 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3533 sd = 0.0516 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+allele 2 : freq = 0.6467 sd = 0.0516 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.3542 freq = 0.0000 freq = 0.3516
+allele 2 : freq = 0.6562 freq = 0.6458 freq = 0.0000 freq = 0.6484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 480: rs480
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.887833 pvalue = 0.169447 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.072972 pvalue = 0.300275 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.415959 pvalue = 0.0645689 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 sd = 0.0534 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.4250 sd = 0.0534 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5104 freq = 0.0000 freq = 0.5234
+allele 2 : freq = 0.4375 freq = 0.4896 freq = 0.0000 freq = 0.4766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 481: rs481
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.216504 pvalue = 0.641717 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.604034 pvalue = 0.437043 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.203951 pvalue = 0.272533 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207
+allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9125 freq = 0.8896 freq = 0.0000 freq = 0.8953
+allele 2 : freq = 0.0875 freq = 0.1104 freq = 0.0000 freq = 0.1047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 482: rs482
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.506111 pvalue = 0.476827 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.503391 pvalue = 0.478014 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.674295 pvalue = 0.0552576 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4767 sd = 0.0539 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+allele 2 : freq = 0.5233 sd = 0.0539 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.4333 freq = 0.0000 freq = 0.4422
+allele 2 : freq = 0.5312 freq = 0.5667 freq = 0.0000 freq = 0.5578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 483: rs483
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.116459 pvalue = 0.290682 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.286853 pvalue = 0.256629 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.131190 pvalue = 0.144329 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1667 sd = 0.0403 freq = 0.1500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8333 sd = 0.0403 freq = 0.8500 sd = 0.0271 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1688 freq = 0.1292 freq = 0.0000 freq = 0.1391
+allele 2 : freq = 0.8313 freq = 0.8708 freq = 0.0000 freq = 0.8609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 484: rs484
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.597124 pvalue = 0.206311 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.340243 pvalue = 0.12607 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.024190 pvalue = 0.876403 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1200 sd = 0.0351 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8800 sd = 0.0351 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1125 freq = 0.1667 freq = 0.0000 freq = 0.1531
+allele 2 : freq = 0.8875 freq = 0.8333 freq = 0.0000 freq = 0.8469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 485: rs485
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.002234 pvalue = 0.962305 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.406719 pvalue = 0.235602 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2750 sd = 0.0482 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310
+allele 2 : freq = 0.7250 sd = 0.0482 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2625 freq = 0.2625 freq = 0.0000 freq = 0.2625
+allele 2 : freq = 0.7375 freq = 0.7375 freq = 0.0000 freq = 0.7375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 486: rs486
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.012724 pvalue = 0.910189 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 2.332156 pvalue = 0.126726 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9550 sd = 0.0224 freq = 0.9654 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.9650 sd = 0.0130
+allele 2 : freq = 0.0450 sd = 0.0224 freq = 0.0346 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.0350 sd = 0.0130
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9625 freq = 0.9625 freq = 0.0000 freq = 0.9625
+allele 2 : freq = 0.0375 freq = 0.0375 freq = 0.0000 freq = 0.0375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 487: rs487
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.078347 pvalue = 0.779551 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007765 pvalue = 0.929784 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.010385 pvalue = 0.918832 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.6917 freq = 0.0000 freq = 0.6906
+allele 2 : freq = 0.3125 freq = 0.3083 freq = 0.0000 freq = 0.3094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 488: rs488
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.820346 pvalue = 0.365079 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.778927 pvalue = 0.37747 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.545781 pvalue = 0.460047 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1183 sd = 0.0349 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8817 sd = 0.0349 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1187 freq = 0.1500 freq = 0.0000 freq = 0.1422
+allele 2 : freq = 0.8812 freq = 0.8500 freq = 0.0000 freq = 0.8578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 489: rs489
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.195433 pvalue = 0.658433 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.034944 pvalue = 0.309 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.341757 pvalue = 0.558817 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.7167 freq = 0.0000 freq = 0.7047
+allele 2 : freq = 0.3312 freq = 0.2833 freq = 0.0000 freq = 0.2953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 490: rs490
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.042672 pvalue = 0.836344 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.584519 pvalue = 0.444546 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.992904 pvalue = 0.319034 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3875 freq = 0.3500 freq = 0.0000 freq = 0.3594
+allele 2 : freq = 0.6125 freq = 0.6500 freq = 0.0000 freq = 0.6406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 491: rs491
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.770341 pvalue = 0.380112 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.593985 pvalue = 0.440882 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.468392 pvalue = 0.493728 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2233 sd = 0.0450 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+allele 2 : freq = 0.7767 sd = 0.0450 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2125 freq = 0.2458 freq = 0.0000 freq = 0.2375
+allele 2 : freq = 0.7875 freq = 0.7542 freq = 0.0000 freq = 0.7625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 492: rs492
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.287282 pvalue = 0.591967 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.122473 pvalue = 0.289387 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.530200 pvalue = 0.466523 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6183 sd = 0.0525 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.3817 sd = 0.0525 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5938 freq = 0.6458 freq = 0.0000 freq = 0.6328
+allele 2 : freq = 0.4062 freq = 0.3542 freq = 0.0000 freq = 0.3672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 493: rs493
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.072435 pvalue = 0.300396 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.051022 pvalue = 0.152104 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.409888 pvalue = 0.522026 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5700 sd = 0.0535 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4300 sd = 0.0535 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.6271 freq = 0.0000 freq = 0.6094
+allele 2 : freq = 0.4437 freq = 0.3729 freq = 0.0000 freq = 0.3906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 494: rs494
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.118371 pvalue = 0.730808 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.529218 pvalue = 0.466936 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.499820 pvalue = 0.479579 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3812 freq = 0.3458 freq = 0.0000 freq = 0.3547
+allele 2 : freq = 0.6188 freq = 0.6542 freq = 0.0000 freq = 0.6453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 495: rs495
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.845034 pvalue = 0.0916566 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.602433 pvalue = 0.437651 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.504387 pvalue = 0.477579 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8150 sd = 0.0419 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+allele 2 : freq = 0.1850 sd = 0.0419 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 freq = 0.8271 freq = 0.0000 freq = 0.8203
+allele 2 : freq = 0.2000 freq = 0.1729 freq = 0.0000 freq = 0.1797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 496: rs496
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.135418 pvalue = 0.712879 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.284714 pvalue = 0.593628 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.223090 pvalue = 0.268755 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7350 sd = 0.0477 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+allele 2 : freq = 0.2650 sd = 0.0477 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7500 freq = 0.7729 freq = 0.0000 freq = 0.7672
+allele 2 : freq = 0.2500 freq = 0.2271 freq = 0.0000 freq = 0.2328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 497: rs497
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.378116 pvalue = 0.123046 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.757031 pvalue = 0.0968278 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.228774 pvalue = 0.632434 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5850 sd = 0.0532 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+allele 2 : freq = 0.4150 sd = 0.0532 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.6375 freq = 0.0000 freq = 0.6172
+allele 2 : freq = 0.4437 freq = 0.3625 freq = 0.0000 freq = 0.3828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 498: rs498
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.021657 pvalue = 0.883004 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.061902 pvalue = 0.803514 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.745112 pvalue = 0.388028 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5017 sd = 0.0540 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+allele 2 : freq = 0.4983 sd = 0.0540 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.4938 freq = 0.0000 freq = 0.4969
+allele 2 : freq = 0.4938 freq = 0.5062 freq = 0.0000 freq = 0.5031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 499: rs499
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.191296 pvalue = 0.275068 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.895571 pvalue = 0.168575 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.018626 pvalue = 0.891444 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2700 sd = 0.0480 freq = 0.2962 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+allele 2 : freq = 0.7300 sd = 0.0480 freq = 0.7038 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.3125 freq = 0.0000 freq = 0.2969
+allele 2 : freq = 0.7500 freq = 0.6875 freq = 0.0000 freq = 0.7031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 500: rs500
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.029562 pvalue = 0.154265 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.118104 pvalue = 0.290327 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.977751 pvalue = 0.0461051 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2583 sd = 0.0473 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+allele 2 : freq = 0.7417 sd = 0.0473 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2687 freq = 0.3187 freq = 0.0000 freq = 0.3063
+allele 2 : freq = 0.7312 freq = 0.6813 freq = 0.0000 freq = 0.6937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 501: rs501
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.309031 pvalue = 0.25257 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.711590 pvalue = 0.190779 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.103207 pvalue = 0.0238816 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6483 sd = 0.0516 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+allele 2 : freq = 0.3517 sd = 0.0516 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.5729 freq = 0.0000 freq = 0.5891
+allele 2 : freq = 0.3625 freq = 0.4271 freq = 0.0000 freq = 0.4109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 502: rs502
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.639075 pvalue = 0.104264 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.482000 pvalue = 0.0620397 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.523560 pvalue = 0.0605023 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4233 sd = 0.0534 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.5767 sd = 0.0534 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4188 freq = 0.5125 freq = 0.0000 freq = 0.4891
+allele 2 : freq = 0.5813 freq = 0.4875 freq = 0.0000 freq = 0.5109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 503: rs503
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.101791 pvalue = 0.749691 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.021811 pvalue = 0.882591 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.016933 pvalue = 0.896465 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.7625 freq = 0.0000 freq = 0.7609
+allele 2 : freq = 0.2437 freq = 0.2375 freq = 0.0000 freq = 0.2391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 504: rs504
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.012724 pvalue = 0.910189 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.611827 pvalue = 0.434101 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0383 sd = 0.0207 freq = 0.0346 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.0350 sd = 0.0130
+allele 2 : freq = 0.9617 sd = 0.0207 freq = 0.9654 sd = 0.0139 freq = 0.0000 sd = 0.0000 freq = 0.9650 sd = 0.0130
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0375 freq = 0.0375 freq = 0.0000 freq = 0.0375
+allele 2 : freq = 0.9625 freq = 0.9625 freq = 0.0000 freq = 0.9625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 505: rs505
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 8.432396 pvalue = 0.00368594 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 10.794479 pvalue = 0.00101803 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.851124 pvalue = 0.0497127 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4900 sd = 0.0540 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.5100 sd = 0.0540 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.6438 freq = 0.0000 freq = 0.6031
+allele 2 : freq = 0.5188 freq = 0.3563 freq = 0.0000 freq = 0.3969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 506: rs506
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.158649 pvalue = 0.141769 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.472002 pvalue = 0.22503 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.439577 pvalue = 0.507326 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7288 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2712 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7333 freq = 0.0000 freq = 0.7469
+allele 2 : freq = 0.2125 freq = 0.2667 freq = 0.0000 freq = 0.2531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 507: rs507
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.232641 pvalue = 0.629572 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.023283 pvalue = 0.878723 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.885757 pvalue = 0.34663 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2250 freq = 0.0000 freq = 0.2266
+allele 2 : freq = 0.7688 freq = 0.7750 freq = 0.0000 freq = 0.7734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 508: rs508
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.032592 pvalue = 0.856734 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.006884 pvalue = 0.933874 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.018790 pvalue = 0.89097 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5467 sd = 0.0538 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+allele 2 : freq = 0.4533 sd = 0.0538 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.5417 freq = 0.0000 freq = 0.5406
+allele 2 : freq = 0.4625 freq = 0.4583 freq = 0.0000 freq = 0.4594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 509: rs509
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.812637 pvalue = 0.367342 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.081331 pvalue = 0.775502 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.179811 pvalue = 0.671536 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7967 sd = 0.0435 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+allele 2 : freq = 0.2033 sd = 0.0435 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7750 freq = 0.0000 freq = 0.7781
+allele 2 : freq = 0.2125 freq = 0.2250 freq = 0.0000 freq = 0.2219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 510: rs510
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.984171 pvalue = 0.321171 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.395936 pvalue = 0.529195 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 2.431558 pvalue = 0.118915 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0550 sd = 0.0246 freq = 0.0712 sd = 0.0195 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186
+allele 2 : freq = 0.9450 sd = 0.0246 freq = 0.9288 sd = 0.0195 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0500 freq = 0.0667 freq = 0.0000 freq = 0.0625
+allele 2 : freq = 0.9500 freq = 0.9333 freq = 0.0000 freq = 0.9375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 511: rs511
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.014577 pvalue = 0.903902 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.064676 pvalue = 0.799253 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.101964 pvalue = 0.749486 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2167 sd = 0.0445 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+allele 2 : freq = 0.7833 sd = 0.0445 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2000 freq = 0.1896 freq = 0.0000 freq = 0.1922
+allele 2 : freq = 0.8000 freq = 0.8104 freq = 0.0000 freq = 0.8078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 512: rs512
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.483938 pvalue = 0.486644 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.153753 pvalue = 0.694974 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1983 sd = 0.0431 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8017 sd = 0.0431 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1792 freq = 0.0000 freq = 0.1812
+allele 2 : freq = 0.8125 freq = 0.8208 freq = 0.0000 freq = 0.8187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 513: rs513
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.027681 pvalue = 0.86786 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.490652 pvalue = 0.483636 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4667 sd = 0.0539 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+allele 2 : freq = 0.5333 sd = 0.0539 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4500 freq = 0.0000 freq = 0.4500
+allele 2 : freq = 0.5500 freq = 0.5500 freq = 0.0000 freq = 0.5500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 514: rs514
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.739698 pvalue = 0.053134 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.155589 pvalue = 0.0414973 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.006985 pvalue = 0.315626 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4917 sd = 0.0540 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+allele 2 : freq = 0.5083 sd = 0.0540 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.5708 freq = 0.0000 freq = 0.5453
+allele 2 : freq = 0.5312 freq = 0.4292 freq = 0.0000 freq = 0.4547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 515: rs515
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.650098 pvalue = 0.420078 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.081320 pvalue = 0.775517 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.024662 pvalue = 0.875212 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9667 sd = 0.0194 freq = 0.9481 sd = 0.0169 freq = 0.0000 sd = 0.0000 freq = 0.9500 sd = 0.0154
+allele 2 : freq = 0.0333 sd = 0.0194 freq = 0.0519 sd = 0.0169 freq = 0.0000 sd = 0.0000 freq = 0.0500 sd = 0.0154
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9688 freq = 0.9625 freq = 0.0000 freq = 0.9641
+allele 2 : freq = 0.0312 freq = 0.0375 freq = 0.0000 freq = 0.0359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 516: rs516
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.372719 pvalue = 0.123472 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.151907 pvalue = 0.28315 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.446398 pvalue = 0.229107 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2167 sd = 0.0445 freq = 0.2846 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+allele 2 : freq = 0.7833 sd = 0.0445 freq = 0.7154 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.2542 freq = 0.0000 freq = 0.2422
+allele 2 : freq = 0.7937 freq = 0.7458 freq = 0.0000 freq = 0.7578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 517: rs517
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.316755 pvalue = 0.573564 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.507058 pvalue = 0.476415 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.004519 pvalue = 0.946403 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8017 sd = 0.0431 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.1983 sd = 0.0431 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.7771 freq = 0.0000 freq = 0.7844
+allele 2 : freq = 0.1938 freq = 0.2229 freq = 0.0000 freq = 0.2156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 518: rs518
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.051726 pvalue = 0.820086 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.320923 pvalue = 0.127644 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0967 sd = 0.0319 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+allele 2 : freq = 0.9033 sd = 0.0319 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1062 freq = 0.1062 freq = 0.0000 freq = 0.1062
+allele 2 : freq = 0.8938 freq = 0.8938 freq = 0.0000 freq = 0.8938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 519: rs519
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.274654 pvalue = 0.600227 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.369763 pvalue = 0.543134 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.252313 pvalue = 0.615451 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.6396 freq = 0.0000 freq = 0.6469
+allele 2 : freq = 0.3312 freq = 0.3604 freq = 0.0000 freq = 0.3531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 520: rs520
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.224659 pvalue = 0.635513 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.551084 pvalue = 0.457875 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.052881 pvalue = 0.818124 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2850 sd = 0.0488 freq = 0.2731 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+allele 2 : freq = 0.7150 sd = 0.0488 freq = 0.7269 sd = 0.0338 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.2542 freq = 0.0000 freq = 0.2625
+allele 2 : freq = 0.7125 freq = 0.7458 freq = 0.0000 freq = 0.7375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 521: rs521
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.077220 pvalue = 0.781101 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.047482 pvalue = 0.827504 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.383408 pvalue = 0.535785 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3146 freq = 0.0000 freq = 0.3172
+allele 2 : freq = 0.6750 freq = 0.6854 freq = 0.0000 freq = 0.6828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 522: rs522
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.060073 pvalue = 0.80638 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.179090 pvalue = 0.277541 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.329552 pvalue = 0.565923 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1033 sd = 0.0329 freq = 0.1038 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202
+allele 2 : freq = 0.8967 sd = 0.0329 freq = 0.8962 sd = 0.0232 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0938 freq = 0.1250 freq = 0.0000 freq = 0.1172
+allele 2 : freq = 0.9062 freq = 0.8750 freq = 0.0000 freq = 0.8828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 523: rs523
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.047047 pvalue = 0.828284 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.973768 pvalue = 0.323742 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2683 sd = 0.0479 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+allele 2 : freq = 0.7317 sd = 0.0479 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2562 freq = 0.2562 freq = 0.0000 freq = 0.2562
+allele 2 : freq = 0.7438 freq = 0.7438 freq = 0.0000 freq = 0.7438
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 524: rs524
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.097131 pvalue = 0.7553 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002178 pvalue = 0.962781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.040178 pvalue = 0.841134 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2900 sd = 0.0490 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+allele 2 : freq = 0.7100 sd = 0.0490 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.2896 freq = 0.0000 freq = 0.2891
+allele 2 : freq = 0.7125 freq = 0.7104 freq = 0.0000 freq = 0.7109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 525: rs525
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.058021 pvalue = 0.0803395 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.033267 pvalue = 0.15389 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.666953 pvalue = 0.414116 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2117 sd = 0.0441 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+allele 2 : freq = 0.7883 sd = 0.0441 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.2500 freq = 0.0000 freq = 0.2344
+allele 2 : freq = 0.8125 freq = 0.7500 freq = 0.0000 freq = 0.7656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 526: rs526
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.863775 pvalue = 0.352684 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.850035 pvalue = 0.356542 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.479367 pvalue = 0.488709 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4650 sd = 0.0539 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+allele 2 : freq = 0.5350 sd = 0.0539 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4625 freq = 0.4167 freq = 0.0000 freq = 0.4281
+allele 2 : freq = 0.5375 freq = 0.5833 freq = 0.0000 freq = 0.5719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 527: rs527
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.820364 pvalue = 0.365074 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.269912 pvalue = 0.603391 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.029469 pvalue = 0.863702 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6983 sd = 0.0496 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3017 sd = 0.0496 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.6625 freq = 0.0000 freq = 0.6687
+allele 2 : freq = 0.3125 freq = 0.3375 freq = 0.0000 freq = 0.3312
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 528: rs528
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.164046 pvalue = 0.280628 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.242175 pvalue = 0.0394316 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 7.801450 pvalue = 0.00522043 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3900 sd = 0.0527 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341
+allele 2 : freq = 0.6100 sd = 0.0527 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3937 freq = 0.2938 freq = 0.0000 freq = 0.3187
+allele 2 : freq = 0.6062 freq = 0.7063 freq = 0.0000 freq = 0.6813
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 529: rs529
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.957250 pvalue = 0.327881 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.803283 pvalue = 0.370114 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3467 sd = 0.0514 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.6533 sd = 0.0514 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3500 freq = 0.3396 freq = 0.0000 freq = 0.3422
+allele 2 : freq = 0.6500 freq = 0.6604 freq = 0.0000 freq = 0.6578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 530: rs530
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.180061 pvalue = 0.277344 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.004615 pvalue = 0.156821 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.958217 pvalue = 0.0854421 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5125 freq = 0.5833 freq = 0.0000 freq = 0.5656
+allele 2 : freq = 0.4875 freq = 0.4167 freq = 0.0000 freq = 0.4344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 531: rs531
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.552487 pvalue = 0.457303 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.229778 pvalue = 0.135373 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.667806 pvalue = 0.413818 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2533 sd = 0.0470 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+allele 2 : freq = 0.7467 sd = 0.0470 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2562 freq = 0.3229 freq = 0.0000 freq = 0.3063
+allele 2 : freq = 0.7438 freq = 0.6771 freq = 0.0000 freq = 0.6937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 532: rs532
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.953974 pvalue = 0.32871 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.021486 pvalue = 0.883462 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.064600 pvalue = 0.150755 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1938 freq = 0.0000 freq = 0.1922
+allele 2 : freq = 0.8125 freq = 0.8063 freq = 0.0000 freq = 0.8078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 533: rs533
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.355257 pvalue = 0.124861 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.545929 pvalue = 0.0596917 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.188817 pvalue = 0.139016 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6150 sd = 0.0526 freq = 0.5519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.3850 sd = 0.0526 freq = 0.4481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.5312 freq = 0.0000 freq = 0.5547
+allele 2 : freq = 0.3750 freq = 0.4688 freq = 0.0000 freq = 0.4453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 534: rs534
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.018814 pvalue = 0.890902 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027567 pvalue = 0.86813 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.295888 pvalue = 0.254966 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4667 sd = 0.0539 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+allele 2 : freq = 0.5333 sd = 0.0539 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 freq = 0.4667 freq = 0.0000 freq = 0.4688
+allele 2 : freq = 0.5250 freq = 0.5333 freq = 0.0000 freq = 0.5312
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 535: rs535
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.011260 pvalue = 0.915493 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.055390 pvalue = 0.813936 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.296324 pvalue = 0.586196 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1450 sd = 0.0380 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8550 sd = 0.0380 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.1521 freq = 0.0000 freq = 0.1500
+allele 2 : freq = 0.8562 freq = 0.8479 freq = 0.0000 freq = 0.8500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 536: rs536
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.653553 pvalue = 0.418845 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.689949 pvalue = 0.406182 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.551533 pvalue = 0.457692 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2625 freq = 0.2271 freq = 0.0000 freq = 0.2359
+allele 2 : freq = 0.7375 freq = 0.7729 freq = 0.0000 freq = 0.7641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 537: rs537
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.191992 pvalue = 0.661264 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.250110 pvalue = 0.616998 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.002458 pvalue = 0.960462 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2133 sd = 0.0442 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+allele 2 : freq = 0.7867 sd = 0.0442 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.2271 freq = 0.0000 freq = 0.2219
+allele 2 : freq = 0.7937 freq = 0.7729 freq = 0.0000 freq = 0.7781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 538: rs538
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.536791 pvalue = 0.463766 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.076849 pvalue = 0.299404 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.009217 pvalue = 0.923515 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.5583 freq = 0.0000 freq = 0.5453
+allele 2 : freq = 0.4938 freq = 0.4417 freq = 0.0000 freq = 0.4547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 539: rs539
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.896624 pvalue = 0.343688 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.165570 pvalue = 0.684079 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.734648 pvalue = 0.391381 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7417 sd = 0.0473 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2583 sd = 0.0473 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7500 freq = 0.7667 freq = 0.0000 freq = 0.7625
+allele 2 : freq = 0.2500 freq = 0.2333 freq = 0.0000 freq = 0.2375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 540: rs540
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.065498 pvalue = 0.798007 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.016481 pvalue = 0.89785 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.719741 pvalue = 0.396229 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6300 sd = 0.0521 freq = 0.6404 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.3700 sd = 0.0521 freq = 0.3596 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.6312 freq = 0.0000 freq = 0.6328
+allele 2 : freq = 0.3625 freq = 0.3688 freq = 0.0000 freq = 0.3672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 541: rs541
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.352093 pvalue = 0.244913 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.514724 pvalue = 0.473101 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.343014 pvalue = 0.558095 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6467 sd = 0.0516 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+allele 2 : freq = 0.3533 sd = 0.0516 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 freq = 0.6146 freq = 0.0000 freq = 0.6234
+allele 2 : freq = 0.3500 freq = 0.3854 freq = 0.0000 freq = 0.3766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 542: rs542
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.013277 pvalue = 0.908267 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.084129 pvalue = 0.771777 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.586588 pvalue = 0.207814 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.4917 freq = 0.0000 freq = 0.4953
+allele 2 : freq = 0.4938 freq = 0.5083 freq = 0.0000 freq = 0.5047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 543: rs543
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.085399 pvalue = 0.77011 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.526459 pvalue = 0.468099 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.229912 pvalue = 0.631589 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1617 sd = 0.0398 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+allele 2 : freq = 0.8383 sd = 0.0398 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1625 freq = 0.1896 freq = 0.0000 freq = 0.1828
+allele 2 : freq = 0.8375 freq = 0.8104 freq = 0.0000 freq = 0.8172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 544: rs544
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.236650 pvalue = 0.134773 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.420181 pvalue = 0.119781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.968901 pvalue = 0.160565 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.4346 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.5654 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3563 freq = 0.4333 freq = 0.0000 freq = 0.4141
+allele 2 : freq = 0.6438 freq = 0.5667 freq = 0.0000 freq = 0.5859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 545: rs545
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000001 pvalue = 0.999228 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015527 pvalue = 0.900835 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.286489 pvalue = 0.592479 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5423 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4577 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.5437 freq = 0.0000 freq = 0.5422
+allele 2 : freq = 0.4625 freq = 0.4562 freq = 0.0000 freq = 0.4578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 546: rs546
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.156904 pvalue = 0.14193 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.395893 pvalue = 0.237412 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.017068 pvalue = 0.313216 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1833 sd = 0.0418 freq = 0.2423 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+allele 2 : freq = 0.8167 sd = 0.0418 freq = 0.7577 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.2250 freq = 0.0000 freq = 0.2125
+allele 2 : freq = 0.8250 freq = 0.7750 freq = 0.0000 freq = 0.7875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 547: rs547
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.037221 pvalue = 0.847016 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.006873 pvalue = 0.933927 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.893171 pvalue = 0.34462 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 sd = 0.0539 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+allele 2 : freq = 0.4750 sd = 0.0539 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.5208 freq = 0.0000 freq = 0.5219
+allele 2 : freq = 0.4750 freq = 0.4792 freq = 0.0000 freq = 0.4781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 548: rs548
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.129896 pvalue = 0.71854 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.313031 pvalue = 0.575826 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.678158 pvalue = 0.410222 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.8042 freq = 0.0000 freq = 0.7984
+allele 2 : freq = 0.2188 freq = 0.1958 freq = 0.0000 freq = 0.2016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 549: rs549
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000237 pvalue = 0.987725 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.041393 pvalue = 0.838782 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.734648 pvalue = 0.391381 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7683 sd = 0.0456 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2317 sd = 0.0456 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7792 freq = 0.0000 freq = 0.7812
+allele 2 : freq = 0.2125 freq = 0.2208 freq = 0.0000 freq = 0.2188
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 550: rs550
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.462130 pvalue = 0.226591 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.210532 pvalue = 0.271227 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.064317 pvalue = 0.0437984 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7500 sd = 0.0468 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+allele 2 : freq = 0.2500 sd = 0.0468 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7375 freq = 0.7833 freq = 0.0000 freq = 0.7719
+allele 2 : freq = 0.2625 freq = 0.2167 freq = 0.0000 freq = 0.2281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 551: rs551
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.469111 pvalue = 0.493396 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.266625 pvalue = 0.605605 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.365916 pvalue = 0.545239 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 sd = 0.0451 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+allele 2 : freq = 0.2250 sd = 0.0451 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7396 freq = 0.0000 freq = 0.7453
+allele 2 : freq = 0.2375 freq = 0.2604 freq = 0.0000 freq = 0.2547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 552: rs552
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.865190 pvalue = 0.090515 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.130537 pvalue = 0.14439 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.085439 pvalue = 0.770057 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7217 sd = 0.0484 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.2783 sd = 0.0484 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7438 freq = 0.6750 freq = 0.0000 freq = 0.6922
+allele 2 : freq = 0.2562 freq = 0.3250 freq = 0.0000 freq = 0.3078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 553: rs553
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.906849 pvalue = 0.167314 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.434755 pvalue = 0.118672 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.031842 pvalue = 0.154034 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7533 sd = 0.0466 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+allele 2 : freq = 0.2467 sd = 0.0466 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.6917 freq = 0.0000 freq = 0.7094
+allele 2 : freq = 0.2375 freq = 0.3083 freq = 0.0000 freq = 0.2906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 554: rs554
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.015743 pvalue = 0.900151 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.148328 pvalue = 0.700139 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.004998 pvalue = 0.943638 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3683 sd = 0.0521 freq = 0.3731 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+allele 2 : freq = 0.6317 sd = 0.0521 freq = 0.6269 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.3937 freq = 0.0000 freq = 0.3891
+allele 2 : freq = 0.6250 freq = 0.6062 freq = 0.0000 freq = 0.6109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 555: rs555
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.128953 pvalue = 0.71952 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003795 pvalue = 0.95088 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.324817 pvalue = 0.568727 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8633 sd = 0.0371 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238
+allele 2 : freq = 0.1367 sd = 0.0371 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8562 freq = 0.8583 freq = 0.0000 freq = 0.8578
+allele 2 : freq = 0.1437 freq = 0.1417 freq = 0.0000 freq = 0.1422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 556: rs556
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.459436 pvalue = 0.497887 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.178484 pvalue = 0.672679 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.106094 pvalue = 0.744636 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7200 sd = 0.0485 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+allele 2 : freq = 0.2800 sd = 0.0485 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7063 freq = 0.7250 freq = 0.0000 freq = 0.7203
+allele 2 : freq = 0.2938 freq = 0.2750 freq = 0.0000 freq = 0.2797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 557: rs557
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.247495 pvalue = 0.0715327 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.239542 pvalue = 0.0718807 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.389941 pvalue = 0.53233 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2383 sd = 0.0460 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+allele 2 : freq = 0.7617 sd = 0.0460 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.3208 freq = 0.0000 freq = 0.3000
+allele 2 : freq = 0.7625 freq = 0.6792 freq = 0.0000 freq = 0.7000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 558: rs558
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.774907 pvalue = 0.378703 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.877320 pvalue = 0.348937 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.143080 pvalue = 0.285003 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.6271 freq = 0.0000 freq = 0.6156
+allele 2 : freq = 0.4188 freq = 0.3729 freq = 0.0000 freq = 0.3844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 559: rs559
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.756849 pvalue = 0.185018 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.288668 pvalue = 0.130322 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.054417 pvalue = 0.815549 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2567 sd = 0.0472 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+allele 2 : freq = 0.7433 sd = 0.0472 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2562 freq = 0.1938 freq = 0.0000 freq = 0.2094
+allele 2 : freq = 0.7438 freq = 0.8063 freq = 0.0000 freq = 0.7906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 560: rs560
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.275311 pvalue = 0.258773 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.532036 pvalue = 0.215807 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.277075 pvalue = 0.131299 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6533 sd = 0.0514 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+allele 2 : freq = 0.3467 sd = 0.0514 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.6021 freq = 0.0000 freq = 0.6172
+allele 2 : freq = 0.3375 freq = 0.3979 freq = 0.0000 freq = 0.3828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 561: rs561
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.567488 pvalue = 0.451259 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.278875 pvalue = 0.597439 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.251871 pvalue = 0.133453 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8417 sd = 0.0394 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.1583 sd = 0.0394 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8167 freq = 0.0000 freq = 0.8219
+allele 2 : freq = 0.1625 freq = 0.1833 freq = 0.0000 freq = 0.1781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 562: rs562
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.154883 pvalue = 0.693912 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.112145 pvalue = 0.737715 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.517302 pvalue = 0.471995 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8150 sd = 0.0419 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1850 sd = 0.0419 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8125 freq = 0.8000 freq = 0.0000 freq = 0.8031
+allele 2 : freq = 0.1875 freq = 0.2000 freq = 0.0000 freq = 0.1969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 563: rs563
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.041434 pvalue = 0.307488 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.431328 pvalue = 0.511338 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.263091 pvalue = 0.608005 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1050 sd = 0.0331 freq = 0.1423 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8950 sd = 0.0331 freq = 0.8577 sd = 0.0265 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1062 freq = 0.1292 freq = 0.0000 freq = 0.1234
+allele 2 : freq = 0.8938 freq = 0.8708 freq = 0.0000 freq = 0.8766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 564: rs564
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.947658 pvalue = 0.330316 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.901084 pvalue = 0.167957 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.233031 pvalue = 0.0125389 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1833 sd = 0.0418 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.8167 sd = 0.0418 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1938 freq = 0.1417 freq = 0.0000 freq = 0.1547
+allele 2 : freq = 0.8063 freq = 0.8583 freq = 0.0000 freq = 0.8453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 565: rs565
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.759901 pvalue = 0.383359 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.565058 pvalue = 0.45223 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.042842 pvalue = 0.836024 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9033 sd = 0.0319 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+allele 2 : freq = 0.0967 sd = 0.0319 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9000 freq = 0.8750 freq = 0.0000 freq = 0.8812
+allele 2 : freq = 0.1000 freq = 0.1250 freq = 0.0000 freq = 0.1187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 566: rs566
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.918916 pvalue = 0.33776 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.346475 pvalue = 0.245895 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.744218 pvalue = 0.388313 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8200 sd = 0.0415 freq = 0.8596 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1800 sd = 0.0415 freq = 0.1404 sd = 0.0264 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.8667 freq = 0.0000 freq = 0.8562
+allele 2 : freq = 0.1750 freq = 0.1333 freq = 0.0000 freq = 0.1437
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 567: rs567
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.404207 pvalue = 0.524925 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.700907 pvalue = 0.402479 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.183910 pvalue = 0.276561 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8100 sd = 0.0424 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1900 sd = 0.0424 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.8500 freq = 0.0000 freq = 0.8422
+allele 2 : freq = 0.1812 freq = 0.1500 freq = 0.0000 freq = 0.1578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 568: rs568
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.899765 pvalue = 0.168105 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.869546 pvalue = 0.171527 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.217234 pvalue = 0.0400153 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5517 sd = 0.0537 freq = 0.4885 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.4483 sd = 0.0537 freq = 0.5115 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5563 freq = 0.4875 freq = 0.0000 freq = 0.5047
+allele 2 : freq = 0.4437 freq = 0.5125 freq = 0.0000 freq = 0.4953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 569: rs569
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.017902 pvalue = 0.893561 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001774 pvalue = 0.966402 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.564855 pvalue = 0.452311 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5567 sd = 0.0537 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4433 sd = 0.0537 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.5792 freq = 0.0000 freq = 0.5797
+allele 2 : freq = 0.4188 freq = 0.4208 freq = 0.0000 freq = 0.4203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 570: rs570
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.635900 pvalue = 0.104473 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.302353 pvalue = 0.253784 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.092759 pvalue = 0.760698 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3967 sd = 0.0528 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.6033 sd = 0.0528 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.3521 freq = 0.0000 freq = 0.3656
+allele 2 : freq = 0.5938 freq = 0.6479 freq = 0.0000 freq = 0.6344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 571: rs571
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.503332 pvalue = 0.113606 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.265446 pvalue = 0.260623 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.718208 pvalue = 0.396732 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7767 sd = 0.0450 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+allele 2 : freq = 0.2233 sd = 0.0450 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7104 freq = 0.0000 freq = 0.7234
+allele 2 : freq = 0.2375 freq = 0.2896 freq = 0.0000 freq = 0.2766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 572: rs572
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.529549 pvalue = 0.466796 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.098066 pvalue = 0.294691 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.897976 pvalue = 0.343325 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1917 sd = 0.0425 freq = 0.1654 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.8083 sd = 0.0425 freq = 0.8346 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1479 freq = 0.0000 freq = 0.1578
+allele 2 : freq = 0.8125 freq = 0.8521 freq = 0.0000 freq = 0.8422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 573: rs573
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.053207 pvalue = 0.817573 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015677 pvalue = 0.90036 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.341847 pvalue = 0.246708 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5350 sd = 0.0539 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+allele 2 : freq = 0.4650 sd = 0.0539 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.5375 freq = 0.0000 freq = 0.5391
+allele 2 : freq = 0.4562 freq = 0.4625 freq = 0.0000 freq = 0.4609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 574: rs574
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.207416 pvalue = 0.6488 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.569032 pvalue = 0.450644 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.234890 pvalue = 0.627921 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.4500 freq = 0.0000 freq = 0.4406
+allele 2 : freq = 0.5875 freq = 0.5500 freq = 0.0000 freq = 0.5594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 575: rs575
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.129706 pvalue = 0.718737 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002908 pvalue = 0.956996 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.002857 pvalue = 0.957371 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8417 sd = 0.0394 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.1583 sd = 0.0394 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8396 freq = 0.0000 freq = 0.8391
+allele 2 : freq = 0.1625 freq = 0.1604 freq = 0.0000 freq = 0.1609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 576: rs576
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.878117 pvalue = 0.348718 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.833781 pvalue = 0.361181 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.957594 pvalue = 0.0854751 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321
+allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.7167 freq = 0.0000 freq = 0.7063
+allele 2 : freq = 0.3250 freq = 0.2833 freq = 0.0000 freq = 0.2938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 577: rs577
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.258445 pvalue = 0.611191 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.950061 pvalue = 0.329704 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.530200 pvalue = 0.466523 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6083 sd = 0.0527 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.3917 sd = 0.0527 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5938 freq = 0.6417 freq = 0.0000 freq = 0.6297
+allele 2 : freq = 0.4062 freq = 0.3583 freq = 0.0000 freq = 0.3703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 578: rs578
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.779111 pvalue = 0.377413 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.492136 pvalue = 0.221885 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.564855 pvalue = 0.452311 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3800 sd = 0.0524 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+allele 2 : freq = 0.6200 sd = 0.0524 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3812 freq = 0.4417 freq = 0.0000 freq = 0.4266
+allele 2 : freq = 0.6188 freq = 0.5583 freq = 0.0000 freq = 0.5734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 579: rs579
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007574 pvalue = 0.930648 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.211298 pvalue = 0.645752 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.183219 pvalue = 0.668621 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.5917 freq = 0.0000 freq = 0.5859
+allele 2 : freq = 0.4313 freq = 0.4083 freq = 0.0000 freq = 0.4141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 580: rs580
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.279996 pvalue = 0.596704 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.284022 pvalue = 0.594077 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.307935 pvalue = 0.0212285 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3117 sd = 0.0500 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+allele 2 : freq = 0.6883 sd = 0.0500 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.3250 freq = 0.0000 freq = 0.3187
+allele 2 : freq = 0.7000 freq = 0.6750 freq = 0.0000 freq = 0.6813
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 581: rs581
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.413451 pvalue = 0.120297 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.054446 pvalue = 0.151762 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.272829 pvalue = 0.0216608 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5950 sd = 0.0530 freq = 0.6692 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.4050 sd = 0.0530 freq = 0.3308 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.6562 freq = 0.0000 freq = 0.6391
+allele 2 : freq = 0.4125 freq = 0.3438 freq = 0.0000 freq = 0.3609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 582: rs582
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.386093 pvalue = 0.53436 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.149992 pvalue = 0.698543 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003235 pvalue = 0.954645 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6017 sd = 0.0529 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340
+allele 2 : freq = 0.3983 sd = 0.0529 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.6250 freq = 0.0000 freq = 0.6203
+allele 2 : freq = 0.3937 freq = 0.3750 freq = 0.0000 freq = 0.3797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 583: rs583
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.124515 pvalue = 0.724188 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.286424 pvalue = 0.592521 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000217 pvalue = 0.988242 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6950 sd = 0.0497 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.3050 sd = 0.0497 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.7000 freq = 0.0000 freq = 0.6937
+allele 2 : freq = 0.3250 freq = 0.3000 freq = 0.0000 freq = 0.3063
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 584: rs584
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.231961 pvalue = 0.630073 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.228272 pvalue = 0.632808 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.3462 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.6538 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3688 freq = 0.3458 freq = 0.0000 freq = 0.3516
+allele 2 : freq = 0.6312 freq = 0.6542 freq = 0.0000 freq = 0.6484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 585: rs585
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.386180 pvalue = 0.122412 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.676519 pvalue = 0.195388 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.756767 pvalue = 0.384342 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5700 sd = 0.0535 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339
+allele 2 : freq = 0.4300 sd = 0.0535 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.6375 freq = 0.0000 freq = 0.6219
+allele 2 : freq = 0.4250 freq = 0.3625 freq = 0.0000 freq = 0.3781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 586: rs586
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.870077 pvalue = 0.350934 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.563187 pvalue = 0.211199 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.279620 pvalue = 0.596951 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8050 sd = 0.0428 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+allele 2 : freq = 0.1950 sd = 0.0428 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.7542 freq = 0.0000 freq = 0.7672
+allele 2 : freq = 0.1938 freq = 0.2458 freq = 0.0000 freq = 0.2328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 587: rs587
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.403729 pvalue = 0.52517 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.777114 pvalue = 0.378025 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.151624 pvalue = 0.28321 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2783 sd = 0.0484 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+allele 2 : freq = 0.7217 sd = 0.0484 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.2542 freq = 0.0000 freq = 0.2641
+allele 2 : freq = 0.7063 freq = 0.7458 freq = 0.0000 freq = 0.7359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 588: rs588
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.033735 pvalue = 0.854273 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.317845 pvalue = 0.572906 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.524811 pvalue = 0.468797 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8783 sd = 0.0353 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+allele 2 : freq = 0.1217 sd = 0.0353 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8750 freq = 0.8562 freq = 0.0000 freq = 0.8609
+allele 2 : freq = 0.1250 freq = 0.1437 freq = 0.0000 freq = 0.1391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 589: rs589
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.711910 pvalue = 0.39881 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.404622 pvalue = 0.524712 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.923189 pvalue = 0.336639 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9550 sd = 0.0224 freq = 0.9404 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.9450 sd = 0.0161
+allele 2 : freq = 0.0450 sd = 0.0224 freq = 0.0596 sd = 0.0180 freq = 0.0000 sd = 0.0000 freq = 0.0550 sd = 0.0161
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9625 freq = 0.9479 freq = 0.0000 freq = 0.9516
+allele 2 : freq = 0.0375 freq = 0.0521 freq = 0.0000 freq = 0.0484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 590: rs590
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.145439 pvalue = 0.702932 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027471 pvalue = 0.868359 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.270680 pvalue = 0.602876 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4583 sd = 0.0538 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.5417 sd = 0.0538 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.4604 freq = 0.0000 freq = 0.4625
+allele 2 : freq = 0.5312 freq = 0.5396 freq = 0.0000 freq = 0.5375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 591: rs591
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.522136 pvalue = 0.469932 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027869 pvalue = 0.867416 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.128556 pvalue = 0.719934 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6133 sd = 0.0526 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+allele 2 : freq = 0.3867 sd = 0.0526 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.5917 freq = 0.0000 freq = 0.5938
+allele 2 : freq = 0.4000 freq = 0.4083 freq = 0.0000 freq = 0.4062
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 592: rs592
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.054863 pvalue = 0.814807 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.269890 pvalue = 0.603405 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.442453 pvalue = 0.505941 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9000 sd = 0.0324 freq = 0.8885 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.1000 sd = 0.0324 freq = 0.1115 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8708 freq = 0.0000 freq = 0.8750
+allele 2 : freq = 0.1125 freq = 0.1292 freq = 0.0000 freq = 0.1250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 593: rs593
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.025694 pvalue = 0.872649 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002320 pvalue = 0.961582 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.559587 pvalue = 0.454427 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7417 sd = 0.0473 freq = 0.7654 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2583 sd = 0.0473 freq = 0.2346 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7604 freq = 0.0000 freq = 0.7609
+allele 2 : freq = 0.2375 freq = 0.2396 freq = 0.0000 freq = 0.2391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 594: rs594
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.069021 pvalue = 0.301167 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.633879 pvalue = 0.425936 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.131702 pvalue = 0.0234927 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7188 freq = 0.6813 freq = 0.0000 freq = 0.6906
+allele 2 : freq = 0.2812 freq = 0.3187 freq = 0.0000 freq = 0.3094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 595: rs595
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.646905 pvalue = 0.421222 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386889 pvalue = 0.533939 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.588972 pvalue = 0.207473 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4200 sd = 0.0533 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.5800 sd = 0.0533 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4437 freq = 0.4750 freq = 0.0000 freq = 0.4672
+allele 2 : freq = 0.5563 freq = 0.5250 freq = 0.0000 freq = 0.5328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 596: rs596
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.097922 pvalue = 0.754337 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015550 pvalue = 0.90076 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.950934 pvalue = 0.329482 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5350 sd = 0.0539 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4650 sd = 0.0539 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5188 freq = 0.5125 freq = 0.0000 freq = 0.5141
+allele 2 : freq = 0.4813 freq = 0.4875 freq = 0.0000 freq = 0.4859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 597: rs597
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.299914 pvalue = 0.583936 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.372258 pvalue = 0.541776 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.365783 pvalue = 0.545312 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 sd = 0.0506 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+allele 2 : freq = 0.6750 sd = 0.0506 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3542 freq = 0.0000 freq = 0.3469
+allele 2 : freq = 0.6750 freq = 0.6458 freq = 0.0000 freq = 0.6531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 598: rs598
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.026654 pvalue = 0.870312 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.251137 pvalue = 0.616276 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.385576 pvalue = 0.534634 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1150 sd = 0.0345 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+allele 2 : freq = 0.8850 sd = 0.0345 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1250 freq = 0.1417 freq = 0.0000 freq = 0.1375
+allele 2 : freq = 0.8750 freq = 0.8583 freq = 0.0000 freq = 0.8625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 599: rs599
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.554408 pvalue = 0.456522 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.254296 pvalue = 0.614066 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.199161 pvalue = 0.138086 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.7771 freq = 0.0000 freq = 0.7719
+allele 2 : freq = 0.2437 freq = 0.2229 freq = 0.0000 freq = 0.2281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 600: rs600
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.216549 pvalue = 0.641682 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.317306 pvalue = 0.573231 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.217147 pvalue = 0.136485 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7417 sd = 0.0473 freq = 0.7250 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+allele 2 : freq = 0.2583 sd = 0.0473 freq = 0.2750 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7500 freq = 0.7250 freq = 0.0000 freq = 0.7312
+allele 2 : freq = 0.2500 freq = 0.2750 freq = 0.0000 freq = 0.2687
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 601: rs601
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.361945 pvalue = 0.0667192 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.823796 pvalue = 0.176862 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.280789 pvalue = 0.596184 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4783 sd = 0.0540 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+allele 2 : freq = 0.5217 sd = 0.0540 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.4208 freq = 0.0000 freq = 0.4375
+allele 2 : freq = 0.5125 freq = 0.5792 freq = 0.0000 freq = 0.5625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 602: rs602
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 6.110609 pvalue = 0.0134373 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.079976 pvalue = 0.0433943 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.873119 pvalue = 0.0490653 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2817 sd = 0.0486 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+allele 2 : freq = 0.7183 sd = 0.0486 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.2062 freq = 0.0000 freq = 0.2266
+allele 2 : freq = 0.7125 freq = 0.7937 freq = 0.0000 freq = 0.7734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 603: rs603
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.103172 pvalue = 0.748056 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.732159 pvalue = 0.392184 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.2271 freq = 0.0000 freq = 0.2250
+allele 2 : freq = 0.7812 freq = 0.7729 freq = 0.0000 freq = 0.7750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 604: rs604
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.273839 pvalue = 0.259048 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.225137 pvalue = 0.135781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.060734 pvalue = 0.805339 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4650 sd = 0.0539 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.5350 sd = 0.0539 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.5312 freq = 0.0000 freq = 0.5125
+allele 2 : freq = 0.5437 freq = 0.4688 freq = 0.0000 freq = 0.4875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 605: rs605
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.683322 pvalue = 0.194484 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.648706 pvalue = 0.199135 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.921955 pvalue = 0.336962 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8700 sd = 0.0363 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.8950 sd = 0.0217
+allele 2 : freq = 0.1300 sd = 0.0363 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.1050 sd = 0.0217
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8625 freq = 0.9021 freq = 0.0000 freq = 0.8922
+allele 2 : freq = 0.1375 freq = 0.0979 freq = 0.0000 freq = 0.1078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 606: rs606
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.069914 pvalue = 0.15023 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.306542 pvalue = 0.0690046 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.362432 pvalue = 0.124288 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5500 freq = 0.6396 freq = 0.0000 freq = 0.6172
+allele 2 : freq = 0.4500 freq = 0.3604 freq = 0.0000 freq = 0.3828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 607: rs607
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000433 pvalue = 0.983393 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.193498 pvalue = 0.660021 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4633 sd = 0.0539 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+allele 2 : freq = 0.5367 sd = 0.0539 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.4562 freq = 0.0000 freq = 0.4562
+allele 2 : freq = 0.5437 freq = 0.5437 freq = 0.0000 freq = 0.5437
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 608: rs608
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.136730 pvalue = 0.0234247 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.492684 pvalue = 0.0616406 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.189284 pvalue = 0.663513 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4683 sd = 0.0539 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.5317 sd = 0.0539 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.3958 freq = 0.0000 freq = 0.4188
+allele 2 : freq = 0.5125 freq = 0.6042 freq = 0.0000 freq = 0.5813
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 609: rs609
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.890169 pvalue = 0.345432 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.996301 pvalue = 0.318207 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.179811 pvalue = 0.671536 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7233 sd = 0.0483 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+allele 2 : freq = 0.2767 sd = 0.0483 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.7562 freq = 0.0000 freq = 0.7453
+allele 2 : freq = 0.2875 freq = 0.2437 freq = 0.0000 freq = 0.2547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 610: rs610
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.871296 pvalue = 0.350597 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.638192 pvalue = 0.424366 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.293569 pvalue = 0.587942 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6033 sd = 0.0528 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+allele 2 : freq = 0.3967 sd = 0.0528 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.5854 freq = 0.0000 freq = 0.5953
+allele 2 : freq = 0.3750 freq = 0.4146 freq = 0.0000 freq = 0.4047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 611: rs611
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.221442 pvalue = 0.637943 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002543 pvalue = 0.959781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.009995 pvalue = 0.920364 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7646 freq = 0.0000 freq = 0.7641
+allele 2 : freq = 0.2375 freq = 0.2354 freq = 0.0000 freq = 0.2359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 612: rs612
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 7.067292 pvalue = 0.00785038 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 7.627688 pvalue = 0.0057479 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 7.800898 pvalue = 0.00522203 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3417 sd = 0.0512 freq = 0.4346 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+allele 2 : freq = 0.6583 sd = 0.0512 freq = 0.5654 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.4625 freq = 0.0000 freq = 0.4281
+allele 2 : freq = 0.6750 freq = 0.5375 freq = 0.0000 freq = 0.5719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 613: rs613
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.460772 pvalue = 0.497263 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.140882 pvalue = 0.285466 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.823619 pvalue = 0.364124 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8217 sd = 0.0413 freq = 0.7808 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.1783 sd = 0.0413 freq = 0.2192 sd = 0.0314 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.7625 freq = 0.0000 freq = 0.7734
+allele 2 : freq = 0.1938 freq = 0.2375 freq = 0.0000 freq = 0.2266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 614: rs614
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.640947 pvalue = 0.423368 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.282332 pvalue = 0.257466 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.248894 pvalue = 0.617855 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7950 sd = 0.0436 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.2050 sd = 0.0436 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 freq = 0.8438 freq = 0.0000 freq = 0.8328
+allele 2 : freq = 0.2000 freq = 0.1562 freq = 0.0000 freq = 0.1672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 615: rs615
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.061676 pvalue = 0.803866 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.107598 pvalue = 0.742896 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8200 sd = 0.0415 freq = 0.8192 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1800 sd = 0.0415 freq = 0.1808 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.8187 freq = 0.0000 freq = 0.8187
+allele 2 : freq = 0.1812 freq = 0.1812 freq = 0.0000 freq = 0.1812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 616: rs616
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.553986 pvalue = 0.456694 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.545590 pvalue = 0.213788 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.042186 pvalue = 0.837265 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1667 sd = 0.0403 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8333 sd = 0.0403 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.1292 freq = 0.0000 freq = 0.1406
+allele 2 : freq = 0.8250 freq = 0.8708 freq = 0.0000 freq = 0.8594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 617: rs617
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.102926 pvalue = 0.147018 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.632654 pvalue = 0.0566564 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.699030 pvalue = 0.100409 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.5458 freq = 0.0000 freq = 0.5219
+allele 2 : freq = 0.5500 freq = 0.4542 freq = 0.0000 freq = 0.4781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 618: rs618
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.659194 pvalue = 0.416845 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.337327 pvalue = 0.561376 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.568405 pvalue = 0.450894 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5533 sd = 0.0537 freq = 0.5231 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+allele 2 : freq = 0.4467 sd = 0.0537 freq = 0.4769 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5333 freq = 0.0000 freq = 0.5406
+allele 2 : freq = 0.4375 freq = 0.4667 freq = 0.0000 freq = 0.4594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 619: rs619
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.784122 pvalue = 0.181644 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.053386 pvalue = 0.304729 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001150 pvalue = 0.972947 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8317 sd = 0.0404 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+allele 2 : freq = 0.1683 sd = 0.0404 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8021 freq = 0.0000 freq = 0.8125
+allele 2 : freq = 0.1562 freq = 0.1979 freq = 0.0000 freq = 0.1875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 620: rs620
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.300589 pvalue = 0.129325 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.207748 pvalue = 0.648538 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.630586 pvalue = 0.42714 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5783 sd = 0.0533 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+allele 2 : freq = 0.4217 sd = 0.0533 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.5646 freq = 0.0000 freq = 0.5703
+allele 2 : freq = 0.4125 freq = 0.4354 freq = 0.0000 freq = 0.4297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 621: rs621
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.117262 pvalue = 0.732023 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.444872 pvalue = 0.50478 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.206614 pvalue = 0.649434 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5583 sd = 0.0536 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+allele 2 : freq = 0.4417 sd = 0.0536 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5625 freq = 0.5292 freq = 0.0000 freq = 0.5375
+allele 2 : freq = 0.4375 freq = 0.4708 freq = 0.0000 freq = 0.4625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 622: rs622
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.858202 pvalue = 0.354242 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.192277 pvalue = 0.661029 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.385576 pvalue = 0.534634 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9133 sd = 0.0304 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+allele 2 : freq = 0.0867 sd = 0.0304 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9062 freq = 0.8917 freq = 0.0000 freq = 0.8953
+allele 2 : freq = 0.0938 freq = 0.1083 freq = 0.0000 freq = 0.1047
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 623: rs623
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.843838 pvalue = 0.358302 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.454770 pvalue = 0.500079 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.198604 pvalue = 0.65585 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7083 sd = 0.0491 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2917 sd = 0.0491 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7188 freq = 0.7479 freq = 0.0000 freq = 0.7406
+allele 2 : freq = 0.2812 freq = 0.2521 freq = 0.0000 freq = 0.2594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 624: rs624
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.284936 pvalue = 0.593484 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.788950 pvalue = 0.374418 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.862482 pvalue = 0.172339 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7050 sd = 0.0493 freq = 0.6673 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+allele 2 : freq = 0.2950 sd = 0.0493 freq = 0.3327 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6521 freq = 0.0000 freq = 0.6625
+allele 2 : freq = 0.3063 freq = 0.3479 freq = 0.0000 freq = 0.3375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 625: rs625
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.023802 pvalue = 0.311619 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.581890 pvalue = 0.445572 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.503742 pvalue = 0.113576 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3400 sd = 0.0512 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6600 sd = 0.0512 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3500 freq = 0.3875 freq = 0.0000 freq = 0.3781
+allele 2 : freq = 0.6500 freq = 0.6125 freq = 0.0000 freq = 0.6219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 626: rs626
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.062478 pvalue = 0.802622 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.112161 pvalue = 0.737697 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.306140 pvalue = 0.580059 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2750 sd = 0.0482 freq = 0.2635 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7250 sd = 0.0482 freq = 0.7365 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2687 freq = 0.2833 freq = 0.0000 freq = 0.2797
+allele 2 : freq = 0.7312 freq = 0.7167 freq = 0.0000 freq = 0.7203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 627: rs627
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.064130 pvalue = 0.800084 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001989 pvalue = 0.964427 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.945958 pvalue = 0.33075 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3150 sd = 0.0502 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.6850 sd = 0.0502 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.2979 freq = 0.0000 freq = 0.2984
+allele 2 : freq = 0.7000 freq = 0.7021 freq = 0.0000 freq = 0.7016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 628: rs628
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.602546 pvalue = 0.437608 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.882903 pvalue = 0.347408 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.867545 pvalue = 0.351636 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1333 sd = 0.0367 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+allele 2 : freq = 0.8667 sd = 0.0367 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1437 freq = 0.1125 freq = 0.0000 freq = 0.1203
+allele 2 : freq = 0.8562 freq = 0.8875 freq = 0.0000 freq = 0.8797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 629: rs629
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.003727 pvalue = 0.951322 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.063427 pvalue = 0.801159 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.424916 pvalue = 0.514494 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.5938 freq = 0.0000 freq = 0.5906
+allele 2 : freq = 0.4188 freq = 0.4062 freq = 0.0000 freq = 0.4094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 630: rs630
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.072670 pvalue = 0.787488 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.199365 pvalue = 0.655234 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2125 freq = 0.0000 freq = 0.2172
+allele 2 : freq = 0.7688 freq = 0.7875 freq = 0.0000 freq = 0.7828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 631: rs631
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.046571 pvalue = 0.0246747 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.265996 pvalue = 0.0388824 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.509058 pvalue = 0.475547 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 sd = 0.0432 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+allele 2 : freq = 0.2000 sd = 0.0432 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.7271 freq = 0.0000 freq = 0.7500
+allele 2 : freq = 0.1812 freq = 0.2729 freq = 0.0000 freq = 0.2500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 632: rs632
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.902747 pvalue = 0.342046 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.051875 pvalue = 0.080644 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.368249 pvalue = 0.54396 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6817 sd = 0.0503 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+allele 2 : freq = 0.3183 sd = 0.0503 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.7500 freq = 0.0000 freq = 0.7297
+allele 2 : freq = 0.3312 freq = 0.2500 freq = 0.0000 freq = 0.2703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 633: rs633
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.283633 pvalue = 0.59433 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.180092 pvalue = 0.671294 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000401 pvalue = 0.984018 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8950 sd = 0.0331 freq = 0.8615 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.1050 sd = 0.0331 freq = 0.1385 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8812 freq = 0.8667 freq = 0.0000 freq = 0.8703
+allele 2 : freq = 0.1187 freq = 0.1333 freq = 0.0000 freq = 0.1297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 634: rs634
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.656944 pvalue = 0.198016 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.138553 pvalue = 0.285958 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.892811 pvalue = 0.344717 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3267 sd = 0.0507 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+allele 2 : freq = 0.6733 sd = 0.0507 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3771 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.6750 freq = 0.6229 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 635: rs635
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 7.926986 pvalue = 0.00487029 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 8.120998 pvalue = 0.00437555 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.761156 pvalue = 0.0965785 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6883 sd = 0.0500 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+allele 2 : freq = 0.3117 sd = 0.0500 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.5458 freq = 0.0000 freq = 0.5813
+allele 2 : freq = 0.3125 freq = 0.4542 freq = 0.0000 freq = 0.4188
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 636: rs636
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.266372 pvalue = 0.605776 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001751 pvalue = 0.966622 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.588252 pvalue = 0.0581894 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5900 sd = 0.0531 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.4100 sd = 0.0531 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.5979 freq = 0.0000 freq = 0.5984
+allele 2 : freq = 0.4000 freq = 0.4021 freq = 0.0000 freq = 0.4016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 637: rs637
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.402967 pvalue = 0.236227 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.128783 pvalue = 0.144555 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.350808 pvalue = 0.553656 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4867 sd = 0.0540 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5133 sd = 0.0540 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.4146 freq = 0.0000 freq = 0.4328
+allele 2 : freq = 0.5125 freq = 0.5854 freq = 0.0000 freq = 0.5672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 638: rs638
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.208182 pvalue = 0.648196 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.192277 pvalue = 0.661029 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.010710 pvalue = 0.917573 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0983 sd = 0.0322 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+allele 2 : freq = 0.9017 sd = 0.0322 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1125 freq = 0.1271 freq = 0.0000 freq = 0.1234
+allele 2 : freq = 0.8875 freq = 0.8729 freq = 0.0000 freq = 0.8766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 639: rs639
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.781639 pvalue = 0.0953505 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.051022 pvalue = 0.152104 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.130947 pvalue = 0.717452 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4767 sd = 0.0539 freq = 0.3962 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+allele 2 : freq = 0.5233 sd = 0.0539 freq = 0.6038 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.4104 freq = 0.0000 freq = 0.4281
+allele 2 : freq = 0.5188 freq = 0.5896 freq = 0.0000 freq = 0.5719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 640: rs640
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.137396 pvalue = 0.710884 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.288871 pvalue = 0.590945 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.094094 pvalue = 0.759035 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7733 sd = 0.0452 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+allele 2 : freq = 0.2267 sd = 0.0452 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 freq = 0.7521 freq = 0.0000 freq = 0.7578
+allele 2 : freq = 0.2250 freq = 0.2479 freq = 0.0000 freq = 0.2422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 641: rs641
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.974299 pvalue = 0.0461997 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.947033 pvalue = 0.0147421 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.718192 pvalue = 0.396737 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.4646 freq = 0.0000 freq = 0.4344
+allele 2 : freq = 0.6562 freq = 0.5354 freq = 0.0000 freq = 0.5656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 642: rs642
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.060945 pvalue = 0.805008 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.140193 pvalue = 0.708089 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.148147 pvalue = 0.700312 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.5563 freq = 0.0000 freq = 0.5516
+allele 2 : freq = 0.4625 freq = 0.4437 freq = 0.0000 freq = 0.4484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 643: rs643
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.037970 pvalue = 0.845503 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027493 pvalue = 0.868307 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.082732 pvalue = 0.773628 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.5083 freq = 0.0000 freq = 0.5062
+allele 2 : freq = 0.5000 freq = 0.4917 freq = 0.0000 freq = 0.4938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 644: rs644
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.091304 pvalue = 0.762526 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.345228 pvalue = 0.246114 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.266809 pvalue = 0.60548 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2317 sd = 0.0456 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+allele 2 : freq = 0.7683 sd = 0.0456 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.2667 freq = 0.0000 freq = 0.2547
+allele 2 : freq = 0.7812 freq = 0.7333 freq = 0.0000 freq = 0.7453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 645: rs645
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.415914 pvalue = 0.019954 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 7.935860 pvalue = 0.00484646 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.778786 pvalue = 0.182298 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6367 sd = 0.0519 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+allele 2 : freq = 0.3633 sd = 0.0519 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.5292 freq = 0.0000 freq = 0.5641
+allele 2 : freq = 0.3312 freq = 0.4708 freq = 0.0000 freq = 0.4359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 646: rs646
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.625272 pvalue = 0.202358 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.166235 pvalue = 0.280176 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.743629 pvalue = 0.388501 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6367 sd = 0.0519 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+allele 2 : freq = 0.3633 sd = 0.0519 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6438 freq = 0.6937 freq = 0.0000 freq = 0.6813
+allele 2 : freq = 0.3563 freq = 0.3063 freq = 0.0000 freq = 0.3187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 647: rs647
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.846730 pvalue = 0.174164 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.418890 pvalue = 0.517492 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003402 pvalue = 0.953491 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1800 sd = 0.0415 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8200 sd = 0.0415 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1938 freq = 0.1708 freq = 0.0000 freq = 0.1766
+allele 2 : freq = 0.8063 freq = 0.8292 freq = 0.0000 freq = 0.8234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 648: rs648
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.067379 pvalue = 0.795192 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.171951 pvalue = 0.678384 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.147183 pvalue = 0.701242 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5125 freq = 0.5333 freq = 0.0000 freq = 0.5281
+allele 2 : freq = 0.4875 freq = 0.4667 freq = 0.0000 freq = 0.4719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 649: rs649
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.174973 pvalue = 0.278382 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.952292 pvalue = 0.0857559 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.939560 pvalue = 0.332391 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3933 sd = 0.0528 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+allele 2 : freq = 0.6067 sd = 0.0528 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3937 freq = 0.4792 freq = 0.0000 freq = 0.4578
+allele 2 : freq = 0.6062 freq = 0.5208 freq = 0.0000 freq = 0.5422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 650: rs650
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.082382 pvalue = 0.774095 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.652905 pvalue = 0.419076 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.568292 pvalue = 0.450939 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2562 freq = 0.2208 freq = 0.0000 freq = 0.2297
+allele 2 : freq = 0.7438 freq = 0.7792 freq = 0.0000 freq = 0.7703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 651: rs651
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.100954 pvalue = 0.750688 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.757165 pvalue = 0.384217 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000750 pvalue = 0.978155 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5312 freq = 0.5750 freq = 0.0000 freq = 0.5641
+allele 2 : freq = 0.4688 freq = 0.4250 freq = 0.0000 freq = 0.4359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 652: rs652
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.062080 pvalue = 0.803238 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.474992 pvalue = 0.4907 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.085726 pvalue = 0.769683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.7979 freq = 0.0000 freq = 0.7906
+allele 2 : freq = 0.2313 freq = 0.2021 freq = 0.0000 freq = 0.2094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 653: rs653
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.003518 pvalue = 0.316461 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.213165 pvalue = 0.270706 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.128990 pvalue = 0.0421545 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7683 sd = 0.0456 freq = 0.6904 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+allele 2 : freq = 0.2317 sd = 0.0456 freq = 0.3096 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7500 freq = 0.7000 freq = 0.0000 freq = 0.7125
+allele 2 : freq = 0.2500 freq = 0.3000 freq = 0.0000 freq = 0.2875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 654: rs654
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.088050 pvalue = 0.766671 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.043269 pvalue = 0.835219 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.848256 pvalue = 0.357046 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5383 sd = 0.0538 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+allele 2 : freq = 0.4617 sd = 0.0538 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5312 freq = 0.5417 freq = 0.0000 freq = 0.5391
+allele 2 : freq = 0.4688 freq = 0.4583 freq = 0.0000 freq = 0.4609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 655: rs655
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.479960 pvalue = 0.48844 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.098984 pvalue = 0.753052 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.151972 pvalue = 0.696658 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0567 sd = 0.0250 freq = 0.0615 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186
+allele 2 : freq = 0.9433 sd = 0.0250 freq = 0.9385 sd = 0.0183 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0563 freq = 0.0646 freq = 0.0000 freq = 0.0625
+allele 2 : freq = 0.9437 freq = 0.9354 freq = 0.0000 freq = 0.9375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 656: rs656
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.418917 pvalue = 0.517478 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003924 pvalue = 0.950052 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.042842 pvalue = 0.836024 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1533 sd = 0.0389 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+allele 2 : freq = 0.8467 sd = 0.0389 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 freq = 0.1479 freq = 0.0000 freq = 0.1484
+allele 2 : freq = 0.8500 freq = 0.8521 freq = 0.0000 freq = 0.8516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 657: rs657
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.072679 pvalue = 0.300341 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.522676 pvalue = 0.11222 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.117145 pvalue = 0.732151 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9167 sd = 0.0299 freq = 0.8865 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212
+allele 2 : freq = 0.0833 sd = 0.0299 freq = 0.1135 sd = 0.0241 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9187 freq = 0.8708 freq = 0.0000 freq = 0.8828
+allele 2 : freq = 0.0813 freq = 0.1292 freq = 0.0000 freq = 0.1172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 658: rs658
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.221600 pvalue = 0.269047 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.004064 pvalue = 0.949168 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.454382 pvalue = 0.500261 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8450 sd = 0.0391 freq = 0.8692 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230
+allele 2 : freq = 0.1550 sd = 0.0391 freq = 0.1308 sd = 0.0256 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8396 freq = 0.0000 freq = 0.8391
+allele 2 : freq = 0.1625 freq = 0.1604 freq = 0.0000 freq = 0.1609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 659: rs659
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.072904 pvalue = 0.787154 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.160070 pvalue = 0.689092 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.078916 pvalue = 0.778772 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2083 sd = 0.0439 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+allele 2 : freq = 0.7917 sd = 0.0439 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2000 freq = 0.1833 freq = 0.0000 freq = 0.1875
+allele 2 : freq = 0.8000 freq = 0.8167 freq = 0.0000 freq = 0.8125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 660: rs660
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.629719 pvalue = 0.10488 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.640288 pvalue = 0.0563972 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.866079 pvalue = 0.352043 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.2788 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.7212 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3500 freq = 0.2625 freq = 0.0000 freq = 0.2844
+allele 2 : freq = 0.6500 freq = 0.7375 freq = 0.0000 freq = 0.7156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 661: rs661
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.561566 pvalue = 0.45363 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.457801 pvalue = 0.498653 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.078097 pvalue = 0.779893 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4154 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5846 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3688 freq = 0.4021 freq = 0.0000 freq = 0.3937
+allele 2 : freq = 0.6312 freq = 0.5979 freq = 0.0000 freq = 0.6062
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 662: rs662
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.127653 pvalue = 0.288277 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.139177 pvalue = 0.143579 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.289986 pvalue = 0.59023 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5817 sd = 0.0533 freq = 0.5538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+allele 2 : freq = 0.4183 sd = 0.0533 freq = 0.4462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.5271 freq = 0.0000 freq = 0.5453
+allele 2 : freq = 0.4000 freq = 0.4729 freq = 0.0000 freq = 0.4547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 663: rs663
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.055373 pvalue = 0.813965 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001717 pvalue = 0.966944 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.126755 pvalue = 0.72182 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5400 sd = 0.0538 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+allele 2 : freq = 0.4600 sd = 0.0538 freq = 0.5000 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.5271 freq = 0.0000 freq = 0.5266
+allele 2 : freq = 0.4750 freq = 0.4729 freq = 0.0000 freq = 0.4734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 664: rs664
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.301193 pvalue = 0.129275 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.098062 pvalue = 0.0783855 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.494588 pvalue = 0.0615697 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3688 freq = 0.4562 freq = 0.0000 freq = 0.4344
+allele 2 : freq = 0.6312 freq = 0.5437 freq = 0.0000 freq = 0.5656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 665: rs665
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.009262 pvalue = 0.923329 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001956 pvalue = 0.96472 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.021360 pvalue = 0.883803 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.6667 freq = 0.0000 freq = 0.6672
+allele 2 : freq = 0.3312 freq = 0.3333 freq = 0.0000 freq = 0.3328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 666: rs666
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.383920 pvalue = 0.535513 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.029990 pvalue = 0.862512 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.013097 pvalue = 0.908887 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6100 sd = 0.0527 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3900 sd = 0.0527 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6125 freq = 0.6208 freq = 0.0000 freq = 0.6188
+allele 2 : freq = 0.3875 freq = 0.3792 freq = 0.0000 freq = 0.3812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 667: rs667
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.261434 pvalue = 0.609137 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.029990 pvalue = 0.862512 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.452057 pvalue = 0.50136 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.6271 freq = 0.0000 freq = 0.6250
+allele 2 : freq = 0.3812 freq = 0.3729 freq = 0.0000 freq = 0.3750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 668: rs668
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.777304 pvalue = 0.377967 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.309252 pvalue = 0.25253 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.345885 pvalue = 0.556452 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.3827 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.6173 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.3688 freq = 0.0000 freq = 0.3828
+allele 2 : freq = 0.5750 freq = 0.6312 freq = 0.0000 freq = 0.6172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 669: rs669
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 7.283962 pvalue = 0.00695729 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 6.288114 pvalue = 0.012155 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.623934 pvalue = 0.0315288 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2033 sd = 0.0435 freq = 0.1288 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.7967 sd = 0.0435 freq = 0.8712 sd = 0.0254 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.1313 freq = 0.0000 freq = 0.1531
+allele 2 : freq = 0.7812 freq = 0.8688 freq = 0.0000 freq = 0.8469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 670: rs670
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.567990 pvalue = 0.0589036 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.756081 pvalue = 0.0291949 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.798416 pvalue = 0.371567 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0950 sd = 0.0317 freq = 0.0558 sd = 0.0174 freq = 0.0000 sd = 0.0000 freq = 0.0600 sd = 0.0168
+allele 2 : freq = 0.9050 sd = 0.0317 freq = 0.9442 sd = 0.0174 freq = 0.0000 sd = 0.0000 freq = 0.9400 sd = 0.0168
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0938 freq = 0.0417 freq = 0.0000 freq = 0.0547
+allele 2 : freq = 0.9062 freq = 0.9583 freq = 0.0000 freq = 0.9453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 671: rs671
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.885934 pvalue = 0.346582 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.156051 pvalue = 0.692818 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.659621 pvalue = 0.416694 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5933 sd = 0.0531 freq = 0.6750 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+allele 2 : freq = 0.4067 sd = 0.0531 freq = 0.3250 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.6375 freq = 0.0000 freq = 0.6328
+allele 2 : freq = 0.3812 freq = 0.3625 freq = 0.0000 freq = 0.3672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 672: rs672
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.482975 pvalue = 0.487078 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.938573 pvalue = 0.332645 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.069929 pvalue = 0.79144 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3875 freq = 0.4354 freq = 0.0000 freq = 0.4234
+allele 2 : freq = 0.6125 freq = 0.5646 freq = 0.0000 freq = 0.5766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 673: rs673
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.250755 pvalue = 0.263408 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.741638 pvalue = 0.389137 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.099964 pvalue = 0.751873 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.2562 freq = 0.0000 freq = 0.2656
+allele 2 : freq = 0.7063 freq = 0.7438 freq = 0.0000 freq = 0.7344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 674: rs674
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.131535 pvalue = 0.716846 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.113551 pvalue = 0.736137 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.409888 pvalue = 0.522026 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5667 sd = 0.0535 freq = 0.5846 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4333 sd = 0.0535 freq = 0.4154 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.5917 freq = 0.0000 freq = 0.5875
+allele 2 : freq = 0.4250 freq = 0.4083 freq = 0.0000 freq = 0.4125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 675: rs675
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.182281 pvalue = 0.66942 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.117968 pvalue = 0.731249 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.389605 pvalue = 0.532507 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8200 sd = 0.0415 freq = 0.8615 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+allele 2 : freq = 0.1800 sd = 0.0415 freq = 0.1385 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8313 freq = 0.8438 freq = 0.0000 freq = 0.8406
+allele 2 : freq = 0.1688 freq = 0.1562 freq = 0.0000 freq = 0.1594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 676: rs676
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.116459 pvalue = 0.290682 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.286853 pvalue = 0.256629 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.014011 pvalue = 0.905777 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 sd = 0.0386 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8500 sd = 0.0386 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1688 freq = 0.1292 freq = 0.0000 freq = 0.1391
+allele 2 : freq = 0.8313 freq = 0.8708 freq = 0.0000 freq = 0.8609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 677: rs677
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.441113 pvalue = 0.0635928 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.955797 pvalue = 0.161964 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.468454 pvalue = 0.0625497 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3125 freq = 0.3812 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.6875 freq = 0.6188 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 678: rs678
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 9.589246 pvalue = 0.0019572 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 9.314497 pvalue = 0.00227348 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.468119 pvalue = 0.0193665 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.3500 freq = 0.0000 freq = 0.3141
+allele 2 : freq = 0.7937 freq = 0.6500 freq = 0.0000 freq = 0.6859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 679: rs679
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.358969 pvalue = 0.54908 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.019160 pvalue = 0.889908 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.318198 pvalue = 0.572692 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7500 freq = 0.7438 freq = 0.0000 freq = 0.7453
+allele 2 : freq = 0.2500 freq = 0.2562 freq = 0.0000 freq = 0.2547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 680: rs680
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.150469 pvalue = 0.698088 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.417707 pvalue = 0.233781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.429953 pvalue = 0.512012 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7700 sd = 0.0455 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.2300 sd = 0.0455 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 freq = 0.8250 freq = 0.0000 freq = 0.8125
+allele 2 : freq = 0.2250 freq = 0.1750 freq = 0.0000 freq = 0.1875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 681: rs681
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.079865 pvalue = 0.298728 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.668624 pvalue = 0.413532 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.109048 pvalue = 0.74123 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.7000 freq = 0.0000 freq = 0.6906
+allele 2 : freq = 0.3375 freq = 0.3000 freq = 0.0000 freq = 0.3094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 682: rs682
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.261661 pvalue = 0.608981 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.757165 pvalue = 0.384217 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.414080 pvalue = 0.519906 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4933 sd = 0.0540 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.5067 sd = 0.0540 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.5250 freq = 0.0000 freq = 0.5141
+allele 2 : freq = 0.5188 freq = 0.4750 freq = 0.0000 freq = 0.4859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 683: rs683
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.016310 pvalue = 0.898379 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.341400 pvalue = 0.559022 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.037274 pvalue = 0.846909 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4437 freq = 0.4729 freq = 0.0000 freq = 0.4656
+allele 2 : freq = 0.5563 freq = 0.5271 freq = 0.0000 freq = 0.5344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 684: rs684
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.064575 pvalue = 0.799405 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.194671 pvalue = 0.659057 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.276561 pvalue = 0.258539 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8233 sd = 0.0412 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1767 sd = 0.0412 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.8417 freq = 0.0000 freq = 0.8375
+allele 2 : freq = 0.1750 freq = 0.1583 freq = 0.0000 freq = 0.1625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 685: rs685
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.002263 pvalue = 0.962055 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.074292 pvalue = 0.785188 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.065114 pvalue = 0.798589 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2850 sd = 0.0488 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+allele 2 : freq = 0.7150 sd = 0.0488 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.2750 freq = 0.0000 freq = 0.2781
+allele 2 : freq = 0.7125 freq = 0.7250 freq = 0.0000 freq = 0.7219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 686: rs686
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.126398 pvalue = 0.722197 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.862482 pvalue = 0.172339 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3050 sd = 0.0497 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+allele 2 : freq = 0.6950 sd = 0.0497 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.3000 freq = 0.0000 freq = 0.3000
+allele 2 : freq = 0.7000 freq = 0.7000 freq = 0.0000 freq = 0.7000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 687: rs687
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.009061 pvalue = 0.315128 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.053262 pvalue = 0.15188 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.099632 pvalue = 0.752272 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1383 sd = 0.0373 freq = 0.1346 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8617 sd = 0.0373 freq = 0.8654 sd = 0.0259 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1625 freq = 0.1125 freq = 0.0000 freq = 0.1250
+allele 2 : freq = 0.8375 freq = 0.8875 freq = 0.0000 freq = 0.8750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 688: rs688
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.806753 pvalue = 0.369082 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.830993 pvalue = 0.361986 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.609029 pvalue = 0.435153 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4767 sd = 0.0539 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+allele 2 : freq = 0.5233 sd = 0.0539 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.5146 freq = 0.0000 freq = 0.5031
+allele 2 : freq = 0.5312 freq = 0.4854 freq = 0.0000 freq = 0.4969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 689: rs689
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.094825 pvalue = 0.295405 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.030394 pvalue = 0.310066 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.808155 pvalue = 0.0510036 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6700 sd = 0.0508 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.3300 sd = 0.0508 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.7271 freq = 0.0000 freq = 0.7156
+allele 2 : freq = 0.3187 freq = 0.2729 freq = 0.0000 freq = 0.2844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 690: rs690
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.039548 pvalue = 0.842367 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.455949 pvalue = 0.499523 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000778 pvalue = 0.97775 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.4396 freq = 0.0000 freq = 0.4313
+allele 2 : freq = 0.5938 freq = 0.5604 freq = 0.0000 freq = 0.5687
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 691: rs691
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.018578 pvalue = 0.891584 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003924 pvalue = 0.950052 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.096394 pvalue = 0.756201 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1192 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8808 sd = 0.0246 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1187 freq = 0.1167 freq = 0.0000 freq = 0.1172
+allele 2 : freq = 0.8812 freq = 0.8833 freq = 0.0000 freq = 0.8828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 692: rs692
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.683933 pvalue = 0.101365 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.535042 pvalue = 0.111344 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.051756 pvalue = 0.820036 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6800 sd = 0.0504 freq = 0.6288 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340
+allele 2 : freq = 0.3200 sd = 0.0504 freq = 0.3712 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 freq = 0.6229 freq = 0.0000 freq = 0.6422
+allele 2 : freq = 0.3000 freq = 0.3771 freq = 0.0000 freq = 0.3578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 693: rs693
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.515076 pvalue = 0.218366 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.892899 pvalue = 0.344693 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.037358 pvalue = 0.846737 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3300 sd = 0.0508 freq = 0.3115 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+allele 2 : freq = 0.6700 sd = 0.0508 freq = 0.6885 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3563 freq = 0.3125 freq = 0.0000 freq = 0.3234
+allele 2 : freq = 0.6438 freq = 0.6875 freq = 0.0000 freq = 0.6766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 694: rs694
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.193904 pvalue = 0.274543 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.822243 pvalue = 0.177047 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.240729 pvalue = 0.62368 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7100 sd = 0.0490 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+allele 2 : freq = 0.2900 sd = 0.0490 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.6687 freq = 0.0000 freq = 0.6844
+allele 2 : freq = 0.2687 freq = 0.3312 freq = 0.0000 freq = 0.3156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 695: rs695
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.584777 pvalue = 0.107896 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.145068 pvalue = 0.143029 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000765 pvalue = 0.977938 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3850 sd = 0.0526 freq = 0.4269 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+allele 2 : freq = 0.6150 sd = 0.0526 freq = 0.5731 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.4354 freq = 0.0000 freq = 0.4172
+allele 2 : freq = 0.6375 freq = 0.5646 freq = 0.0000 freq = 0.5828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 696: rs696
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.325073 pvalue = 0.568575 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.008516 pvalue = 0.926475 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.182226 pvalue = 0.669467 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3267 sd = 0.0507 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+allele 2 : freq = 0.6733 sd = 0.0507 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3125 freq = 0.3167 freq = 0.0000 freq = 0.3156
+allele 2 : freq = 0.6875 freq = 0.6833 freq = 0.0000 freq = 0.6844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 697: rs697
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.082591 pvalue = 0.773816 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.139113 pvalue = 0.709165 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.126755 pvalue = 0.72182 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4833 sd = 0.0540 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.5167 sd = 0.0540 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.4813 freq = 0.0000 freq = 0.4859
+allele 2 : freq = 0.5000 freq = 0.5188 freq = 0.0000 freq = 0.5141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 698: rs698
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.003853 pvalue = 0.950505 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.042919 pvalue = 0.835878 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.885912 pvalue = 0.346588 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7950 sd = 0.0436 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+allele 2 : freq = 0.2050 sd = 0.0436 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7937 freq = 0.7854 freq = 0.0000 freq = 0.7875
+allele 2 : freq = 0.2062 freq = 0.2146 freq = 0.0000 freq = 0.2125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 699: rs699
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.773972 pvalue = 0.378991 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.625900 pvalue = 0.428863 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.586076 pvalue = 0.443941 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8300 sd = 0.0406 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+allele 2 : freq = 0.1700 sd = 0.0406 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8125 freq = 0.8417 freq = 0.0000 freq = 0.8344
+allele 2 : freq = 0.1875 freq = 0.1583 freq = 0.0000 freq = 0.1656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 700: rs700
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.046110 pvalue = 0.829975 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.275415 pvalue = 0.599722 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.501366 pvalue = 0.478901 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.3481 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.6519 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3625 freq = 0.0000 freq = 0.3563
+allele 2 : freq = 0.6625 freq = 0.6375 freq = 0.0000 freq = 0.6438
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 701: rs701
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.343641 pvalue = 0.246393 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.263162 pvalue = 0.132483 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.757073 pvalue = 0.18499 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4700 sd = 0.0539 freq = 0.4058 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5300 sd = 0.0539 freq = 0.5942 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 freq = 0.4000 freq = 0.0000 freq = 0.4188
+allele 2 : freq = 0.5250 freq = 0.6000 freq = 0.0000 freq = 0.5813
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 702: rs702
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.344033 pvalue = 0.246324 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.909432 pvalue = 0.0880629 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.510957 pvalue = 0.474725 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4300 sd = 0.0535 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+allele 2 : freq = 0.5700 sd = 0.0535 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4188 freq = 0.5042 freq = 0.0000 freq = 0.4828
+allele 2 : freq = 0.5813 freq = 0.4958 freq = 0.0000 freq = 0.5172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 703: rs703
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.084500 pvalue = 0.297693 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.616388 pvalue = 0.432393 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 1.608464 pvalue = 0.204708 df = 1
+
+The p-value might not be exact because of the small number of type 1 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0300 sd = 0.0184 freq = 0.0577 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.0600 sd = 0.0168
+allele 2 : freq = 0.9700 sd = 0.0184 freq = 0.9423 sd = 0.0177 freq = 0.0000 sd = 0.0000 freq = 0.9400 sd = 0.0168
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0375 freq = 0.0563 freq = 0.0000 freq = 0.0516
+allele 2 : freq = 0.9625 freq = 0.9437 freq = 0.0000 freq = 0.9484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 704: rs704
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.777159 pvalue = 0.378011 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.869817 pvalue = 0.351006 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001938 pvalue = 0.964886 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6867 sd = 0.0501 freq = 0.6788 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+allele 2 : freq = 0.3133 sd = 0.0501 freq = 0.3212 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.6687 freq = 0.0000 freq = 0.6797
+allele 2 : freq = 0.2875 freq = 0.3312 freq = 0.0000 freq = 0.3203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 705: rs705
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.093294 pvalue = 0.295743 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.666466 pvalue = 0.196733 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.503835 pvalue = 0.113569 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4217 sd = 0.0533 freq = 0.4481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5783 sd = 0.0533 freq = 0.5519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.4771 freq = 0.0000 freq = 0.4609
+allele 2 : freq = 0.5875 freq = 0.5229 freq = 0.0000 freq = 0.5391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 706: rs706
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.149105 pvalue = 0.0416565 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.680014 pvalue = 0.0305155 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.810254 pvalue = 0.0509397 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3700 sd = 0.0521 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+allele 2 : freq = 0.6300 sd = 0.0521 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.4833 freq = 0.0000 freq = 0.4562
+allele 2 : freq = 0.6250 freq = 0.5167 freq = 0.0000 freq = 0.5437
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 707: rs707
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.016829 pvalue = 0.896782 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.286424 pvalue = 0.592521 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.281442 pvalue = 0.595758 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7000 sd = 0.0495 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.3000 sd = 0.0495 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.7125 freq = 0.0000 freq = 0.7063
+allele 2 : freq = 0.3125 freq = 0.2875 freq = 0.0000 freq = 0.2938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 708: rs708
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.328663 pvalue = 0.127011 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.098021 pvalue = 0.14749 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 7.121219 pvalue = 0.00761769 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2633 sd = 0.0476 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.7367 sd = 0.0476 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2750 freq = 0.3438 freq = 0.0000 freq = 0.3266
+allele 2 : freq = 0.7250 freq = 0.6562 freq = 0.0000 freq = 0.6734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 709: rs709
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.537602 pvalue = 0.463428 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.124628 pvalue = 0.724068 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.024190 pvalue = 0.876403 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1250 sd = 0.0357 freq = 0.1365 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8750 sd = 0.0357 freq = 0.8635 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1187 freq = 0.1313 freq = 0.0000 freq = 0.1281
+allele 2 : freq = 0.8812 freq = 0.8688 freq = 0.0000 freq = 0.8719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 710: rs710
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.899779 pvalue = 0.342841 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.557120 pvalue = 0.455423 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.609944 pvalue = 0.434809 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.4827 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.5173 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4750 freq = 0.0000 freq = 0.4656
+allele 2 : freq = 0.5625 freq = 0.5250 freq = 0.0000 freq = 0.5344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 711: rs711
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.340534 pvalue = 0.559521 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.303661 pvalue = 0.253546 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.581463 pvalue = 0.20855 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5983 sd = 0.0530 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+allele 2 : freq = 0.4017 sd = 0.0530 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.6438 freq = 0.0000 freq = 0.6297
+allele 2 : freq = 0.4125 freq = 0.3563 freq = 0.0000 freq = 0.3703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 712: rs712
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 6.279555 pvalue = 0.0122139 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.259951 pvalue = 0.039021 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.386686 pvalue = 0.122373 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4850 sd = 0.0540 freq = 0.5865 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.5150 sd = 0.0540 freq = 0.4135 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.5833 freq = 0.0000 freq = 0.5578
+allele 2 : freq = 0.5188 freq = 0.4167 freq = 0.0000 freq = 0.4422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 713: rs713
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.317025 pvalue = 0.251127 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.029568 pvalue = 0.0817598 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.744218 pvalue = 0.388313 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8350 sd = 0.0401 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1650 sd = 0.0401 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.8875 freq = 0.0000 freq = 0.8719
+allele 2 : freq = 0.1750 freq = 0.1125 freq = 0.0000 freq = 0.1281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 714: rs714
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.078308 pvalue = 0.779604 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007071 pvalue = 0.932984 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.049411 pvalue = 0.824092 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.5958 freq = 0.0000 freq = 0.5969
+allele 2 : freq = 0.4000 freq = 0.4042 freq = 0.0000 freq = 0.4031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 715: rs715
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.860079 pvalue = 0.353717 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.293685 pvalue = 0.587869 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.011062 pvalue = 0.314648 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4000 freq = 0.4271 freq = 0.0000 freq = 0.4203
+allele 2 : freq = 0.6000 freq = 0.5729 freq = 0.0000 freq = 0.5797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 716: rs716
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.906676 pvalue = 0.167333 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.705277 pvalue = 0.0542407 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.187601 pvalue = 0.0407207 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5150 sd = 0.0540 freq = 0.5885 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.4850 sd = 0.0540 freq = 0.4115 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.6208 freq = 0.0000 freq = 0.5969
+allele 2 : freq = 0.4750 freq = 0.3792 freq = 0.0000 freq = 0.4031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 717: rs717
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.202762 pvalue = 0.073514 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.865447 pvalue = 0.171997 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.068666 pvalue = 0.793289 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.3417 freq = 0.0000 freq = 0.3578
+allele 2 : freq = 0.5938 freq = 0.6583 freq = 0.0000 freq = 0.6422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 718: rs718
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.138355 pvalue = 0.709921 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.484731 pvalue = 0.486287 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.450206 pvalue = 0.502237 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8433 sd = 0.0393 freq = 0.8635 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1567 sd = 0.0393 freq = 0.1365 sd = 0.0261 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8688 freq = 0.0000 freq = 0.8625
+allele 2 : freq = 0.1562 freq = 0.1313 freq = 0.0000 freq = 0.1375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 719: rs719
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.263614 pvalue = 0.607648 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386270 pvalue = 0.534267 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.042172 pvalue = 0.837292 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5067 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.4933 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.5125 freq = 0.0000 freq = 0.5047
+allele 2 : freq = 0.5188 freq = 0.4875 freq = 0.0000 freq = 0.4953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 720: rs720
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.042899 pvalue = 0.835916 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.162750 pvalue = 0.686637 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.359817 pvalue = 0.548608 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2167 sd = 0.0445 freq = 0.2096 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+allele 2 : freq = 0.7833 sd = 0.0445 freq = 0.7904 sd = 0.0309 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.2021 freq = 0.0000 freq = 0.2062
+allele 2 : freq = 0.7812 freq = 0.7979 freq = 0.0000 freq = 0.7937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 721: rs721
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.044494 pvalue = 0.832936 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.837580 pvalue = 0.36009 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.067185 pvalue = 0.795481 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6517 sd = 0.0515 freq = 0.6442 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+allele 2 : freq = 0.3483 sd = 0.0515 freq = 0.3558 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 freq = 0.6062 freq = 0.0000 freq = 0.6172
+allele 2 : freq = 0.3500 freq = 0.3937 freq = 0.0000 freq = 0.3828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 722: rs722
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.083269 pvalue = 0.297967 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.337700 pvalue = 0.56116 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.347815 pvalue = 0.555353 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4217 sd = 0.0533 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+allele 2 : freq = 0.5783 sd = 0.0533 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4188 freq = 0.4479 freq = 0.0000 freq = 0.4406
+allele 2 : freq = 0.5813 freq = 0.5521 freq = 0.0000 freq = 0.5594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 723: rs723
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.107503 pvalue = 0.0779323 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.100046 pvalue = 0.042882 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.718208 pvalue = 0.396732 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2283 sd = 0.0453 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3050 sd = 0.0326
+allele 2 : freq = 0.7717 sd = 0.0453 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6950 sd = 0.0326
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.3375 freq = 0.0000 freq = 0.3141
+allele 2 : freq = 0.7562 freq = 0.6625 freq = 0.0000 freq = 0.6859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 724: rs724
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.387265 pvalue = 0.53374 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.451461 pvalue = 0.501642 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.638796 pvalue = 0.424147 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2800 sd = 0.0485 freq = 0.3231 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+allele 2 : freq = 0.7200 sd = 0.0485 freq = 0.6769 sd = 0.0355 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.3187 freq = 0.0000 freq = 0.3109
+allele 2 : freq = 0.7125 freq = 0.6813 freq = 0.0000 freq = 0.6891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 725: rs725
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.608226 pvalue = 0.435456 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.427337 pvalue = 0.513299 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.261578 pvalue = 0.261353 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6900 sd = 0.0500 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+allele 2 : freq = 0.3100 sd = 0.0500 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.6562 freq = 0.0000 freq = 0.6641
+allele 2 : freq = 0.3125 freq = 0.3438 freq = 0.0000 freq = 0.3359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 726: rs726
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.130740 pvalue = 0.717666 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.035256 pvalue = 0.85106 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.858281 pvalue = 0.0909046 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6983 sd = 0.0496 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+allele 2 : freq = 0.3017 sd = 0.0496 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.7042 freq = 0.0000 freq = 0.7063
+allele 2 : freq = 0.2875 freq = 0.2958 freq = 0.0000 freq = 0.2938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 727: rs727
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.667214 pvalue = 0.414025 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.379219 pvalue = 0.538022 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.415175 pvalue = 0.519354 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1700 sd = 0.0406 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+allele 2 : freq = 0.8300 sd = 0.0406 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.2000 freq = 0.0000 freq = 0.1938
+allele 2 : freq = 0.8250 freq = 0.8000 freq = 0.0000 freq = 0.8063
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 728: rs728
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.386293 pvalue = 0.239032 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.173410 pvalue = 0.677099 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.211686 pvalue = 0.270999 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3875 freq = 0.4083 freq = 0.0000 freq = 0.4031
+allele 2 : freq = 0.6125 freq = 0.5917 freq = 0.0000 freq = 0.5969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 729: rs729
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.306741 pvalue = 0.579687 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.498513 pvalue = 0.480154 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.063876 pvalue = 0.800471 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8667 sd = 0.0367 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+allele 2 : freq = 0.1333 sd = 0.0367 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8438 freq = 0.0000 freq = 0.8500
+allele 2 : freq = 0.1313 freq = 0.1562 freq = 0.0000 freq = 0.1500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 730: rs730
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.771258 pvalue = 0.0521404 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.884570 pvalue = 0.0487318 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.369415 pvalue = 0.123733 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2600 sd = 0.0474 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3100 sd = 0.0327
+allele 2 : freq = 0.7400 sd = 0.0474 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6900 sd = 0.0327
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.3292 freq = 0.0000 freq = 0.3063
+allele 2 : freq = 0.7625 freq = 0.6708 freq = 0.0000 freq = 0.6937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 731: rs731
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.658782 pvalue = 0.41699 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.393992 pvalue = 0.530208 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.422316 pvalue = 0.515784 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6100 sd = 0.0527 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350
+allele 2 : freq = 0.3900 sd = 0.0527 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.5750 freq = 0.0000 freq = 0.5828
+allele 2 : freq = 0.3937 freq = 0.4250 freq = 0.0000 freq = 0.4172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 732: rs732
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.753348 pvalue = 0.385418 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.541699 pvalue = 0.461729 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.222856 pvalue = 0.636872 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.6458 freq = 0.0000 freq = 0.6547
+allele 2 : freq = 0.3187 freq = 0.3542 freq = 0.0000 freq = 0.3453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 733: rs733
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.524176 pvalue = 0.469066 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.066607 pvalue = 0.301713 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.007278 pvalue = 0.932013 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3767 sd = 0.0523 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3650 sd = 0.0340
+allele 2 : freq = 0.6233 sd = 0.0523 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6350 sd = 0.0340
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3875 freq = 0.3375 freq = 0.0000 freq = 0.3500
+allele 2 : freq = 0.6125 freq = 0.6625 freq = 0.0000 freq = 0.6500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 734: rs734
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.002881 pvalue = 0.957191 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.297817 pvalue = 0.585254 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.241849 pvalue = 0.622874 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2067 sd = 0.0437 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+allele 2 : freq = 0.7933 sd = 0.0437 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2542 freq = 0.0000 freq = 0.2484
+allele 2 : freq = 0.7688 freq = 0.7458 freq = 0.0000 freq = 0.7516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 735: rs735
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.658119 pvalue = 0.197857 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.381579 pvalue = 0.239832 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.089254 pvalue = 0.765128 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.6923 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.3077 sd = 0.0351 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 freq = 0.7042 freq = 0.0000 freq = 0.6906
+allele 2 : freq = 0.3500 freq = 0.2958 freq = 0.0000 freq = 0.3094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 736: rs736
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.735483 pvalue = 0.0532683 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.201480 pvalue = 0.137878 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 1.833450 pvalue = 0.175721 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9550 sd = 0.0224 freq = 0.9058 sd = 0.0222 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207
+allele 2 : freq = 0.0450 sd = 0.0224 freq = 0.0942 sd = 0.0222 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9563 freq = 0.9125 freq = 0.0000 freq = 0.9234
+allele 2 : freq = 0.0437 freq = 0.0875 freq = 0.0000 freq = 0.0766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 737: rs737
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.150927 pvalue = 0.697651 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002461 pvalue = 0.960432 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.107488 pvalue = 0.743022 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2417 sd = 0.0462 freq = 0.2288 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+allele 2 : freq = 0.7583 sd = 0.0462 freq = 0.7712 sd = 0.0319 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2417 freq = 0.0000 freq = 0.2422
+allele 2 : freq = 0.7562 freq = 0.7583 freq = 0.0000 freq = 0.7578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 738: rs738
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.239406 pvalue = 0.624636 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.009281 pvalue = 0.923252 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.541208 pvalue = 0.214438 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7517 sd = 0.0467 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2483 sd = 0.0467 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.7354 freq = 0.0000 freq = 0.7344
+allele 2 : freq = 0.2687 freq = 0.2646 freq = 0.0000 freq = 0.2656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 739: rs739
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.035947 pvalue = 0.849625 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.009694 pvalue = 0.92157 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.568729 pvalue = 0.210392 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7833 sd = 0.0445 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.2167 sd = 0.0445 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7854 freq = 0.0000 freq = 0.7844
+allele 2 : freq = 0.2188 freq = 0.2146 freq = 0.0000 freq = 0.2156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 740: rs740
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.604097 pvalue = 0.205324 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.261241 pvalue = 0.132648 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.332940 pvalue = 0.563933 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 freq = 0.7354 freq = 0.0000 freq = 0.7516
+allele 2 : freq = 0.2000 freq = 0.2646 freq = 0.0000 freq = 0.2484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 741: rs741
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.529674 pvalue = 0.0602796 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.403195 pvalue = 0.0200999 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.575035 pvalue = 0.108562 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5283 sd = 0.0539 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353
+allele 2 : freq = 0.4717 sd = 0.0539 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.4208 freq = 0.0000 freq = 0.4500
+allele 2 : freq = 0.4625 freq = 0.5792 freq = 0.0000 freq = 0.5500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 742: rs742
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.057215 pvalue = 0.810953 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.045102 pvalue = 0.831817 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.015954 pvalue = 0.899487 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3983 sd = 0.0529 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.6017 sd = 0.0529 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4000 freq = 0.3896 freq = 0.0000 freq = 0.3922
+allele 2 : freq = 0.6000 freq = 0.6104 freq = 0.0000 freq = 0.6078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 743: rs743
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.298788 pvalue = 0.584643 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.507562 pvalue = 0.476196 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.240523 pvalue = 0.0718377 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4083 sd = 0.0531 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+allele 2 : freq = 0.5917 sd = 0.0531 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.4417 freq = 0.0000 freq = 0.4328
+allele 2 : freq = 0.5938 freq = 0.5583 freq = 0.0000 freq = 0.5672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 744: rs744
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.017620 pvalue = 0.894398 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.001746 pvalue = 0.966667 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.403425 pvalue = 0.525326 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4437 freq = 0.4458 freq = 0.0000 freq = 0.4453
+allele 2 : freq = 0.5563 freq = 0.5542 freq = 0.0000 freq = 0.5547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 745: rs745
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.191229 pvalue = 0.275082 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.330570 pvalue = 0.248704 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.112497 pvalue = 0.737319 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6867 sd = 0.0501 freq = 0.7231 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.3133 sd = 0.0501 freq = 0.2769 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.7333 freq = 0.0000 freq = 0.7203
+allele 2 : freq = 0.3187 freq = 0.2667 freq = 0.0000 freq = 0.2797
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 746: rs746
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.349078 pvalue = 0.554636 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.871230 pvalue = 0.171334 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006754 pvalue = 0.934503 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5365 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4635 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.5750 freq = 0.0000 freq = 0.5578
+allele 2 : freq = 0.4938 freq = 0.4250 freq = 0.0000 freq = 0.4422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 747: rs747
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.005619 pvalue = 0.940249 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003193 pvalue = 0.954936 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.906831 pvalue = 0.340957 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8350 sd = 0.0401 freq = 0.8365 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+allele 2 : freq = 0.1650 sd = 0.0401 freq = 0.1635 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8396 freq = 0.0000 freq = 0.8391
+allele 2 : freq = 0.1625 freq = 0.1604 freq = 0.0000 freq = 0.1609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 748: rs748
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.750680 pvalue = 0.386261 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.799376 pvalue = 0.37128 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000198 pvalue = 0.988776 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4383 sd = 0.0536 freq = 0.3692 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+allele 2 : freq = 0.5617 sd = 0.0536 freq = 0.6308 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4188 freq = 0.3750 freq = 0.0000 freq = 0.3859
+allele 2 : freq = 0.5813 freq = 0.6250 freq = 0.0000 freq = 0.6141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 749: rs749
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.024915 pvalue = 0.87458 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027537 pvalue = 0.868202 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.018790 pvalue = 0.89097 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.4771 freq = 0.0000 freq = 0.4750
+allele 2 : freq = 0.5312 freq = 0.5229 freq = 0.0000 freq = 0.5250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 750: rs750
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.017099 pvalue = 0.0823907 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.310977 pvalue = 0.252218 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.073026 pvalue = 0.786981 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1117 sd = 0.0340 freq = 0.1846 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+allele 2 : freq = 0.8883 sd = 0.0340 freq = 0.8154 sd = 0.0295 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1125 freq = 0.1562 freq = 0.0000 freq = 0.1453
+allele 2 : freq = 0.8875 freq = 0.8438 freq = 0.0000 freq = 0.8547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 751: rs751
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.556124 pvalue = 0.455826 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.109305 pvalue = 0.740937 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.515342 pvalue = 0.472835 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2833 sd = 0.0487 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310
+allele 2 : freq = 0.7167 sd = 0.0487 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2938 freq = 0.2792 freq = 0.0000 freq = 0.2828
+allele 2 : freq = 0.7063 freq = 0.7208 freq = 0.0000 freq = 0.7172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 752: rs752
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.536034 pvalue = 0.464081 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.785443 pvalue = 0.375481 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.482962 pvalue = 0.115085 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4313 freq = 0.3875 freq = 0.0000 freq = 0.3984
+allele 2 : freq = 0.5687 freq = 0.6125 freq = 0.0000 freq = 0.6016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 753: rs753
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.032450 pvalue = 0.857044 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.205980 pvalue = 0.649937 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.721118 pvalue = 0.0990286 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2500 freq = 0.0000 freq = 0.2453
+allele 2 : freq = 0.7688 freq = 0.7500 freq = 0.0000 freq = 0.7547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 754: rs754
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.405712 pvalue = 0.120893 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.088648 pvalue = 0.296771 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.554539 pvalue = 0.456469 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.5731 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.4269 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4875 freq = 0.5396 freq = 0.0000 freq = 0.5266
+allele 2 : freq = 0.5125 freq = 0.4604 freq = 0.0000 freq = 0.4734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 755: rs755
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.500347 pvalue = 0.220618 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.852740 pvalue = 0.355778 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001731 pvalue = 0.966811 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5367 sd = 0.0539 freq = 0.5904 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+allele 2 : freq = 0.4633 sd = 0.0539 freq = 0.4096 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5250 freq = 0.5708 freq = 0.0000 freq = 0.5594
+allele 2 : freq = 0.4750 freq = 0.4292 freq = 0.0000 freq = 0.4406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 756: rs756
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.657564 pvalue = 0.417421 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.774516 pvalue = 0.378824 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.761156 pvalue = 0.0965785 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6267 sd = 0.0522 freq = 0.5596 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+allele 2 : freq = 0.3733 sd = 0.0522 freq = 0.4404 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.5625 freq = 0.0000 freq = 0.5734
+allele 2 : freq = 0.3937 freq = 0.4375 freq = 0.0000 freq = 0.4266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 757: rs757
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.356775 pvalue = 0.244097 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.649967 pvalue = 0.198963 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.277558 pvalue = 0.0122276 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4583 sd = 0.0538 freq = 0.5154 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.5417 sd = 0.0538 freq = 0.4846 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.5146 freq = 0.0000 freq = 0.4984
+allele 2 : freq = 0.5500 freq = 0.4854 freq = 0.0000 freq = 0.5016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 758: rs758
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.054166 pvalue = 0.815967 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.046860 pvalue = 0.82862 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.010028 pvalue = 0.920235 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3271 freq = 0.0000 freq = 0.3297
+allele 2 : freq = 0.6625 freq = 0.6729 freq = 0.0000 freq = 0.6703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 759: rs759
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.643565 pvalue = 0.422423 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.445910 pvalue = 0.504283 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.109539 pvalue = 0.74067 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4817 sd = 0.0540 freq = 0.4308 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351
+allele 2 : freq = 0.5183 sd = 0.0540 freq = 0.5692 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 freq = 0.4417 freq = 0.0000 freq = 0.4500
+allele 2 : freq = 0.5250 freq = 0.5583 freq = 0.0000 freq = 0.5500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 760: rs760
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.095596 pvalue = 0.75718 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003366 pvalue = 0.953734 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.450206 pvalue = 0.502237 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1417 sd = 0.0377 freq = 0.1635 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+allele 2 : freq = 0.8583 sd = 0.0377 freq = 0.8365 sd = 0.0281 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1375 freq = 0.1396 freq = 0.0000 freq = 0.1391
+allele 2 : freq = 0.8625 freq = 0.8604 freq = 0.0000 freq = 0.8609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 761: rs761
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.181757 pvalue = 0.669867 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.042135 pvalue = 0.837362 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.807636 pvalue = 0.36882 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2000 sd = 0.0432 freq = 0.1923 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+allele 2 : freq = 0.8000 sd = 0.0432 freq = 0.8077 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1958 freq = 0.0000 freq = 0.1938
+allele 2 : freq = 0.8125 freq = 0.8042 freq = 0.0000 freq = 0.8063
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 762: rs762
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.140082 pvalue = 0.708199 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.171495 pvalue = 0.279094 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.066304 pvalue = 0.796796 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6583 sd = 0.0512 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3417 sd = 0.0512 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6438 freq = 0.6958 freq = 0.0000 freq = 0.6828
+allele 2 : freq = 0.3563 freq = 0.3042 freq = 0.0000 freq = 0.3172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 763: rs763
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.315494 pvalue = 0.574328 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386842 pvalue = 0.533964 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.006248 pvalue = 0.936999 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7300 sd = 0.0480 freq = 0.7673 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+allele 2 : freq = 0.2700 sd = 0.0480 freq = 0.2327 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.7583 freq = 0.0000 freq = 0.7516
+allele 2 : freq = 0.2687 freq = 0.2417 freq = 0.0000 freq = 0.2484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 764: rs764
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.431557 pvalue = 0.511226 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.765042 pvalue = 0.381755 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.007517 pvalue = 0.930908 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6683 sd = 0.0509 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+allele 2 : freq = 0.3317 sd = 0.0509 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.6396 freq = 0.0000 freq = 0.6500
+allele 2 : freq = 0.3187 freq = 0.3604 freq = 0.0000 freq = 0.3500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 765: rs765
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.123442 pvalue = 0.72533 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.607253 pvalue = 0.435824 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.602685 pvalue = 0.205523 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1333 sd = 0.0367 freq = 0.0962 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+allele 2 : freq = 0.8667 sd = 0.0367 freq = 0.9038 sd = 0.0224 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1187 freq = 0.0938 freq = 0.0000 freq = 0.1000
+allele 2 : freq = 0.8812 freq = 0.9062 freq = 0.0000 freq = 0.9000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 766: rs766
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.025777 pvalue = 0.872447 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.042923 pvalue = 0.83587 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.988671 pvalue = 0.15848 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 sd = 0.0539 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.5250 sd = 0.0539 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4813 freq = 0.4708 freq = 0.0000 freq = 0.4734
+allele 2 : freq = 0.5188 freq = 0.5292 freq = 0.0000 freq = 0.5266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 767: rs767
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.707209 pvalue = 0.191348 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.409481 pvalue = 0.120602 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.612856 pvalue = 0.0317331 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2833 sd = 0.0487 freq = 0.2231 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+allele 2 : freq = 0.7167 sd = 0.0487 freq = 0.7769 sd = 0.0316 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2812 freq = 0.2146 freq = 0.0000 freq = 0.2313
+allele 2 : freq = 0.7188 freq = 0.7854 freq = 0.0000 freq = 0.7688
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 768: rs768
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000217 pvalue = 0.988249 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002044 pvalue = 0.963942 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.139459 pvalue = 0.70882 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3017 sd = 0.0496 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.6983 sd = 0.0496 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 freq = 0.2979 freq = 0.0000 freq = 0.2984
+allele 2 : freq = 0.7000 freq = 0.7021 freq = 0.0000 freq = 0.7016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 769: rs769
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.447075 pvalue = 0.503727 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.528296 pvalue = 0.467324 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.230714 pvalue = 0.630995 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6833 sd = 0.0502 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.3167 sd = 0.0502 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6813 freq = 0.7146 freq = 0.0000 freq = 0.7063
+allele 2 : freq = 0.3187 freq = 0.2854 freq = 0.0000 freq = 0.2938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 770: rs770
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.333290 pvalue = 0.563728 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.247832 pvalue = 0.618606 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.380502 pvalue = 0.537335 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5633 sd = 0.0536 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5250 sd = 0.0353
+allele 2 : freq = 0.4367 sd = 0.0536 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4750 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5500 freq = 0.5250 freq = 0.0000 freq = 0.5312
+allele 2 : freq = 0.4500 freq = 0.4750 freq = 0.0000 freq = 0.4688
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 771: rs771
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.302631 pvalue = 0.582238 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.297817 pvalue = 0.585254 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.544159 pvalue = 0.460714 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.7792 freq = 0.0000 freq = 0.7734
+allele 2 : freq = 0.2437 freq = 0.2208 freq = 0.0000 freq = 0.2266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 772: rs772
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.004086 pvalue = 0.949035 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.288740 pvalue = 0.591029 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.076281 pvalue = 0.782402 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1733 sd = 0.0409 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8267 sd = 0.0409 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 freq = 0.1688 freq = 0.0000 freq = 0.1641
+allele 2 : freq = 0.8500 freq = 0.8313 freq = 0.0000 freq = 0.8359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 773: rs773
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.485482 pvalue = 0.019175 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.729815 pvalue = 0.0534493 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.978603 pvalue = 0.0843721 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7617 sd = 0.0460 freq = 0.6500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+allele 2 : freq = 0.2383 sd = 0.0460 freq = 0.3500 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.6708 freq = 0.0000 freq = 0.6937
+allele 2 : freq = 0.2375 freq = 0.3292 freq = 0.0000 freq = 0.3063
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 774: rs774
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.668886 pvalue = 0.196408 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.209988 pvalue = 0.13712 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.165648 pvalue = 0.684009 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4183 sd = 0.0533 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.5817 sd = 0.0533 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.3646 freq = 0.0000 freq = 0.3828
+allele 2 : freq = 0.5625 freq = 0.6354 freq = 0.0000 freq = 0.6172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 775: rs775
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.564539 pvalue = 0.211002 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.369430 pvalue = 0.123732 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.858824 pvalue = 0.0908739 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4967 sd = 0.0540 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352
+allele 2 : freq = 0.5033 sd = 0.0540 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.5771 freq = 0.0000 freq = 0.5578
+allele 2 : freq = 0.5000 freq = 0.4229 freq = 0.0000 freq = 0.4422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 776: rs776
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.715778 pvalue = 0.0993605 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.860604 pvalue = 0.0907734 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.470181 pvalue = 0.0624845 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0800 sd = 0.0293 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+allele 2 : freq = 0.9200 sd = 0.0293 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0813 freq = 0.1375 freq = 0.0000 freq = 0.1234
+allele 2 : freq = 0.9187 freq = 0.8625 freq = 0.0000 freq = 0.8766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 777: rs777
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.118593 pvalue = 0.730565 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.070143 pvalue = 0.791128 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.172786 pvalue = 0.677647 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0983 sd = 0.0322 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221
+allele 2 : freq = 0.9017 sd = 0.0322 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0938 freq = 0.0854 freq = 0.0000 freq = 0.0875
+allele 2 : freq = 0.9062 freq = 0.9146 freq = 0.0000 freq = 0.9125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 778: rs778
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.242746 pvalue = 0.264942 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.861068 pvalue = 0.35344 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.094010 pvalue = 0.75914 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7633 sd = 0.0459 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+allele 2 : freq = 0.2367 sd = 0.0459 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7688 freq = 0.7271 freq = 0.0000 freq = 0.7375
+allele 2 : freq = 0.2313 freq = 0.2729 freq = 0.0000 freq = 0.2625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 779: rs779
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.722578 pvalue = 0.3953 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.369763 pvalue = 0.543134 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.059699 pvalue = 0.15124 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6083 sd = 0.0527 freq = 0.6615 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.3917 sd = 0.0527 freq = 0.3385 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6125 freq = 0.6417 freq = 0.0000 freq = 0.6344
+allele 2 : freq = 0.3875 freq = 0.3583 freq = 0.0000 freq = 0.3656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 780: rs780
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.704490 pvalue = 0.401279 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.627469 pvalue = 0.428285 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.954822 pvalue = 0.328495 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8433 sd = 0.0393 freq = 0.7962 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.1567 sd = 0.0393 freq = 0.2038 sd = 0.0306 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8063 freq = 0.0000 freq = 0.8141
+allele 2 : freq = 0.1625 freq = 0.1938 freq = 0.0000 freq = 0.1859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 781: rs781
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.241727 pvalue = 0.622961 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.728717 pvalue = 0.393299 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.472699 pvalue = 0.491748 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1533 sd = 0.0389 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275
+allele 2 : freq = 0.8467 sd = 0.0389 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.2083 freq = 0.0000 freq = 0.2000
+allele 2 : freq = 0.8250 freq = 0.7917 freq = 0.0000 freq = 0.8000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 782: rs782
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.150629 pvalue = 0.697935 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.516159 pvalue = 0.472485 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.048590 pvalue = 0.825534 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7883 sd = 0.0441 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+allele 2 : freq = 0.2117 sd = 0.0441 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.8167 freq = 0.0000 freq = 0.8094
+allele 2 : freq = 0.2125 freq = 0.1833 freq = 0.0000 freq = 0.1906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 783: rs783
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000047 pvalue = 0.994537 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.776980 pvalue = 0.378066 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001731 pvalue = 0.966811 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4567 sd = 0.0538 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+allele 2 : freq = 0.5433 sd = 0.0538 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4813 freq = 0.0000 freq = 0.4703
+allele 2 : freq = 0.5625 freq = 0.5188 freq = 0.0000 freq = 0.5297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 784: rs784
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.294186 pvalue = 0.587551 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.207748 pvalue = 0.648538 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.431888 pvalue = 0.511064 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5188 freq = 0.4958 freq = 0.0000 freq = 0.5016
+allele 2 : freq = 0.4813 freq = 0.5042 freq = 0.0000 freq = 0.4984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 785: rs785
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.857699 pvalue = 0.0155091 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 6.237683 pvalue = 0.012506 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 4.951513 pvalue = 0.0260678 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2267 sd = 0.0452 freq = 0.3346 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.7733 sd = 0.0452 freq = 0.6654 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 freq = 0.3417 freq = 0.0000 freq = 0.3125
+allele 2 : freq = 0.7750 freq = 0.6583 freq = 0.0000 freq = 0.6875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 786: rs786
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.283081 pvalue = 0.257327 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.258703 pvalue = 0.611012 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.983202 pvalue = 0.32141 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8400 sd = 0.0396 freq = 0.7942 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.1600 sd = 0.0396 freq = 0.2058 sd = 0.0307 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8167 freq = 0.0000 freq = 0.8219
+allele 2 : freq = 0.1625 freq = 0.1833 freq = 0.0000 freq = 0.1781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 787: rs787
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.027711 pvalue = 0.154453 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.249745 pvalue = 0.263601 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.603798 pvalue = 0.106608 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0967 sd = 0.0319 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.9033 sd = 0.0319 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1000 freq = 0.1396 freq = 0.0000 freq = 0.1297
+allele 2 : freq = 0.9000 freq = 0.8604 freq = 0.0000 freq = 0.8703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 788: rs788
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.151376 pvalue = 0.283261 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.553792 pvalue = 0.456772 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001431 pvalue = 0.969824 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1283 sd = 0.0361 freq = 0.1558 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+allele 2 : freq = 0.8717 sd = 0.0361 freq = 0.8442 sd = 0.0275 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1187 freq = 0.1458 freq = 0.0000 freq = 0.1391
+allele 2 : freq = 0.8812 freq = 0.8542 freq = 0.0000 freq = 0.8609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 789: rs789
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.181490 pvalue = 0.670096 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.077879 pvalue = 0.780193 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.122778 pvalue = 0.72604 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1433 sd = 0.0378 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+allele 2 : freq = 0.8567 sd = 0.0378 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 freq = 0.1604 freq = 0.0000 freq = 0.1578
+allele 2 : freq = 0.8500 freq = 0.8396 freq = 0.0000 freq = 0.8422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 790: rs790
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.464273 pvalue = 0.495634 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386842 pvalue = 0.533964 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.056230 pvalue = 0.812557 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2617 sd = 0.0475 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7383 sd = 0.0475 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2750 freq = 0.2479 freq = 0.0000 freq = 0.2547
+allele 2 : freq = 0.7250 freq = 0.7521 freq = 0.0000 freq = 0.7453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 791: rs791
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.006761 pvalue = 0.934466 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.048164 pvalue = 0.82629 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.121155 pvalue = 0.727785 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3550 sd = 0.0517 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+allele 2 : freq = 0.6450 sd = 0.0517 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.3542 freq = 0.0000 freq = 0.3516
+allele 2 : freq = 0.6562 freq = 0.6458 freq = 0.0000 freq = 0.6484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 792: rs792
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.020865 pvalue = 0.885146 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.124628 pvalue = 0.724068 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.122461 pvalue = 0.726381 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8667 sd = 0.0367 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+allele 2 : freq = 0.1333 sd = 0.0367 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8562 freq = 0.8438 freq = 0.0000 freq = 0.8469
+allele 2 : freq = 0.1437 freq = 0.1562 freq = 0.0000 freq = 0.1531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 793: rs793
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.995050 pvalue = 0.318511 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.452569 pvalue = 0.501118 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.378084 pvalue = 0.123048 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6433 sd = 0.0517 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5850 sd = 0.0348
+allele 2 : freq = 0.3567 sd = 0.0517 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4150 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.5979 freq = 0.0000 freq = 0.6062
+allele 2 : freq = 0.3688 freq = 0.4021 freq = 0.0000 freq = 0.3937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 794: rs794
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.070593 pvalue = 0.300811 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.155485 pvalue = 0.282404 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.303093 pvalue = 0.129117 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1883 sd = 0.0422 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+allele 2 : freq = 0.8117 sd = 0.0422 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2000 freq = 0.2458 freq = 0.0000 freq = 0.2344
+allele 2 : freq = 0.8000 freq = 0.7542 freq = 0.0000 freq = 0.7656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 795: rs795
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.194257 pvalue = 0.138526 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.225805 pvalue = 0.135722 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.028082 pvalue = 0.154415 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4800 sd = 0.0540 freq = 0.5115 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+allele 2 : freq = 0.5200 sd = 0.0540 freq = 0.4885 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.5250 freq = 0.0000 freq = 0.5062
+allele 2 : freq = 0.5500 freq = 0.4750 freq = 0.0000 freq = 0.4938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 796: rs796
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.550019 pvalue = 0.45831 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.152642 pvalue = 0.696023 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.517302 pvalue = 0.471995 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8625 freq = 0.8479 freq = 0.0000 freq = 0.8516
+allele 2 : freq = 0.1375 freq = 0.1521 freq = 0.0000 freq = 0.1484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 797: rs797
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.096277 pvalue = 0.295085 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.606359 pvalue = 0.205004 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003849 pvalue = 0.950529 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2300 sd = 0.0455 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+allele 2 : freq = 0.7700 sd = 0.0455 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2875 freq = 0.0000 freq = 0.2734
+allele 2 : freq = 0.7688 freq = 0.7125 freq = 0.0000 freq = 0.7266
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 798: rs798
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.970571 pvalue = 0.0847919 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.186381 pvalue = 0.139236 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.132938 pvalue = 0.287149 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8650 sd = 0.0369 freq = 0.8019 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.1350 sd = 0.0369 freq = 0.1981 sd = 0.0303 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8104 freq = 0.0000 freq = 0.8250
+allele 2 : freq = 0.1313 freq = 0.1896 freq = 0.0000 freq = 0.1750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 799: rs799
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.570259 pvalue = 0.10889 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.733467 pvalue = 0.187969 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.906525 pvalue = 0.16735 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7817 sd = 0.0446 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8450 sd = 0.0256
+allele 2 : freq = 0.2183 sd = 0.0446 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1550 sd = 0.0256
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7937 freq = 0.8417 freq = 0.0000 freq = 0.8297
+allele 2 : freq = 0.2062 freq = 0.1583 freq = 0.0000 freq = 0.1703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 800: rs800
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.167509 pvalue = 0.682335 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.358916 pvalue = 0.549109 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.124955 pvalue = 0.723721 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6217 sd = 0.0524 freq = 0.6115 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.3783 sd = 0.0524 freq = 0.3885 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6375 freq = 0.6083 freq = 0.0000 freq = 0.6156
+allele 2 : freq = 0.3625 freq = 0.3917 freq = 0.0000 freq = 0.3844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 801: rs801
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.530169 pvalue = 0.466536 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.136649 pvalue = 0.711636 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.059676 pvalue = 0.807008 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7617 sd = 0.0460 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.2383 sd = 0.0460 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7812 freq = 0.7958 freq = 0.0000 freq = 0.7922
+allele 2 : freq = 0.2188 freq = 0.2042 freq = 0.0000 freq = 0.2078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 802: rs802
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.082507 pvalue = 0.298137 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.615256 pvalue = 0.432816 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.002092 pvalue = 0.96352 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7667 sd = 0.0457 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.2333 sd = 0.0457 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7271 freq = 0.0000 freq = 0.7359
+allele 2 : freq = 0.2375 freq = 0.2729 freq = 0.0000 freq = 0.2641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 803: rs803
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.319071 pvalue = 0.127796 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.775137 pvalue = 0.182748 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.966665 pvalue = 0.325513 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6267 sd = 0.0522 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+allele 2 : freq = 0.3733 sd = 0.0522 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.6813 freq = 0.0000 freq = 0.6656
+allele 2 : freq = 0.3812 freq = 0.3187 freq = 0.0000 freq = 0.3344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 804: rs804
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.046314 pvalue = 0.306358 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.879061 pvalue = 0.348459 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.117157 pvalue = 0.290531 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8717 sd = 0.0361 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+allele 2 : freq = 0.1283 sd = 0.0361 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8625 freq = 0.8271 freq = 0.0000 freq = 0.8359
+allele 2 : freq = 0.1375 freq = 0.1729 freq = 0.0000 freq = 0.1641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 805: rs805
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.056637 pvalue = 0.151544 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.874893 pvalue = 0.0272501 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.320923 pvalue = 0.127644 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0917 sd = 0.0312 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+allele 2 : freq = 0.9083 sd = 0.0312 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0875 freq = 0.1583 freq = 0.0000 freq = 0.1406
+allele 2 : freq = 0.9125 freq = 0.8417 freq = 0.0000 freq = 0.8594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 806: rs806
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.849584 pvalue = 0.35667 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.279526 pvalue = 0.597012 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000848 pvalue = 0.976772 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2950 sd = 0.0493 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+allele 2 : freq = 0.7050 sd = 0.0493 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.3125 freq = 0.0000 freq = 0.3063
+allele 2 : freq = 0.7125 freq = 0.6875 freq = 0.0000 freq = 0.6937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 807: rs807
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.734323 pvalue = 0.0533053 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.076126 pvalue = 0.149619 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.268433 pvalue = 0.604385 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5533 sd = 0.0537 freq = 0.6077 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.4467 sd = 0.0537 freq = 0.3923 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5188 freq = 0.5896 freq = 0.0000 freq = 0.5719
+allele 2 : freq = 0.4813 freq = 0.4104 freq = 0.0000 freq = 0.4281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 808: rs808
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.254715 pvalue = 0.262654 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.685638 pvalue = 0.407652 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.797091 pvalue = 0.371964 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6167 sd = 0.0525 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+allele 2 : freq = 0.3833 sd = 0.0525 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.6458 freq = 0.0000 freq = 0.6359
+allele 2 : freq = 0.3937 freq = 0.3542 freq = 0.0000 freq = 0.3641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 809: rs809
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007888 pvalue = 0.92923 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.074318 pvalue = 0.78515 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.371260 pvalue = 0.241595 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.1646 freq = 0.0000 freq = 0.1672
+allele 2 : freq = 0.8250 freq = 0.8354 freq = 0.0000 freq = 0.8328
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 810: rs810
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.811301 pvalue = 0.0509079 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.765072 pvalue = 0.0290428 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.812880 pvalue = 0.36727 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8333 sd = 0.0403 freq = 0.7615 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.1667 sd = 0.0403 freq = 0.2385 sd = 0.0324 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.7458 freq = 0.0000 freq = 0.7688
+allele 2 : freq = 0.1625 freq = 0.2542 freq = 0.0000 freq = 0.2313
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 811: rs811
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.074935 pvalue = 0.784282 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.256780 pvalue = 0.612341 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.020597 pvalue = 0.885882 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0950 sd = 0.0317 freq = 0.0923 sd = 0.0220 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202
+allele 2 : freq = 0.9050 sd = 0.0317 freq = 0.9077 sd = 0.0220 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0938 freq = 0.0792 freq = 0.0000 freq = 0.0828
+allele 2 : freq = 0.9062 freq = 0.9208 freq = 0.0000 freq = 0.9172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 812: rs812
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001119 pvalue = 0.973318 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.195642 pvalue = 0.658262 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.048060 pvalue = 0.826475 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6617 sd = 0.0511 freq = 0.6615 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.3383 sd = 0.0511 freq = 0.3385 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6687 freq = 0.6479 freq = 0.0000 freq = 0.6531
+allele 2 : freq = 0.3312 freq = 0.3521 freq = 0.0000 freq = 0.3469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 813: rs813
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.030383 pvalue = 0.861623 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.220424 pvalue = 0.638717 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.350839 pvalue = 0.553638 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6269 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3731 sd = 0.0367 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.6417 freq = 0.0000 freq = 0.6359
+allele 2 : freq = 0.3812 freq = 0.3583 freq = 0.0000 freq = 0.3641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 814: rs814
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.718602 pvalue = 0.396603 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.985522 pvalue = 0.320839 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.016272 pvalue = 0.898494 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1883 sd = 0.0422 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.8117 sd = 0.0422 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1938 freq = 0.1562 freq = 0.0000 freq = 0.1656
+allele 2 : freq = 0.8063 freq = 0.8438 freq = 0.0000 freq = 0.8344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 815: rs815
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.248869 pvalue = 0.617873 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.141448 pvalue = 0.706846 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.250885 pvalue = 0.263383 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4283 sd = 0.0534 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5717 sd = 0.0534 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.4313 freq = 0.0000 freq = 0.4266
+allele 2 : freq = 0.5875 freq = 0.5687 freq = 0.0000 freq = 0.5734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 816: rs816
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.022382 pvalue = 0.881076 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.067473 pvalue = 0.795053 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.532233 pvalue = 0.46567 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8933 sd = 0.0333 freq = 0.8904 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.1067 sd = 0.0333 freq = 0.1096 sd = 0.0237 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8875 freq = 0.8792 freq = 0.0000 freq = 0.8812
+allele 2 : freq = 0.1125 freq = 0.1208 freq = 0.0000 freq = 0.1187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 817: rs817
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.762018 pvalue = 0.184373 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.166083 pvalue = 0.141085 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.720141 pvalue = 0.189675 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3667 sd = 0.0521 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.6333 sd = 0.0521 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.2938 freq = 0.0000 freq = 0.3109
+allele 2 : freq = 0.6375 freq = 0.7063 freq = 0.0000 freq = 0.6891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 818: rs818
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.694259 pvalue = 0.40472 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.412695 pvalue = 0.23461 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.072901 pvalue = 0.78716 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9150 sd = 0.0301 freq = 0.9269 sd = 0.0198 freq = 0.0000 sd = 0.0000 freq = 0.9150 sd = 0.0197
+allele 2 : freq = 0.0850 sd = 0.0301 freq = 0.0731 sd = 0.0198 freq = 0.0000 sd = 0.0000 freq = 0.0850 sd = 0.0197
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9000 freq = 0.9333 freq = 0.0000 freq = 0.9250
+allele 2 : freq = 0.1000 freq = 0.0667 freq = 0.0000 freq = 0.0750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 819: rs819
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.098945 pvalue = 0.753099 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.073575 pvalue = 0.786201 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.022313 pvalue = 0.881256 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.7000 freq = 0.0000 freq = 0.7031
+allele 2 : freq = 0.2875 freq = 0.3000 freq = 0.0000 freq = 0.2969
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 820: rs820
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.569207 pvalue = 0.210322 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.536056 pvalue = 0.111272 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.043143 pvalue = 0.835456 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.5731 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.4269 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5312 freq = 0.6104 freq = 0.0000 freq = 0.5906
+allele 2 : freq = 0.4688 freq = 0.3896 freq = 0.0000 freq = 0.4094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 821: rs821
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.723902 pvalue = 0.394867 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.775714 pvalue = 0.182676 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.134158 pvalue = 0.0132595 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4733 sd = 0.0539 freq = 0.4231 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5267 sd = 0.0539 freq = 0.5769 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 freq = 0.4083 freq = 0.0000 freq = 0.4250
+allele 2 : freq = 0.5250 freq = 0.5917 freq = 0.0000 freq = 0.5750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 822: rs822
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.153359 pvalue = 0.0757708 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.450022 pvalue = 0.228524 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.798319 pvalue = 0.179916 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2450 sd = 0.0465 freq = 0.3154 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+allele 2 : freq = 0.7550 sd = 0.0465 freq = 0.6846 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.2938 freq = 0.0000 freq = 0.2797
+allele 2 : freq = 0.7625 freq = 0.7063 freq = 0.0000 freq = 0.7203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 823: rs823
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.556592 pvalue = 0.455637 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.815566 pvalue = 0.36648 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.252574 pvalue = 0.615268 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2300 sd = 0.0455 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+allele 2 : freq = 0.7700 sd = 0.0455 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2708 freq = 0.0000 freq = 0.2609
+allele 2 : freq = 0.7688 freq = 0.7292 freq = 0.0000 freq = 0.7391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 824: rs824
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.755063 pvalue = 0.384878 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.516815 pvalue = 0.472204 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.590608 pvalue = 0.442184 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4400 sd = 0.0536 freq = 0.4173 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.5600 sd = 0.0536 freq = 0.5827 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4021 freq = 0.0000 freq = 0.4109
+allele 2 : freq = 0.5625 freq = 0.5979 freq = 0.0000 freq = 0.5891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 825: rs825
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.636625 pvalue = 0.424936 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.323230 pvalue = 0.569673 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.141159 pvalue = 0.707131 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3600 sd = 0.0518 freq = 0.3346 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+allele 2 : freq = 0.6400 sd = 0.0518 freq = 0.6654 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3750 freq = 0.3479 freq = 0.0000 freq = 0.3547
+allele 2 : freq = 0.6250 freq = 0.6521 freq = 0.0000 freq = 0.6453
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 826: rs826
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.135428 pvalue = 0.712869 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.004769 pvalue = 0.944945 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.013016 pvalue = 0.909168 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1000 sd = 0.0324 freq = 0.1058 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212
+allele 2 : freq = 0.9000 sd = 0.0324 freq = 0.8942 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1125 freq = 0.1104 freq = 0.0000 freq = 0.1109
+allele 2 : freq = 0.8875 freq = 0.8896 freq = 0.0000 freq = 0.8891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 827: rs827
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.281057 pvalue = 0.59601 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.998809 pvalue = 0.317599 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.038077 pvalue = 0.845289 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7017 sd = 0.0494 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.2983 sd = 0.0494 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.7396 freq = 0.0000 freq = 0.7281
+allele 2 : freq = 0.3063 freq = 0.2604 freq = 0.0000 freq = 0.2719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 828: rs828
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000191 pvalue = 0.988978 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.319337 pvalue = 0.572006 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.674981 pvalue = 0.411321 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1617 sd = 0.0398 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8383 sd = 0.0398 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1688 freq = 0.1896 freq = 0.0000 freq = 0.1844
+allele 2 : freq = 0.8313 freq = 0.8104 freq = 0.0000 freq = 0.8156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 829: rs829
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.039054 pvalue = 0.843342 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.057225 pvalue = 0.810937 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.024991 pvalue = 0.874389 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2550 sd = 0.0471 freq = 0.2462 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7450 sd = 0.0471 freq = 0.7538 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2542 freq = 0.0000 freq = 0.2516
+allele 2 : freq = 0.7562 freq = 0.7458 freq = 0.0000 freq = 0.7484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 830: rs830
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.232644 pvalue = 0.62957 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.504671 pvalue = 0.477455 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.247088 pvalue = 0.619133 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4717 sd = 0.0539 freq = 0.4365 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5283 sd = 0.0539 freq = 0.5635 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4500 freq = 0.4146 freq = 0.0000 freq = 0.4234
+allele 2 : freq = 0.5500 freq = 0.5854 freq = 0.0000 freq = 0.5766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 831: rs831
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.401448 pvalue = 0.526342 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.045316 pvalue = 0.831424 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.322762 pvalue = 0.0210486 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6933 sd = 0.0498 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+allele 2 : freq = 0.3067 sd = 0.0498 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6562 freq = 0.6667 freq = 0.0000 freq = 0.6641
+allele 2 : freq = 0.3438 freq = 0.3333 freq = 0.0000 freq = 0.3359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 832: rs832
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.250974 pvalue = 0.263367 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.374871 pvalue = 0.540361 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.092088 pvalue = 0.76154 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3000 sd = 0.0495 freq = 0.3327 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+allele 2 : freq = 0.7000 sd = 0.0495 freq = 0.6673 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.3167 freq = 0.0000 freq = 0.3094
+allele 2 : freq = 0.7125 freq = 0.6833 freq = 0.0000 freq = 0.6906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 833: rs833
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.125949 pvalue = 0.72267 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.336619 pvalue = 0.561788 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.837762 pvalue = 0.175213 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5133 sd = 0.0540 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.4867 sd = 0.0540 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.4708 freq = 0.0000 freq = 0.4781
+allele 2 : freq = 0.5000 freq = 0.5292 freq = 0.0000 freq = 0.5219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 834: rs834
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.359024 pvalue = 0.243707 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.837611 pvalue = 0.360081 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.171359 pvalue = 0.279122 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 sd = 0.0432 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2000 sd = 0.0432 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 freq = 0.7604 freq = 0.0000 freq = 0.7703
+allele 2 : freq = 0.2000 freq = 0.2396 freq = 0.0000 freq = 0.2297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 835: rs835
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.057669 pvalue = 0.303747 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.565058 pvalue = 0.45223 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.171367 pvalue = 0.6789 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8917 sd = 0.0336 freq = 0.8788 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234
+allele 2 : freq = 0.1083 sd = 0.0336 freq = 0.1212 sd = 0.0248 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9062 freq = 0.8812 freq = 0.0000 freq = 0.8875
+allele 2 : freq = 0.0938 freq = 0.1187 freq = 0.0000 freq = 0.1125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 836: rs836
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.032187 pvalue = 0.857617 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.047164 pvalue = 0.828074 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.623059 pvalue = 0.429913 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3317 sd = 0.0509 freq = 0.3519 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+allele 2 : freq = 0.6683 sd = 0.0509 freq = 0.6481 sd = 0.0363 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.3542 freq = 0.0000 freq = 0.3516
+allele 2 : freq = 0.6562 freq = 0.6458 freq = 0.0000 freq = 0.6484
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 837: rs837
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.001239 pvalue = 0.971919 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.006870 pvalue = 0.933944 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.912765 pvalue = 0.166656 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4950 sd = 0.0540 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353
+allele 2 : freq = 0.5050 sd = 0.0540 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4938 freq = 0.4979 freq = 0.0000 freq = 0.4969
+allele 2 : freq = 0.5062 freq = 0.5021 freq = 0.0000 freq = 0.5031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 838: rs838
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.016949 pvalue = 0.896418 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.051094 pvalue = 0.821171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.125862 pvalue = 0.722762 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8483 sd = 0.0387 freq = 0.8519 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+allele 2 : freq = 0.1517 sd = 0.0387 freq = 0.1481 sd = 0.0270 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8375 freq = 0.8458 freq = 0.0000 freq = 0.8438
+allele 2 : freq = 0.1625 freq = 0.1542 freq = 0.0000 freq = 0.1562
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 839: rs839
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.121439 pvalue = 0.727479 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.112161 pvalue = 0.737697 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.056230 pvalue = 0.812557 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2442 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7558 sd = 0.0326 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.2521 freq = 0.0000 freq = 0.2484
+allele 2 : freq = 0.7625 freq = 0.7479 freq = 0.0000 freq = 0.7516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 840: rs840
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.930951 pvalue = 0.0868963 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.468611 pvalue = 0.225565 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.068826 pvalue = 0.793053 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3567 sd = 0.0517 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.6433 sd = 0.0517 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3563 freq = 0.4167 freq = 0.0000 freq = 0.4016
+allele 2 : freq = 0.6438 freq = 0.5833 freq = 0.0000 freq = 0.5984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 841: rs841
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000024 pvalue = 0.996068 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.402364 pvalue = 0.525871 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.581463 pvalue = 0.20855 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3983 sd = 0.0529 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.6017 sd = 0.0529 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3875 freq = 0.3563 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.6125 freq = 0.6438 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 842: rs842
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.976478 pvalue = 0.0844829 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.007435 pvalue = 0.15653 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.268055 pvalue = 0.0122934 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1967 sd = 0.0429 freq = 0.1250 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238
+allele 2 : freq = 0.8033 sd = 0.0429 freq = 0.8750 sd = 0.0251 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1812 freq = 0.1333 freq = 0.0000 freq = 0.1453
+allele 2 : freq = 0.8187 freq = 0.8667 freq = 0.0000 freq = 0.8547
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 843: rs843
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.116676 pvalue = 0.732668 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.018760 pvalue = 0.891057 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.058260 pvalue = 0.809268 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6917 sd = 0.0499 freq = 0.7038 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321
+allele 2 : freq = 0.3083 sd = 0.0499 freq = 0.2962 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.7000 freq = 0.0000 freq = 0.6984
+allele 2 : freq = 0.3063 freq = 0.3000 freq = 0.0000 freq = 0.3016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 844: rs844
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.550361 pvalue = 0.45817 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.852740 pvalue = 0.355778 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.032508 pvalue = 0.856917 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6017 sd = 0.0529 freq = 0.5673 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+allele 2 : freq = 0.3983 sd = 0.0529 freq = 0.4327 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6062 freq = 0.5604 freq = 0.0000 freq = 0.5719
+allele 2 : freq = 0.3937 freq = 0.4396 freq = 0.0000 freq = 0.4281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 845: rs845
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.847782 pvalue = 0.357181 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386842 pvalue = 0.533964 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.624775 pvalue = 0.429278 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2200 sd = 0.0447 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7800 sd = 0.0447 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2125 freq = 0.2396 freq = 0.0000 freq = 0.2328
+allele 2 : freq = 0.7875 freq = 0.7604 freq = 0.0000 freq = 0.7672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 846: rs846
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.951610 pvalue = 0.0260664 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.961742 pvalue = 0.0465455 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.453804 pvalue = 0.227919 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5683 sd = 0.0535 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.4317 sd = 0.0535 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.4750 freq = 0.0000 freq = 0.5000
+allele 2 : freq = 0.4250 freq = 0.5250 freq = 0.0000 freq = 0.5000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 847: rs847
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.975661 pvalue = 0.323273 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.124566 pvalue = 0.288937 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.816595 pvalue = 0.366177 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8017 sd = 0.0431 freq = 0.8423 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1983 sd = 0.0431 freq = 0.1577 sd = 0.0277 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.8458 freq = 0.0000 freq = 0.8359
+allele 2 : freq = 0.1938 freq = 0.1542 freq = 0.0000 freq = 0.1641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 848: rs848
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.679498 pvalue = 0.194991 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.384759 pvalue = 0.239292 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.014173 pvalue = 0.155836 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1100 sd = 0.0338 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249
+allele 2 : freq = 0.8900 sd = 0.0338 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1062 freq = 0.1479 freq = 0.0000 freq = 0.1375
+allele 2 : freq = 0.8938 freq = 0.8521 freq = 0.0000 freq = 0.8625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 849: rs849
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.540857 pvalue = 0.462078 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.533830 pvalue = 0.215539 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.261658 pvalue = 0.608983 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6917 sd = 0.0499 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6750 sd = 0.0331
+allele 2 : freq = 0.3083 sd = 0.0499 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3250 sd = 0.0331
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6354 freq = 0.0000 freq = 0.6500
+allele 2 : freq = 0.3063 freq = 0.3646 freq = 0.0000 freq = 0.3500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 850: rs850
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.061017 pvalue = 0.804896 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.300161 pvalue = 0.583781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003641 pvalue = 0.951883 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7133 sd = 0.0488 freq = 0.7192 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321
+allele 2 : freq = 0.2867 sd = 0.0488 freq = 0.2808 sd = 0.0341 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7063 freq = 0.7312 freq = 0.0000 freq = 0.7250
+allele 2 : freq = 0.2938 freq = 0.2687 freq = 0.0000 freq = 0.2750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 851: rs851
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.214319 pvalue = 0.643403 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.148496 pvalue = 0.699977 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.275867 pvalue = 0.599423 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7433 sd = 0.0472 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2567 sd = 0.0472 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7375 freq = 0.7542 freq = 0.0000 freq = 0.7500
+allele 2 : freq = 0.2625 freq = 0.2458 freq = 0.0000 freq = 0.2500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 852: rs852
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.298378 pvalue = 0.584901 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.437209 pvalue = 0.508473 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.326510 pvalue = 0.567721 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7967 sd = 0.0435 freq = 0.7923 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2033 sd = 0.0435 freq = 0.2077 sd = 0.0308 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.7792 freq = 0.0000 freq = 0.7859
+allele 2 : freq = 0.1938 freq = 0.2208 freq = 0.0000 freq = 0.2141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 853: rs853
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.418698 pvalue = 0.517588 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.142258 pvalue = 0.706047 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.996046 pvalue = 0.083468 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4683 sd = 0.0539 freq = 0.4154 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+allele 2 : freq = 0.5317 sd = 0.0539 freq = 0.5846 sd = 0.0374 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4562 freq = 0.4375 freq = 0.0000 freq = 0.4422
+allele 2 : freq = 0.5437 freq = 0.5625 freq = 0.0000 freq = 0.5578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 854: rs854
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000053 pvalue = 0.994187 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.009281 pvalue = 0.923252 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.042811 pvalue = 0.836081 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2396 freq = 0.0000 freq = 0.2406
+allele 2 : freq = 0.7562 freq = 0.7604 freq = 0.0000 freq = 0.7594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 855: rs855
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.186839 pvalue = 0.665561 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.770104 pvalue = 0.380185 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.597893 pvalue = 0.439383 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4483 sd = 0.0537 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5517 sd = 0.0537 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4437 freq = 0.4000 freq = 0.0000 freq = 0.4109
+allele 2 : freq = 0.5563 freq = 0.6000 freq = 0.0000 freq = 0.5891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 856: rs856
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.199593 pvalue = 0.65505 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.721629 pvalue = 0.39561 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.113452 pvalue = 0.736247 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3983 sd = 0.0529 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.6017 sd = 0.0529 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4000 freq = 0.3583 freq = 0.0000 freq = 0.3688
+allele 2 : freq = 0.6000 freq = 0.6417 freq = 0.0000 freq = 0.6312
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 857: rs857
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.348675 pvalue = 0.12539 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.041338 pvalue = 0.081169 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.027824 pvalue = 0.867523 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 sd = 0.0506 freq = 0.7423 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+allele 2 : freq = 0.3250 sd = 0.0506 freq = 0.2577 sd = 0.0332 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6625 freq = 0.7417 freq = 0.0000 freq = 0.7219
+allele 2 : freq = 0.3375 freq = 0.2583 freq = 0.0000 freq = 0.2781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 858: rs858
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 4.879486 pvalue = 0.0271777 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.436308 pvalue = 0.0197223 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 1.530963 pvalue = 0.215968 df = 1
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9500 sd = 0.0235 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207
+allele 2 : freq = 0.0500 sd = 0.0235 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9563 freq = 0.8875 freq = 0.0000 freq = 0.9047
+allele 2 : freq = 0.0437 freq = 0.1125 freq = 0.0000 freq = 0.0953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 859: rs859
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.541300 pvalue = 0.461894 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.280573 pvalue = 0.596326 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.620308 pvalue = 0.430933 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8783 sd = 0.0353 freq = 0.8885 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221
+allele 2 : freq = 0.1217 sd = 0.0353 freq = 0.1115 sd = 0.0239 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8688 freq = 0.8854 freq = 0.0000 freq = 0.8812
+allele 2 : freq = 0.1313 freq = 0.1146 freq = 0.0000 freq = 0.1187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 860: rs860
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.217507 pvalue = 0.26985 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.885628 pvalue = 0.346665 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.961765 pvalue = 0.326743 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9367 sd = 0.0263 freq = 0.8942 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202
+allele 2 : freq = 0.0633 sd = 0.0263 freq = 0.1058 sd = 0.0234 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9375 freq = 0.9104 freq = 0.0000 freq = 0.9172
+allele 2 : freq = 0.0625 freq = 0.0896 freq = 0.0000 freq = 0.0828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 861: rs861
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.837688 pvalue = 0.175222 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.352564 pvalue = 0.24483 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.744697 pvalue = 0.0529753 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4167 sd = 0.0533 freq = 0.4731 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+allele 2 : freq = 0.5833 sd = 0.0533 freq = 0.5269 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4062 freq = 0.4646 freq = 0.0000 freq = 0.4500
+allele 2 : freq = 0.5938 freq = 0.5354 freq = 0.0000 freq = 0.5500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 862: rs862
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.004755 pvalue = 0.945026 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.019598 pvalue = 0.888667 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.173311 pvalue = 0.677186 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7383 sd = 0.0475 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+allele 2 : freq = 0.2617 sd = 0.0475 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7312 freq = 0.7250 freq = 0.0000 freq = 0.7266
+allele 2 : freq = 0.2687 freq = 0.2750 freq = 0.0000 freq = 0.2734
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 863: rs863
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.024395 pvalue = 0.875883 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.173778 pvalue = 0.676776 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.027321 pvalue = 0.868716 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5233 sd = 0.0539 freq = 0.5404 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+allele 2 : freq = 0.4767 sd = 0.0539 freq = 0.4596 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.5167 freq = 0.0000 freq = 0.5219
+allele 2 : freq = 0.4625 freq = 0.4833 freq = 0.0000 freq = 0.4781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 864: rs864
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.154866 pvalue = 0.693928 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.016886 pvalue = 0.89661 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9317 sd = 0.0273 freq = 0.9231 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186
+allele 2 : freq = 0.0683 sd = 0.0273 freq = 0.0769 sd = 0.0202 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9375 freq = 0.9375 freq = 0.0000 freq = 0.9375
+allele 2 : freq = 0.0625 freq = 0.0625 freq = 0.0000 freq = 0.0625
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 865: rs865
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.305705 pvalue = 0.580328 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.711590 pvalue = 0.190779 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.268092 pvalue = 0.132062 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4017 sd = 0.0530 freq = 0.3865 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+allele 2 : freq = 0.5983 sd = 0.0530 freq = 0.6135 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.3479 freq = 0.0000 freq = 0.3641
+allele 2 : freq = 0.5875 freq = 0.6521 freq = 0.0000 freq = 0.6359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 866: rs866
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.998740 pvalue = 0.0455343 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.214743 pvalue = 0.136698 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.139158 pvalue = 0.709119 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1467 sd = 0.0382 freq = 0.2173 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+allele 2 : freq = 0.8533 sd = 0.0382 freq = 0.7827 sd = 0.0313 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1313 freq = 0.1917 freq = 0.0000 freq = 0.1766
+allele 2 : freq = 0.8688 freq = 0.8083 freq = 0.0000 freq = 0.8234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 867: rs867
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 6.127169 pvalue = 0.013312 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 6.857690 pvalue = 0.00882606 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.139157 pvalue = 0.0764333 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3917 sd = 0.0527 freq = 0.4865 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+allele 2 : freq = 0.6083 sd = 0.0527 freq = 0.5135 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.4938 freq = 0.0000 freq = 0.4609
+allele 2 : freq = 0.6375 freq = 0.5062 freq = 0.0000 freq = 0.5391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 868: rs868
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.520410 pvalue = 0.470667 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.718383 pvalue = 0.396675 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.153727 pvalue = 0.694999 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6233 sd = 0.0523 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346
+allele 2 : freq = 0.3767 sd = 0.0523 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.5896 freq = 0.0000 freq = 0.6000
+allele 2 : freq = 0.3688 freq = 0.4104 freq = 0.0000 freq = 0.4000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 869: rs869
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.721803 pvalue = 0.189461 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.280322 pvalue = 0.257839 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.562538 pvalue = 0.0104148 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3450 sd = 0.0513 freq = 0.4423 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+allele 2 : freq = 0.6550 sd = 0.0513 freq = 0.5577 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3688 freq = 0.4250 freq = 0.0000 freq = 0.4109
+allele 2 : freq = 0.6312 freq = 0.5750 freq = 0.0000 freq = 0.5891
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 870: rs870
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.629086 pvalue = 0.20183 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.556198 pvalue = 0.109863 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.582281 pvalue = 0.445419 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3550 sd = 0.0517 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330
+allele 2 : freq = 0.6450 sd = 0.0517 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3625 freq = 0.2875 freq = 0.0000 freq = 0.3063
+allele 2 : freq = 0.6375 freq = 0.7125 freq = 0.0000 freq = 0.6937
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 871: rs871
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.549211 pvalue = 0.213252 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.181083 pvalue = 0.139716 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.288403 pvalue = 0.130344 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.2135 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.7865 sd = 0.0311 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2687 freq = 0.2062 freq = 0.0000 freq = 0.2219
+allele 2 : freq = 0.7312 freq = 0.7937 freq = 0.0000 freq = 0.7781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 872: rs872
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.658144 pvalue = 0.417216 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.840349 pvalue = 0.359297 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.134649 pvalue = 0.144003 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8550 sd = 0.0380 freq = 0.8308 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.1450 sd = 0.0380 freq = 0.1692 sd = 0.0285 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8083 freq = 0.0000 freq = 0.8172
+allele 2 : freq = 0.1562 freq = 0.1917 freq = 0.0000 freq = 0.1828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 873: rs873
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.317014 pvalue = 0.573408 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.376932 pvalue = 0.53925 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.991750 pvalue = 0.319315 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8283 sd = 0.0407 freq = 0.8404 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1717 sd = 0.0407 freq = 0.1596 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.8417 freq = 0.0000 freq = 0.8359
+allele 2 : freq = 0.1812 freq = 0.1583 freq = 0.0000 freq = 0.1641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 874: rs874
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007118 pvalue = 0.932766 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.067061 pvalue = 0.795665 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 freq = 0.8104 freq = 0.0000 freq = 0.8078
+allele 2 : freq = 0.2000 freq = 0.1896 freq = 0.0000 freq = 0.1922
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 875: rs875
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.932493 pvalue = 0.334216 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.431888 pvalue = 0.511064 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.162629 pvalue = 0.686747 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7700 sd = 0.0455 freq = 0.7365 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+allele 2 : freq = 0.2300 sd = 0.0455 freq = 0.2635 sd = 0.0335 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 freq = 0.7458 freq = 0.0000 freq = 0.7531
+allele 2 : freq = 0.2250 freq = 0.2542 freq = 0.0000 freq = 0.2469
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 876: rs876
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.673345 pvalue = 0.411888 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.277347 pvalue = 0.258393 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.022313 pvalue = 0.881256 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3283 sd = 0.0507 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.6717 sd = 0.0507 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.2729 freq = 0.0000 freq = 0.2859
+allele 2 : freq = 0.6750 freq = 0.7271 freq = 0.0000 freq = 0.7141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 877: rs877
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.546384 pvalue = 0.459799 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.475249 pvalue = 0.224519 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.449588 pvalue = 0.228594 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7933 sd = 0.0437 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.2067 sd = 0.0437 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7937 freq = 0.8417 freq = 0.0000 freq = 0.8297
+allele 2 : freq = 0.2062 freq = 0.1583 freq = 0.0000 freq = 0.1703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 878: rs878
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.640516 pvalue = 0.423524 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.172521 pvalue = 0.677881 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.655666 pvalue = 0.418094 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5700 sd = 0.0535 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+allele 2 : freq = 0.4300 sd = 0.0535 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.5542 freq = 0.0000 freq = 0.5594
+allele 2 : freq = 0.4250 freq = 0.4458 freq = 0.0000 freq = 0.4406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 879: rs879
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.698987 pvalue = 0.403124 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.122407 pvalue = 0.726439 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.175614 pvalue = 0.67517 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6200 sd = 0.0524 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335
+allele 2 : freq = 0.3800 sd = 0.0524 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.6354 freq = 0.0000 freq = 0.6312
+allele 2 : freq = 0.3812 freq = 0.3646 freq = 0.0000 freq = 0.3688
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 880: rs880
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000657 pvalue = 0.979557 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.006187 pvalue = 0.937308 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.067543 pvalue = 0.794948 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9250 sd = 0.0284 freq = 0.9250 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.9250 sd = 0.0186
+allele 2 : freq = 0.0750 sd = 0.0284 freq = 0.0750 sd = 0.0200 freq = 0.0000 sd = 0.0000 freq = 0.0750 sd = 0.0186
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9250 freq = 0.9229 freq = 0.0000 freq = 0.9234
+allele 2 : freq = 0.0750 freq = 0.0771 freq = 0.0000 freq = 0.0766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 881: rs881
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.083611 pvalue = 0.772462 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.574854 pvalue = 0.448337 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.015690 pvalue = 0.900317 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5875 freq = 0.6250 freq = 0.0000 freq = 0.6156
+allele 2 : freq = 0.4125 freq = 0.3750 freq = 0.0000 freq = 0.3844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 882: rs882
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.230186 pvalue = 0.631386 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.499338 pvalue = 0.479791 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.399162 pvalue = 0.527522 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 sd = 0.0539 freq = 0.4654 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+allele 2 : freq = 0.5250 sd = 0.0539 freq = 0.5346 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 freq = 0.4396 freq = 0.0000 freq = 0.4484
+allele 2 : freq = 0.5250 freq = 0.5604 freq = 0.0000 freq = 0.5516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 883: rs883
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.188902 pvalue = 0.663832 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.329552 pvalue = 0.565923 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6400 sd = 0.0518 freq = 0.6423 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.3600 sd = 0.0518 freq = 0.3577 sd = 0.0364 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6250 freq = 0.6250 freq = 0.0000 freq = 0.6250
+allele 2 : freq = 0.3750 freq = 0.3750 freq = 0.0000 freq = 0.3750
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 884: rs884
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.009499 pvalue = 0.922358 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.002847 pvalue = 0.957451 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.081832 pvalue = 0.298288 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275
+allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1812 freq = 0.1833 freq = 0.0000 freq = 0.1828
+allele 2 : freq = 0.8187 freq = 0.8167 freq = 0.0000 freq = 0.8172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 885: rs885
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.721543 pvalue = 0.395638 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.747037 pvalue = 0.18625 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.418250 pvalue = 0.0644793 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6900 sd = 0.0500 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.3100 sd = 0.0500 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6312 freq = 0.0000 freq = 0.6469
+allele 2 : freq = 0.3063 freq = 0.3688 freq = 0.0000 freq = 0.3531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 886: rs886
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.084130 pvalue = 0.771776 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.304173 pvalue = 0.581278 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.047821 pvalue = 0.826899 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.1542 freq = 0.0000 freq = 0.1594
+allele 2 : freq = 0.8250 freq = 0.8458 freq = 0.0000 freq = 0.8406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 887: rs887
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.358116 pvalue = 0.549555 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.065255 pvalue = 0.798375 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.256480 pvalue = 0.612548 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4483 sd = 0.0537 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+allele 2 : freq = 0.5517 sd = 0.0537 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.4375 freq = 0.0000 freq = 0.4344
+allele 2 : freq = 0.5750 freq = 0.5625 freq = 0.0000 freq = 0.5656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 888: rs888
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.502033 pvalue = 0.478608 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.545271 pvalue = 0.460256 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.362218 pvalue = 0.547277 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2050 sd = 0.0436 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+allele 2 : freq = 0.7950 sd = 0.0436 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.2375 freq = 0.0000 freq = 0.2297
+allele 2 : freq = 0.7937 freq = 0.7625 freq = 0.0000 freq = 0.7703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 889: rs889
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.301614 pvalue = 0.582872 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.572167 pvalue = 0.449399 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.004442 pvalue = 0.946861 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7850 sd = 0.0444 freq = 0.7750 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+allele 2 : freq = 0.2150 sd = 0.0444 freq = 0.2250 sd = 0.0317 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8000 freq = 0.7688 freq = 0.0000 freq = 0.7766
+allele 2 : freq = 0.2000 freq = 0.2313 freq = 0.0000 freq = 0.2234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 890: rs890
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.438769 pvalue = 0.507717 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.009306 pvalue = 0.315069 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.149987 pvalue = 0.698548 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1450 sd = 0.0380 freq = 0.1808 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+allele 2 : freq = 0.8550 sd = 0.0380 freq = 0.8192 sd = 0.0292 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1500 freq = 0.1875 freq = 0.0000 freq = 0.1781
+allele 2 : freq = 0.8500 freq = 0.8125 freq = 0.0000 freq = 0.8219
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 891: rs891
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.772057 pvalue = 0.379581 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.157233 pvalue = 0.691717 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.573064 pvalue = 0.449044 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7283 sd = 0.0480 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+allele 2 : freq = 0.2717 sd = 0.0480 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.6937 freq = 0.0000 freq = 0.6984
+allele 2 : freq = 0.2875 freq = 0.3063 freq = 0.0000 freq = 0.3016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 892: rs892
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.282699 pvalue = 0.257398 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.417707 pvalue = 0.233781 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.026872 pvalue = 0.869789 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7617 sd = 0.0460 freq = 0.7981 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+allele 2 : freq = 0.2383 sd = 0.0460 freq = 0.2019 sd = 0.0305 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7375 freq = 0.7875 freq = 0.0000 freq = 0.7750
+allele 2 : freq = 0.2625 freq = 0.2125 freq = 0.0000 freq = 0.2250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 893: rs893
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.138756 pvalue = 0.709521 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.712679 pvalue = 0.398556 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.602685 pvalue = 0.205523 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8800 sd = 0.0351 freq = 0.8923 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+allele 2 : freq = 0.1200 sd = 0.0351 freq = 0.1077 sd = 0.0235 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8812 freq = 0.9083 freq = 0.0000 freq = 0.9016
+allele 2 : freq = 0.1187 freq = 0.0917 freq = 0.0000 freq = 0.0984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 894: rs894
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.362410 pvalue = 0.547171 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.205980 pvalue = 0.649937 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.298603 pvalue = 0.0693388 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2350 sd = 0.0458 freq = 0.2154 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.2150 sd = 0.0290
+allele 2 : freq = 0.7650 sd = 0.0458 freq = 0.7846 sd = 0.0312 freq = 0.0000 sd = 0.0000 freq = 0.7850 sd = 0.0290
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2375 freq = 0.2188 freq = 0.0000 freq = 0.2234
+allele 2 : freq = 0.7625 freq = 0.7812 freq = 0.0000 freq = 0.7766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 895: rs895
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.852395 pvalue = 0.355876 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.128329 pvalue = 0.720171 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.099632 pvalue = 0.752272 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1133 sd = 0.0342 freq = 0.1462 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8867 sd = 0.0342 freq = 0.8538 sd = 0.0268 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1062 freq = 0.1187 freq = 0.0000 freq = 0.1156
+allele 2 : freq = 0.8938 freq = 0.8812 freq = 0.0000 freq = 0.8844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 896: rs896
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.076412 pvalue = 0.78222 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.213185 pvalue = 0.644282 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.243651 pvalue = 0.134164 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4050 sd = 0.0530 freq = 0.4077 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+allele 2 : freq = 0.5950 sd = 0.0530 freq = 0.5923 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.4354 freq = 0.0000 freq = 0.4297
+allele 2 : freq = 0.5875 freq = 0.5646 freq = 0.0000 freq = 0.5703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 897: rs897
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.075441 pvalue = 0.783574 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.044620 pvalue = 0.832704 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.293163 pvalue = 0.0695689 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7833 sd = 0.0445 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277
+allele 2 : freq = 0.2167 sd = 0.0445 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7937 freq = 0.7854 freq = 0.0000 freq = 0.7875
+allele 2 : freq = 0.2062 freq = 0.2146 freq = 0.0000 freq = 0.2125
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 898: rs898
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.280120 pvalue = 0.596623 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.056480 pvalue = 0.812149 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.435098 pvalue = 0.509498 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2383 sd = 0.0460 freq = 0.2558 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+allele 2 : freq = 0.7617 sd = 0.0460 freq = 0.7442 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2313 freq = 0.2417 freq = 0.0000 freq = 0.2391
+allele 2 : freq = 0.7688 freq = 0.7583 freq = 0.0000 freq = 0.7609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 899: rs899
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.015831 pvalue = 0.899873 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.496142 pvalue = 0.4812 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.299892 pvalue = 0.58395 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5050 sd = 0.0540 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.4950 sd = 0.0540 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5062 freq = 0.5417 freq = 0.0000 freq = 0.5328
+allele 2 : freq = 0.4938 freq = 0.4583 freq = 0.0000 freq = 0.4672
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 900: rs900
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.766398 pvalue = 0.0163355 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.374604 pvalue = 0.0662085 df = 1
+
+The p-value might not be exact because of the small number of allele 2 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 8.929619 pvalue = 0.00280583 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+The p-value might not be exact because of the small number of type 2 alleles in cases
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9667 sd = 0.0194 freq = 0.8981 sd = 0.0230 freq = 0.0000 sd = 0.0000 freq = 0.9050 sd = 0.0207
+allele 2 : freq = 0.0333 sd = 0.0194 freq = 0.1019 sd = 0.0230 freq = 0.0000 sd = 0.0000 freq = 0.0950 sd = 0.0207
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9688 freq = 0.9146 freq = 0.0000 freq = 0.9281
+allele 2 : freq = 0.0312 freq = 0.0854 freq = 0.0000 freq = 0.0719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 901: rs901
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.005970 pvalue = 0.938412 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.024607 pvalue = 0.87535 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.217612 pvalue = 0.640866 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8117 sd = 0.0422 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+allele 2 : freq = 0.1883 sd = 0.0422 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.8000 freq = 0.0000 freq = 0.8016
+allele 2 : freq = 0.1938 freq = 0.2000 freq = 0.0000 freq = 0.1984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 902: rs902
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.081216 pvalue = 0.775656 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.058806 pvalue = 0.808394 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.271258 pvalue = 0.602489 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8450 sd = 0.0391 freq = 0.8481 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242
+allele 2 : freq = 0.1550 sd = 0.0391 freq = 0.1519 sd = 0.0273 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8500 freq = 0.8417 freq = 0.0000 freq = 0.8438
+allele 2 : freq = 0.1500 freq = 0.1583 freq = 0.0000 freq = 0.1562
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 903: rs903
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.385127 pvalue = 0.23923 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.888431 pvalue = 0.169379 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.170393 pvalue = 0.679763 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5967 sd = 0.0530 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+allele 2 : freq = 0.4033 sd = 0.0530 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5938 freq = 0.5250 freq = 0.0000 freq = 0.5422
+allele 2 : freq = 0.4062 freq = 0.4750 freq = 0.0000 freq = 0.4578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 904: rs904
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.474881 pvalue = 0.49075 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.065029 pvalue = 0.798718 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001775 pvalue = 0.966395 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8717 sd = 0.0361 freq = 0.8731 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230
+allele 2 : freq = 0.1283 sd = 0.0361 freq = 0.1269 sd = 0.0253 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8562 freq = 0.8646 freq = 0.0000 freq = 0.8625
+allele 2 : freq = 0.1437 freq = 0.1354 freq = 0.0000 freq = 0.1375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 905: rs905
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000068 pvalue = 0.993403 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.027940 pvalue = 0.867249 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.048808 pvalue = 0.825151 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5800 sd = 0.0533 freq = 0.5788 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+allele 2 : freq = 0.4200 sd = 0.0533 freq = 0.4212 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.5771 freq = 0.0000 freq = 0.5750
+allele 2 : freq = 0.4313 freq = 0.4229 freq = 0.0000 freq = 0.4250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 906: rs906
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.298163 pvalue = 0.585036 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.043195 pvalue = 0.835358 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.177302 pvalue = 0.277906 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.5288 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.4712 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.5583 freq = 0.0000 freq = 0.5609
+allele 2 : freq = 0.4313 freq = 0.4417 freq = 0.0000 freq = 0.4391
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 907: rs907
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.265823 pvalue = 0.260552 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.510421 pvalue = 0.219075 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003365 pvalue = 0.953739 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7083 sd = 0.0491 freq = 0.6635 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.6650 sd = 0.0334
+allele 2 : freq = 0.2917 sd = 0.0491 freq = 0.3365 sd = 0.0359 freq = 0.0000 sd = 0.0000 freq = 0.3350 sd = 0.0334
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7063 freq = 0.6479 freq = 0.0000 freq = 0.6625
+allele 2 : freq = 0.2938 freq = 0.3521 freq = 0.0000 freq = 0.3375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 908: rs908
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.071382 pvalue = 0.300633 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.140882 pvalue = 0.285466 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.034176 pvalue = 0.853332 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7600 sd = 0.0461 freq = 0.8058 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2400 sd = 0.0461 freq = 0.1942 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.8000 freq = 0.0000 freq = 0.7891
+allele 2 : freq = 0.2437 freq = 0.2000 freq = 0.0000 freq = 0.2109
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 909: rs909
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.053893 pvalue = 0.816423 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.046525 pvalue = 0.829225 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.002857 pvalue = 0.957371 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1900 sd = 0.0424 freq = 0.1827 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+allele 2 : freq = 0.8100 sd = 0.0424 freq = 0.8173 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1792 freq = 0.0000 freq = 0.1812
+allele 2 : freq = 0.8125 freq = 0.8208 freq = 0.0000 freq = 0.8187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 910: rs910
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.317664 pvalue = 0.573015 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.038101 pvalue = 0.153401 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.139966 pvalue = 0.708315 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7567 sd = 0.0463 freq = 0.7519 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298
+allele 2 : freq = 0.2433 sd = 0.0463 freq = 0.2481 sd = 0.0328 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 freq = 0.7146 freq = 0.0000 freq = 0.7297
+allele 2 : freq = 0.2250 freq = 0.2854 freq = 0.0000 freq = 0.2703
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 911: rs911
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.858630 pvalue = 0.172783 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.572577 pvalue = 0.209833 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.590337 pvalue = 0.207278 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2217 sd = 0.0449 freq = 0.1673 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+allele 2 : freq = 0.7783 sd = 0.0449 freq = 0.8327 sd = 0.0284 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2188 freq = 0.1708 freq = 0.0000 freq = 0.1828
+allele 2 : freq = 0.7812 freq = 0.8292 freq = 0.0000 freq = 0.8172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 912: rs912
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.363530 pvalue = 0.546552 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.545590 pvalue = 0.213788 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.235685 pvalue = 0.62734 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8217 sd = 0.0413 freq = 0.8615 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+allele 2 : freq = 0.1783 sd = 0.0413 freq = 0.1385 sd = 0.0262 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8313 freq = 0.8771 freq = 0.0000 freq = 0.8656
+allele 2 : freq = 0.1688 freq = 0.1229 freq = 0.0000 freq = 0.1344
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 913: rs913
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.496992 pvalue = 0.480825 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.588934 pvalue = 0.207478 df = 1
+
+The p-value might not be exact because of the small number of allele 1 in cases
+
+*****************************************
+RW test
+
+RW statistic value = 0.340016 pvalue = 0.55982 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0683 sd = 0.0273 freq = 0.0692 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174
+allele 2 : freq = 0.9317 sd = 0.0273 freq = 0.9308 sd = 0.0193 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0563 freq = 0.0875 freq = 0.0000 freq = 0.0797
+allele 2 : freq = 0.9437 freq = 0.9125 freq = 0.0000 freq = 0.9203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 914: rs914
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.469517 pvalue = 0.225422 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.212891 pvalue = 0.644511 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.253118 pvalue = 0.614888 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3217 sd = 0.0505 freq = 0.2750 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+allele 2 : freq = 0.6783 sd = 0.0505 freq = 0.7250 sd = 0.0339 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3167 freq = 0.0000 freq = 0.3219
+allele 2 : freq = 0.6625 freq = 0.6833 freq = 0.0000 freq = 0.6781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 915: rs915
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.194799 pvalue = 0.658952 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.144851 pvalue = 0.703505 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.175718 pvalue = 0.675079 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4233 sd = 0.0534 freq = 0.4038 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.5767 sd = 0.0534 freq = 0.5962 sd = 0.0373 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4188 freq = 0.4000 freq = 0.0000 freq = 0.4047
+allele 2 : freq = 0.5813 freq = 0.6000 freq = 0.0000 freq = 0.5953
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 916: rs916
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.591672 pvalue = 0.207087 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.985522 pvalue = 0.320839 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.124652 pvalue = 0.0771164 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2250 sd = 0.0451 freq = 0.1712 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266
+allele 2 : freq = 0.7750 sd = 0.0451 freq = 0.8288 sd = 0.0286 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2125 freq = 0.1750 freq = 0.0000 freq = 0.1844
+allele 2 : freq = 0.7875 freq = 0.8250 freq = 0.0000 freq = 0.8156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 917: rs917
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.476660 pvalue = 0.489939 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.076641 pvalue = 0.781902 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.318198 pvalue = 0.572692 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7050 sd = 0.0493 freq = 0.7173 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.2950 sd = 0.0493 freq = 0.2827 sd = 0.0342 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.7000 freq = 0.0000 freq = 0.6969
+allele 2 : freq = 0.3125 freq = 0.3000 freq = 0.0000 freq = 0.3031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 918: rs918
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.624778 pvalue = 0.429277 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.355100 pvalue = 0.55124 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.172786 pvalue = 0.677647 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0933 sd = 0.0314 freq = 0.1173 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221
+allele 2 : freq = 0.9067 sd = 0.0314 freq = 0.8827 sd = 0.0244 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0875 freq = 0.1062 freq = 0.0000 freq = 0.1016
+allele 2 : freq = 0.9125 freq = 0.8938 freq = 0.0000 freq = 0.8984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 919: rs919
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.737715 pvalue = 0.0166044 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.955407 pvalue = 0.046721 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.761240 pvalue = 0.0524537 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8583 sd = 0.0377 freq = 0.7481 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302
+allele 2 : freq = 0.1417 sd = 0.0377 freq = 0.2519 sd = 0.0330 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8500 freq = 0.7646 freq = 0.0000 freq = 0.7859
+allele 2 : freq = 0.1500 freq = 0.2354 freq = 0.0000 freq = 0.2141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 920: rs920
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.294332 pvalue = 0.587458 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.213165 pvalue = 0.270706 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.045070 pvalue = 0.831875 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2933 sd = 0.0492 freq = 0.2942 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+allele 2 : freq = 0.7067 sd = 0.0492 freq = 0.7058 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2750 freq = 0.3250 freq = 0.0000 freq = 0.3125
+allele 2 : freq = 0.7250 freq = 0.6750 freq = 0.0000 freq = 0.6875
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 921: rs921
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.204379 pvalue = 0.137619 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.670009 pvalue = 0.196257 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.350808 pvalue = 0.553656 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 sd = 0.0529 freq = 0.5385 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+allele 2 : freq = 0.4000 sd = 0.0529 freq = 0.4615 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6188 freq = 0.5542 freq = 0.0000 freq = 0.5703
+allele 2 : freq = 0.3812 freq = 0.4458 freq = 0.0000 freq = 0.4297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 922: rs922
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.057087 pvalue = 0.81116 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.172781 pvalue = 0.677652 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.015280 pvalue = 0.901623 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4417 sd = 0.0536 freq = 0.4288 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+allele 2 : freq = 0.5583 sd = 0.0536 freq = 0.5712 sd = 0.0376 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4167 freq = 0.0000 freq = 0.4219
+allele 2 : freq = 0.5625 freq = 0.5833 freq = 0.0000 freq = 0.5781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 923: rs923
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.071935 pvalue = 0.788539 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.049842 pvalue = 0.823338 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.469425 pvalue = 0.062513 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1467 sd = 0.0382 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+allele 2 : freq = 0.8533 sd = 0.0382 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1562 freq = 0.1646 freq = 0.0000 freq = 0.1625
+allele 2 : freq = 0.8438 freq = 0.8354 freq = 0.0000 freq = 0.8375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 924: rs924
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.027265 pvalue = 0.868848 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.258703 pvalue = 0.611012 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.190935 pvalue = 0.66214 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8050 sd = 0.0428 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.1950 sd = 0.0428 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.8271 freq = 0.0000 freq = 0.8219
+allele 2 : freq = 0.1938 freq = 0.1729 freq = 0.0000 freq = 0.1781
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 925: rs925
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.462073 pvalue = 0.496657 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.481067 pvalue = 0.487939 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.353766 pvalue = 0.244621 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1917 sd = 0.0425 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275
+allele 2 : freq = 0.8083 sd = 0.0425 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2062 freq = 0.1792 freq = 0.0000 freq = 0.1859
+allele 2 : freq = 0.7937 freq = 0.8208 freq = 0.0000 freq = 0.8141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 926: rs926
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.079483 pvalue = 0.778 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.283910 pvalue = 0.257173 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.383408 pvalue = 0.535785 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3567 sd = 0.0517 freq = 0.3654 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+allele 2 : freq = 0.6433 sd = 0.0517 freq = 0.6346 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3500 freq = 0.4042 freq = 0.0000 freq = 0.3906
+allele 2 : freq = 0.6500 freq = 0.5958 freq = 0.0000 freq = 0.6094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 927: rs927
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000162 pvalue = 0.989846 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.381802 pvalue = 0.53664 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.179811 pvalue = 0.671536 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2183 sd = 0.0446 freq = 0.2538 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+allele 2 : freq = 0.7817 sd = 0.0446 freq = 0.7462 sd = 0.0331 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2167 freq = 0.0000 freq = 0.2234
+allele 2 : freq = 0.7562 freq = 0.7833 freq = 0.0000 freq = 0.7766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 928: rs928
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.366643 pvalue = 0.54484 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.652446 pvalue = 0.198626 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.973208 pvalue = 0.323881 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4783 sd = 0.0540 freq = 0.4923 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353
+allele 2 : freq = 0.5217 sd = 0.0540 freq = 0.5077 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.5333 freq = 0.0000 freq = 0.5172
+allele 2 : freq = 0.5312 freq = 0.4667 freq = 0.0000 freq = 0.4828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 929: rs929
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.209212 pvalue = 0.647386 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.015607 pvalue = 0.900581 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000000 pvalue = 1 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.4500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4500 sd = 0.0352
+allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.5500 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5500 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4750 freq = 0.4688 freq = 0.0000 freq = 0.4703
+allele 2 : freq = 0.5250 freq = 0.5312 freq = 0.0000 freq = 0.5297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 930: rs930
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.182884 pvalue = 0.668906 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.073575 pvalue = 0.786201 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.139459 pvalue = 0.70882 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7133 sd = 0.0488 freq = 0.6865 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+allele 2 : freq = 0.2867 sd = 0.0488 freq = 0.3135 sd = 0.0352 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7188 freq = 0.7063 freq = 0.0000 freq = 0.7094
+allele 2 : freq = 0.2812 freq = 0.2938 freq = 0.0000 freq = 0.2906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 931: rs931
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.059207 pvalue = 0.807754 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.021486 pvalue = 0.883462 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.150134 pvalue = 0.698408 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7783 sd = 0.0449 freq = 0.7635 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300
+allele 2 : freq = 0.2217 sd = 0.0449 freq = 0.2365 sd = 0.0323 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7750 freq = 0.7688 freq = 0.0000 freq = 0.7703
+allele 2 : freq = 0.2250 freq = 0.2313 freq = 0.0000 freq = 0.2297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 932: rs932
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.664095 pvalue = 0.415118 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.334116 pvalue = 0.563245 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.823042 pvalue = 0.364292 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7550 sd = 0.0465 freq = 0.7538 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304
+allele 2 : freq = 0.2450 sd = 0.0465 freq = 0.2462 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7625 freq = 0.0000 freq = 0.7688
+allele 2 : freq = 0.2125 freq = 0.2375 freq = 0.0000 freq = 0.2313
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 933: rs933
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.321893 pvalue = 0.570472 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.007216 pvalue = 0.932302 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.078584 pvalue = 0.299014 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5717 sd = 0.0534 freq = 0.6192 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+allele 2 : freq = 0.4283 sd = 0.0534 freq = 0.3808 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5750 freq = 0.5708 freq = 0.0000 freq = 0.5719
+allele 2 : freq = 0.4250 freq = 0.4292 freq = 0.0000 freq = 0.4281
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 934: rs934
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.710003 pvalue = 0.190985 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.623665 pvalue = 0.202582 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.416780 pvalue = 0.518548 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3650 sd = 0.0520 freq = 0.3846 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345
+allele 2 : freq = 0.6350 sd = 0.0520 freq = 0.6154 sd = 0.0370 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.4000 freq = 0.0000 freq = 0.3844
+allele 2 : freq = 0.6625 freq = 0.6000 freq = 0.0000 freq = 0.6156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 935: rs935
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.400819 pvalue = 0.526666 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.291560 pvalue = 0.589222 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.181010 pvalue = 0.670507 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.4538 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353
+allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.5462 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4646 freq = 0.0000 freq = 0.4578
+allele 2 : freq = 0.5625 freq = 0.5354 freq = 0.0000 freq = 0.5422
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 936: rs936
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.081049 pvalue = 0.775881 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.424472 pvalue = 0.514714 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.961765 pvalue = 0.326743 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1017 sd = 0.0326 freq = 0.0904 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.0900 sd = 0.0202
+allele 2 : freq = 0.8983 sd = 0.0326 freq = 0.9096 sd = 0.0218 freq = 0.0000 sd = 0.0000 freq = 0.9100 sd = 0.0202
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0875 freq = 0.1062 freq = 0.0000 freq = 0.1016
+allele 2 : freq = 0.9125 freq = 0.8938 freq = 0.0000 freq = 0.8984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 937: rs937
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.022701 pvalue = 0.880238 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.049842 pvalue = 0.823338 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.027549 pvalue = 0.868174 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8317 sd = 0.0404 freq = 0.8346 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1683 sd = 0.0404 freq = 0.1654 sd = 0.0282 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.8167 freq = 0.0000 freq = 0.8187
+allele 2 : freq = 0.1750 freq = 0.1833 freq = 0.0000 freq = 0.1812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 938: rs938
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.015937 pvalue = 0.899541 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003366 pvalue = 0.953734 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.552751 pvalue = 0.21273 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8350 sd = 0.0401 freq = 0.8558 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252
+allele 2 : freq = 0.1650 sd = 0.0401 freq = 0.1442 sd = 0.0267 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8417 freq = 0.0000 freq = 0.8422
+allele 2 : freq = 0.1562 freq = 0.1583 freq = 0.0000 freq = 0.1578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 939: rs939
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.217058 pvalue = 0.269939 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.267089 pvalue = 0.260314 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.376020 pvalue = 0.24078 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6667 sd = 0.0509 freq = 0.6327 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.6450 sd = 0.0338
+allele 2 : freq = 0.3333 sd = 0.0509 freq = 0.3673 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.3550 sd = 0.0338
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6875 freq = 0.6333 freq = 0.0000 freq = 0.6469
+allele 2 : freq = 0.3125 freq = 0.3667 freq = 0.0000 freq = 0.3531
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 940: rs940
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.379026 pvalue = 0.122974 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.845260 pvalue = 0.0916438 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.241849 pvalue = 0.622874 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1933 sd = 0.0427 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295
+allele 2 : freq = 0.8067 sd = 0.0427 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1750 freq = 0.2458 freq = 0.0000 freq = 0.2281
+allele 2 : freq = 0.8250 freq = 0.7542 freq = 0.0000 freq = 0.7719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 941: rs941
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.043295 pvalue = 0.835171 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.024607 pvalue = 0.87535 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.838506 pvalue = 0.359824 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1867 sd = 0.0421 freq = 0.1885 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+allele 2 : freq = 0.8133 sd = 0.0421 freq = 0.8115 sd = 0.0297 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1938 freq = 0.0000 freq = 0.1922
+allele 2 : freq = 0.8125 freq = 0.8063 freq = 0.0000 freq = 0.8078
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 942: rs942
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.307308 pvalue = 0.252883 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.748834 pvalue = 0.186023 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.429604 pvalue = 0.512183 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8183 sd = 0.0416 freq = 0.7788 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.1817 sd = 0.0416 freq = 0.2212 sd = 0.0315 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8250 freq = 0.7708 freq = 0.0000 freq = 0.7844
+allele 2 : freq = 0.1750 freq = 0.2292 freq = 0.0000 freq = 0.2156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 943: rs943
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.027628 pvalue = 0.867986 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.107018 pvalue = 0.743564 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.073026 pvalue = 0.786981 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1800 sd = 0.0415 freq = 0.1731 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+allele 2 : freq = 0.8200 sd = 0.0415 freq = 0.8269 sd = 0.0287 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.2000 freq = 0.0000 freq = 0.1969
+allele 2 : freq = 0.8125 freq = 0.8000 freq = 0.0000 freq = 0.8031
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 944: rs944
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.005669 pvalue = 0.939979 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.318826 pvalue = 0.572314 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.009253 pvalue = 0.315082 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3583 sd = 0.0518 freq = 0.3269 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+allele 2 : freq = 0.6417 sd = 0.0518 freq = 0.6731 sd = 0.0356 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3438 freq = 0.3167 freq = 0.0000 freq = 0.3234
+allele 2 : freq = 0.6562 freq = 0.6833 freq = 0.0000 freq = 0.6766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 945: rs945
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.147927 pvalue = 0.700524 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.072695 pvalue = 0.787453 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.891765 pvalue = 0.344999 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8033 sd = 0.0429 freq = 0.8135 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.8200 sd = 0.0272
+allele 2 : freq = 0.1967 sd = 0.0429 freq = 0.1865 sd = 0.0296 freq = 0.0000 sd = 0.0000 freq = 0.1800 sd = 0.0272
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8063 freq = 0.8167 freq = 0.0000 freq = 0.8141
+allele 2 : freq = 0.1938 freq = 0.1833 freq = 0.0000 freq = 0.1859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 946: rs946
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.018204 pvalue = 0.892672 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.017902 pvalue = 0.893563 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000217 pvalue = 0.988242 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6817 sd = 0.0503 freq = 0.6808 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328
+allele 2 : freq = 0.3183 sd = 0.0503 freq = 0.3192 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.6687 freq = 0.0000 freq = 0.6703
+allele 2 : freq = 0.3250 freq = 0.3312 freq = 0.0000 freq = 0.3297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 947: rs947
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.100947 pvalue = 0.750697 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.010004 pvalue = 0.920327 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.836097 pvalue = 0.175409 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.7885 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.2115 sd = 0.0310 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7625 freq = 0.7583 freq = 0.0000 freq = 0.7594
+allele 2 : freq = 0.2375 freq = 0.2417 freq = 0.0000 freq = 0.2406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 948: rs948
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.223484 pvalue = 0.135926 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.160526 pvalue = 0.281356 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.566984 pvalue = 0.45146 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5550 sd = 0.0537 freq = 0.4942 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+allele 2 : freq = 0.4450 sd = 0.0537 freq = 0.5058 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5687 freq = 0.5146 freq = 0.0000 freq = 0.5281
+allele 2 : freq = 0.4313 freq = 0.4854 freq = 0.0000 freq = 0.4719
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 949: rs949
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000019 pvalue = 0.996501 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.112401 pvalue = 0.737427 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.580034 pvalue = 0.446299 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5983 sd = 0.0530 freq = 0.5615 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5750 sd = 0.0350
+allele 2 : freq = 0.4017 sd = 0.0530 freq = 0.4385 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4250 sd = 0.0350
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5813 freq = 0.5979 freq = 0.0000 freq = 0.5938
+allele 2 : freq = 0.4188 freq = 0.4021 freq = 0.0000 freq = 0.4062
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 950: rs950
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.312339 pvalue = 0.576249 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.136250 pvalue = 0.712037 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.562868 pvalue = 0.211246 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7483 sd = 0.0469 freq = 0.7077 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.2517 sd = 0.0469 freq = 0.2923 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7438 freq = 0.7271 freq = 0.0000 freq = 0.7312
+allele 2 : freq = 0.2562 freq = 0.2729 freq = 0.0000 freq = 0.2687
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 951: rs951
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.006995 pvalue = 0.933344 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.008175 pvalue = 0.927957 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.273339 pvalue = 0.601101 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.6981 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.3019 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6937 freq = 0.6896 freq = 0.0000 freq = 0.6906
+allele 2 : freq = 0.3063 freq = 0.3104 freq = 0.0000 freq = 0.3094
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 952: rs952
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.000514 pvalue = 0.981911 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.020333 pvalue = 0.886612 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.002220 pvalue = 0.962421 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7467 sd = 0.0470 freq = 0.7500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+allele 2 : freq = 0.2533 sd = 0.0470 freq = 0.2500 sd = 0.0329 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7438 freq = 0.7375 freq = 0.0000 freq = 0.7391
+allele 2 : freq = 0.2562 freq = 0.2625 freq = 0.0000 freq = 0.2609
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 953: rs953
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.065838 pvalue = 0.797496 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.006951 pvalue = 0.933555 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.273968 pvalue = 0.600683 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4450 sd = 0.0537 freq = 0.4519 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5550 sd = 0.0537 freq = 0.5481 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4313 freq = 0.4354 freq = 0.0000 freq = 0.4344
+allele 2 : freq = 0.5687 freq = 0.5646 freq = 0.0000 freq = 0.5656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 954: rs954
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.197771 pvalue = 0.656526 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.011891 pvalue = 0.913166 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.292103 pvalue = 0.588876 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1650 sd = 0.0401 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+allele 2 : freq = 0.8350 sd = 0.0401 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1562 freq = 0.1604 freq = 0.0000 freq = 0.1594
+allele 2 : freq = 0.8438 freq = 0.8396 freq = 0.0000 freq = 0.8406
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 955: rs955
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.915665 pvalue = 0.338616 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.928830 pvalue = 0.335167 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.445184 pvalue = 0.504631 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.2938 freq = 0.0000 freq = 0.2828
+allele 2 : freq = 0.7500 freq = 0.7063 freq = 0.0000 freq = 0.7172
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 956: rs956
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.244035 pvalue = 0.621307 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.005850 pvalue = 0.315899 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003050 pvalue = 0.955954 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 sd = 0.0534 freq = 0.4442 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351
+allele 2 : freq = 0.5750 sd = 0.0534 freq = 0.5558 sd = 0.0377 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4250 freq = 0.4750 freq = 0.0000 freq = 0.4625
+allele 2 : freq = 0.5750 freq = 0.5250 freq = 0.0000 freq = 0.5375
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 957: rs957
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.990927 pvalue = 0.158244 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.754293 pvalue = 0.0526721 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.720790 pvalue = 0.395885 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5650 sd = 0.0535 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348
+allele 2 : freq = 0.4350 sd = 0.0535 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5437 freq = 0.6396 freq = 0.0000 freq = 0.6156
+allele 2 : freq = 0.4562 freq = 0.3604 freq = 0.0000 freq = 0.3844
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 958: rs958
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 6.608352 pvalue = 0.0101502 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.764266 pvalue = 0.0163553 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.037605 pvalue = 0.846239 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2433 sd = 0.0463 freq = 0.1538 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275
+allele 2 : freq = 0.7567 sd = 0.0463 freq = 0.8462 sd = 0.0274 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2687 freq = 0.1750 freq = 0.0000 freq = 0.1984
+allele 2 : freq = 0.7312 freq = 0.8250 freq = 0.0000 freq = 0.8016
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 959: rs959
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.086276 pvalue = 0.768965 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.207914 pvalue = 0.648407 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.108058 pvalue = 0.742366 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4900 sd = 0.0540 freq = 0.4788 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.5100 sd = 0.0540 freq = 0.5212 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4938 freq = 0.4708 freq = 0.0000 freq = 0.4766
+allele 2 : freq = 0.5062 freq = 0.5292 freq = 0.0000 freq = 0.5234
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 960: rs960
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.509870 pvalue = 0.219159 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.989178 pvalue = 0.319943 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.273339 pvalue = 0.601101 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 sd = 0.0468 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.7500 sd = 0.0468 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.2958 freq = 0.0000 freq = 0.2844
+allele 2 : freq = 0.7500 freq = 0.7042 freq = 0.0000 freq = 0.7156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 961: rs961
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.963315 pvalue = 0.0851731 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 4.213542 pvalue = 0.0401025 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.139158 pvalue = 0.709119 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7583 sd = 0.0462 freq = 0.8058 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285
+allele 2 : freq = 0.2417 sd = 0.0462 freq = 0.1942 sd = 0.0300 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7438 freq = 0.8271 freq = 0.0000 freq = 0.8063
+allele 2 : freq = 0.2562 freq = 0.1729 freq = 0.0000 freq = 0.1938
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 962: rs962
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.392849 pvalue = 0.237925 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.301291 pvalue = 0.253978 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 8.170177 pvalue = 0.00425847 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7933 sd = 0.0437 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308
+allele 2 : freq = 0.2067 sd = 0.0437 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7875 freq = 0.7375 freq = 0.0000 freq = 0.7500
+allele 2 : freq = 0.2125 freq = 0.2625 freq = 0.0000 freq = 0.2500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 963: rs963
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.898764 pvalue = 0.0886475 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.352355 pvalue = 0.125094 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 5.045729 pvalue = 0.0246867 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4283 sd = 0.0534 freq = 0.4981 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353
+allele 2 : freq = 0.5717 sd = 0.0534 freq = 0.5019 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4125 freq = 0.4896 freq = 0.0000 freq = 0.4703
+allele 2 : freq = 0.5875 freq = 0.5104 freq = 0.0000 freq = 0.5297
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 964: rs964
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.549831 pvalue = 0.458387 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.386309 pvalue = 0.534246 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.346598 pvalue = 0.556046 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5217 sd = 0.0540 freq = 0.5038 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+allele 2 : freq = 0.4783 sd = 0.0540 freq = 0.4962 sd = 0.0380 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.5062 freq = 0.0000 freq = 0.5141
+allele 2 : freq = 0.4625 freq = 0.4938 freq = 0.0000 freq = 0.4859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 965: rs965
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.035589 pvalue = 0.850367 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.095116 pvalue = 0.757771 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.001907 pvalue = 0.965165 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3433 sd = 0.0513 freq = 0.3288 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+allele 2 : freq = 0.6567 sd = 0.0513 freq = 0.6712 sd = 0.0357 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3250 freq = 0.3396 freq = 0.0000 freq = 0.3359
+allele 2 : freq = 0.6750 freq = 0.6604 freq = 0.0000 freq = 0.6641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 966: rs966
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.264488 pvalue = 0.260803 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 2.789861 pvalue = 0.0948624 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.151624 pvalue = 0.28321 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7200 sd = 0.0485 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316
+allele 2 : freq = 0.2800 sd = 0.0485 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7562 freq = 0.6813 freq = 0.0000 freq = 0.7000
+allele 2 : freq = 0.2437 freq = 0.3187 freq = 0.0000 freq = 0.3000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 967: rs967
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.098610 pvalue = 0.753504 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.297274 pvalue = 0.585597 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.032456 pvalue = 0.857031 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1767 sd = 0.0412 freq = 0.1904 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269
+allele 2 : freq = 0.8233 sd = 0.0412 freq = 0.8096 sd = 0.0298 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1688 freq = 0.1896 freq = 0.0000 freq = 0.1844
+allele 2 : freq = 0.8313 freq = 0.8104 freq = 0.0000 freq = 0.8156
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 968: rs968
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.004964 pvalue = 0.943829 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 3.126523 pvalue = 0.0770279 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2667 sd = 0.0478 freq = 0.2673 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+allele 2 : freq = 0.7333 sd = 0.0478 freq = 0.7327 sd = 0.0336 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2687 freq = 0.2687 freq = 0.0000 freq = 0.2687
+allele 2 : freq = 0.7312 freq = 0.7312 freq = 0.0000 freq = 0.7312
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 969: rs969
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.045650 pvalue = 0.830813 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.003115 pvalue = 0.95549 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.326842 pvalue = 0.567524 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8367 sd = 0.0399 freq = 0.8385 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.8350 sd = 0.0262
+allele 2 : freq = 0.1633 sd = 0.0399 freq = 0.1615 sd = 0.0280 freq = 0.0000 sd = 0.0000 freq = 0.1650 sd = 0.0262
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8438 freq = 0.8417 freq = 0.0000 freq = 0.8422
+allele 2 : freq = 0.1562 freq = 0.1583 freq = 0.0000 freq = 0.1578
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 970: rs970
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.483112 pvalue = 0.487016 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.841087 pvalue = 0.359086 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.027321 pvalue = 0.868716 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4367 sd = 0.0536 freq = 0.4558 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351
+allele 2 : freq = 0.5633 sd = 0.0536 freq = 0.5442 sd = 0.0378 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4688 freq = 0.4229 freq = 0.0000 freq = 0.4344
+allele 2 : freq = 0.5312 freq = 0.5771 freq = 0.0000 freq = 0.5656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 971: rs971
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.746424 pvalue = 0.186327 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.859713 pvalue = 0.172658 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.442453 pvalue = 0.505941 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0800 sd = 0.0293 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+allele 2 : freq = 0.9200 sd = 0.0293 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.0813 freq = 0.1250 freq = 0.0000 freq = 0.1141
+allele 2 : freq = 0.9187 freq = 0.8750 freq = 0.0000 freq = 0.8859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 972: rs972
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.809071 pvalue = 0.368395 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.459845 pvalue = 0.497696 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.612144 pvalue = 0.204191 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3183 sd = 0.0503 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.6817 sd = 0.0503 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3375 freq = 0.3063 freq = 0.0000 freq = 0.3141
+allele 2 : freq = 0.6625 freq = 0.6937 freq = 0.0000 freq = 0.6859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 973: rs973
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.350022 pvalue = 0.554101 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.269890 pvalue = 0.603405 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.000460 pvalue = 0.982881 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1350 sd = 0.0369 freq = 0.1154 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.1150 sd = 0.0226
+allele 2 : freq = 0.8650 sd = 0.0369 freq = 0.8846 sd = 0.0243 freq = 0.0000 sd = 0.0000 freq = 0.8850 sd = 0.0226
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1313 freq = 0.1146 freq = 0.0000 freq = 0.1187
+allele 2 : freq = 0.8688 freq = 0.8854 freq = 0.0000 freq = 0.8812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 974: rs974
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.116741 pvalue = 0.732597 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.000000 pvalue = 1 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.144990 pvalue = 0.70337 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6117 sd = 0.0526 freq = 0.6212 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343
+allele 2 : freq = 0.3883 sd = 0.0526 freq = 0.3788 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.6000 freq = 0.0000 freq = 0.6000
+allele 2 : freq = 0.4000 freq = 0.4000 freq = 0.0000 freq = 0.4000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 975: rs975
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.838684 pvalue = 0.359773 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.642959 pvalue = 0.422641 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.867520 pvalue = 0.171759 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4467 sd = 0.0537 freq = 0.3904 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347
+allele 2 : freq = 0.5533 sd = 0.0537 freq = 0.6096 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4437 freq = 0.4042 freq = 0.0000 freq = 0.4141
+allele 2 : freq = 0.5563 freq = 0.5958 freq = 0.0000 freq = 0.5859
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 976: rs976
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.319470 pvalue = 0.571927 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.139361 pvalue = 0.708917 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.799439 pvalue = 0.17978 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7033 sd = 0.0493 freq = 0.7404 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314
+allele 2 : freq = 0.2967 sd = 0.0493 freq = 0.2596 sd = 0.0333 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7063 freq = 0.7229 freq = 0.0000 freq = 0.7188
+allele 2 : freq = 0.2938 freq = 0.2771 freq = 0.0000 freq = 0.2812
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 977: rs977
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.056014 pvalue = 0.812911 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.024607 pvalue = 0.87535 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.096716 pvalue = 0.755806 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8217 sd = 0.0413 freq = 0.8173 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280
+allele 2 : freq = 0.1783 sd = 0.0413 freq = 0.1827 sd = 0.0294 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.8187 freq = 0.8250 freq = 0.0000 freq = 0.8234
+allele 2 : freq = 0.1812 freq = 0.1750 freq = 0.0000 freq = 0.1766
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 978: rs978
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.460468 pvalue = 0.497405 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 3.238076 pvalue = 0.0719451 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.513441 pvalue = 0.473653 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7283 sd = 0.0480 freq = 0.7019 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.2717 sd = 0.0480 freq = 0.2981 sd = 0.0347 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7250 freq = 0.6438 freq = 0.0000 freq = 0.6641
+allele 2 : freq = 0.2750 freq = 0.3563 freq = 0.0000 freq = 0.3359
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 979: rs979
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.229146 pvalue = 0.135429 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.842476 pvalue = 0.35869 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.001664 pvalue = 0.316908 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6533 sd = 0.0514 freq = 0.7135 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319
+allele 2 : freq = 0.3467 sd = 0.0514 freq = 0.2865 sd = 0.0343 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 freq = 0.6917 freq = 0.0000 freq = 0.6813
+allele 2 : freq = 0.3500 freq = 0.3083 freq = 0.0000 freq = 0.3187
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 980: rs980
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.869985 pvalue = 0.0154012 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 5.023297 pvalue = 0.0250085 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 2.152546 pvalue = 0.142334 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5050 sd = 0.0540 freq = 0.3635 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346
+allele 2 : freq = 0.4950 sd = 0.0540 freq = 0.6365 sd = 0.0365 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5000 freq = 0.3896 freq = 0.0000 freq = 0.4172
+allele 2 : freq = 0.5000 freq = 0.6104 freq = 0.0000 freq = 0.5828
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 981: rs981
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.007835 pvalue = 0.929468 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.009156 pvalue = 0.923769 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.056230 pvalue = 0.812557 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2483 sd = 0.0467 freq = 0.2404 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306
+allele 2 : freq = 0.7517 sd = 0.0467 freq = 0.7596 sd = 0.0325 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2437 freq = 0.2396 freq = 0.0000 freq = 0.2406
+allele 2 : freq = 0.7562 freq = 0.7604 freq = 0.0000 freq = 0.7594
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 982: rs982
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 2.298922 pvalue = 0.129464 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.885947 pvalue = 0.16966 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.885757 pvalue = 0.34663 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7517 sd = 0.0467 freq = 0.8038 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.7900 sd = 0.0288
+allele 2 : freq = 0.2483 sd = 0.0467 freq = 0.1962 sd = 0.0302 freq = 0.0000 sd = 0.0000 freq = 0.2100 sd = 0.0288
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7375 freq = 0.7937 freq = 0.0000 freq = 0.7797
+allele 2 : freq = 0.2625 freq = 0.2062 freq = 0.0000 freq = 0.2203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 983: rs983
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.015412 pvalue = 0.901199 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.171676 pvalue = 0.678627 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.263577 pvalue = 0.607673 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1850 sd = 0.0419 freq = 0.2000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283
+allele 2 : freq = 0.8150 sd = 0.0419 freq = 0.8000 sd = 0.0304 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1875 freq = 0.1708 freq = 0.0000 freq = 0.1750
+allele 2 : freq = 0.8125 freq = 0.8292 freq = 0.0000 freq = 0.8250
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 984: rs984
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.890255 pvalue = 0.169173 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.839380 pvalue = 0.175024 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.293212 pvalue = 0.588169 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1383 sd = 0.0373 freq = 0.1750 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.1600 sd = 0.0259
+allele 2 : freq = 0.8617 sd = 0.0373 freq = 0.8250 sd = 0.0289 freq = 0.0000 sd = 0.0000 freq = 0.8400 sd = 0.0259
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1187 freq = 0.1688 freq = 0.0000 freq = 0.1562
+allele 2 : freq = 0.8812 freq = 0.8313 freq = 0.0000 freq = 0.8438
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 985: rs985
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 5.610408 pvalue = 0.0178541 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 7.604816 pvalue = 0.00582126 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.089254 pvalue = 0.765128 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3783 sd = 0.0524 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324
+allele 2 : freq = 0.6217 sd = 0.0524 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3812 freq = 0.2542 freq = 0.0000 freq = 0.2859
+allele 2 : freq = 0.6188 freq = 0.7458 freq = 0.0000 freq = 0.7141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 986: rs986
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.295876 pvalue = 0.586479 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.228140 pvalue = 0.632906 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.591954 pvalue = 0.441665 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1633 sd = 0.0399 freq = 0.1327 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245
+allele 2 : freq = 0.8367 sd = 0.0399 freq = 0.8673 sd = 0.0258 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1562 freq = 0.1396 freq = 0.0000 freq = 0.1437
+allele 2 : freq = 0.8438 freq = 0.8604 freq = 0.0000 freq = 0.8562
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 987: rs987
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.249216 pvalue = 0.617628 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.055088 pvalue = 0.814436 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.086848 pvalue = 0.768223 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2933 sd = 0.0492 freq = 0.2615 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.2650 sd = 0.0312
+allele 2 : freq = 0.7067 sd = 0.0492 freq = 0.7385 sd = 0.0334 freq = 0.0000 sd = 0.0000 freq = 0.7350 sd = 0.0312
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2875 freq = 0.2771 freq = 0.0000 freq = 0.2797
+allele 2 : freq = 0.7125 freq = 0.7229 freq = 0.0000 freq = 0.7203
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 988: rs988
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.027546 pvalue = 0.86818 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.008255 pvalue = 0.927608 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.032444 pvalue = 0.857056 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7100 sd = 0.0490 freq = 0.7096 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+allele 2 : freq = 0.2900 sd = 0.0490 freq = 0.2904 sd = 0.0345 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7125 freq = 0.7083 freq = 0.0000 freq = 0.7094
+allele 2 : freq = 0.2875 freq = 0.2917 freq = 0.0000 freq = 0.2906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 989: rs989
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.492887 pvalue = 0.482642 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.028248 pvalue = 0.866528 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.444102 pvalue = 0.505149 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9217 sd = 0.0290 freq = 0.9327 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.9350 sd = 0.0174
+allele 2 : freq = 0.0783 sd = 0.0290 freq = 0.0673 sd = 0.0190 freq = 0.0000 sd = 0.0000 freq = 0.0650 sd = 0.0174
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.9125 freq = 0.9083 freq = 0.0000 freq = 0.9094
+allele 2 : freq = 0.0875 freq = 0.0917 freq = 0.0000 freq = 0.0906
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 990: rs990
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.497315 pvalue = 0.0614684 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.987740 pvalue = 0.158577 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.979973 pvalue = 0.322205 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2833 sd = 0.0487 freq = 0.3346 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332
+allele 2 : freq = 0.7167 sd = 0.0487 freq = 0.6654 sd = 0.0358 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.2500 freq = 0.3167 freq = 0.0000 freq = 0.3000
+allele 2 : freq = 0.7500 freq = 0.6833 freq = 0.0000 freq = 0.7000
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 991: rs991
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.884205 pvalue = 0.347053 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.744980 pvalue = 0.38807 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.632886 pvalue = 0.426299 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3033 sd = 0.0497 freq = 0.3038 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322
+allele 2 : freq = 0.6967 sd = 0.0497 freq = 0.6962 sd = 0.0349 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.2917 freq = 0.0000 freq = 0.3016
+allele 2 : freq = 0.6687 freq = 0.7083 freq = 0.0000 freq = 0.6984
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 992: rs992
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.393726 pvalue = 0.237777 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.913087 pvalue = 0.339297 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.005149 pvalue = 0.942794 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 sd = 0.0529 freq = 0.6558 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337
+allele 2 : freq = 0.4000 sd = 0.0529 freq = 0.3442 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6000 freq = 0.6458 freq = 0.0000 freq = 0.6344
+allele 2 : freq = 0.4000 freq = 0.3542 freq = 0.0000 freq = 0.3656
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 993: rs993
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.621670 pvalue = 0.202859 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.354605 pvalue = 0.244475 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.003018 pvalue = 0.956187 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5483 sd = 0.0538 freq = 0.5192 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5400 sd = 0.0352
+allele 2 : freq = 0.4517 sd = 0.0538 freq = 0.4808 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4600 sd = 0.0352
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5938 freq = 0.5354 freq = 0.0000 freq = 0.5500
+allele 2 : freq = 0.4062 freq = 0.4646 freq = 0.0000 freq = 0.4500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 994: rs994
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 1.165258 pvalue = 0.280378 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.468789 pvalue = 0.493545 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.019993 pvalue = 0.887557 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6800 sd = 0.0504 freq = 0.6058 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342
+allele 2 : freq = 0.3200 sd = 0.0504 freq = 0.3942 sd = 0.0371 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6750 freq = 0.6417 freq = 0.0000 freq = 0.6500
+allele 2 : freq = 0.3250 freq = 0.3583 freq = 0.0000 freq = 0.3500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 995: rs995
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 3.178786 pvalue = 0.0746001 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.669067 pvalue = 0.196383 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.628494 pvalue = 0.427908 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7900 sd = 0.0440 freq = 0.7115 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.7200 sd = 0.0317
+allele 2 : freq = 0.2100 sd = 0.0440 freq = 0.2885 sd = 0.0344 freq = 0.0000 sd = 0.0000 freq = 0.2800 sd = 0.0317
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.7937 freq = 0.7354 freq = 0.0000 freq = 0.7500
+allele 2 : freq = 0.2062 freq = 0.2646 freq = 0.0000 freq = 0.2500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 996: rs996
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.969221 pvalue = 0.324875 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.869733 pvalue = 0.171506 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 6.625281 pvalue = 0.0100541 df = 1
+
+Frequency of allele 1 is the same in cases and controls (quasi-score associated to this allele is 0)
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5367 sd = 0.0539 freq = 0.4750 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354
+allele 2 : freq = 0.4633 sd = 0.0539 freq = 0.5250 sd = 0.0379 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.5375 freq = 0.4688 freq = 0.0000 freq = 0.4859
+allele 2 : freq = 0.4625 freq = 0.5312 freq = 0.0000 freq = 0.5141
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 997: rs997
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.168285 pvalue = 0.68164 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.273496 pvalue = 0.600996 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.010161 pvalue = 0.919709 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3333 sd = 0.0509 freq = 0.3423 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336
+allele 2 : freq = 0.6667 sd = 0.0509 freq = 0.6577 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.3312 freq = 0.3563 freq = 0.0000 freq = 0.3500
+allele 2 : freq = 0.6687 freq = 0.6438 freq = 0.0000 freq = 0.6500
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 998: rs998
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.039320 pvalue = 0.842817 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.086331 pvalue = 0.768894 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.196974 pvalue = 0.657175 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4533 sd = 0.0538 freq = 0.4192 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.4200 sd = 0.0349
+allele 2 : freq = 0.5467 sd = 0.0538 freq = 0.5808 sd = 0.0375 freq = 0.0000 sd = 0.0000 freq = 0.5800 sd = 0.0349
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.4375 freq = 0.4521 freq = 0.0000 freq = 0.4484
+allele 2 : freq = 0.5625 freq = 0.5479 freq = 0.0000 freq = 0.5516
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 999: rs999
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.931930 pvalue = 0.334362 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 1.823302 pvalue = 0.176921 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 1.661334 pvalue = 0.197423 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1800 sd = 0.0415 freq = 0.2269 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293
+allele 2 : freq = 0.8200 sd = 0.0415 freq = 0.7731 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.1938 freq = 0.2500 freq = 0.0000 freq = 0.2359
+allele 2 : freq = 0.8063 freq = 0.7500 freq = 0.0000 freq = 0.7641
+*****************************************
+
+
+
+
+****************************************
+
+Analysis of Marker 1000: rs1000
+
+****************************************
+There are 80 affected individuals, 240 unaffected individuals, and 0 individuals of unknown phenotype available.
+
+*****************************************
+RM test
+
+RM statistic value = 0.027542 pvalue = 0.86819 df = 1
+
+
+*****************************************
+RCHI test
+
+RCHI statistic value = 0.116009 pvalue = 0.733404 df = 1
+
+*****************************************
+RW test
+
+RW statistic value = 0.016030 pvalue = 0.899249 df = 1
+
+
+*****************************************
+allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6500 sd = 0.0515 freq = 0.6231 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344
+allele 2 : freq = 0.3500 sd = 0.0515 freq = 0.3769 sd = 0.0368 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344
+*****************************************
+allele frequency estimates using naive counting in
+ cases unaffected controls unknown controls all sample
+allele 1 : freq = 0.6312 freq = 0.6479 freq = 0.0000 freq = 0.6438
+allele 2 : freq = 0.3688 freq = 0.3521 freq = 0.0000 freq = 0.3563
+*****************************************
+
+
+
+
diff --git a/ROADTRIPStest.pvalues.ex b/ROADTRIPStest.pvalues.ex
new file mode 100644
index 0000000..fa4e528
--- /dev/null
+++ b/ROADTRIPStest.pvalues.ex
@@ -0,0 +1,1001 @@
+SNP NAME RM RCHI RW
+1 rs1 0.0781983 0.0823211 0.098853
+2 rs2 0.989035 0.730397 0.444565
+3 rs3 0.201904 0.196257 0.314648
+4 rs4 0.851869 0.821171 0.204191
+5 rs5 0.597268 0.332049 0.904333
+6 rs6 0.71358 0.964858 0.849895
+7 rs7 0.323236 0.212739 0.102429
+8 rs8 0.842154 0.770671 0.491466
+9 rs9 0.205691 0.0759699 0.240913
+10 rs10 0.819765 0.878723 0.986591
+11 rs11 0.396603 0.320839 0.688483
+12 rs12 0.414757 0.517372 0.679189
+13 rs13 0.420386 0.709165 0.88027
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diff --git a/ROADTRIPStest.testvalues.ex b/ROADTRIPStest.testvalues.ex
new file mode 100644
index 0000000..e2c72ba
--- /dev/null
+++ b/ROADTRIPStest.testvalues.ex
@@ -0,0 +1,1001 @@
+SNP NAME RM RCHI RW
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+904 rs904 0.474881 0.0650286 0.00177493
+905 rs905 6.83558e-05 0.0279403 0.0488076
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+913 rs913 0.496992 1.58893 0.340016
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+917 rs917 0.47666 0.0766408 0.318198
+918 rs918 0.624778 0.3551 0.172786
+919 rs919 5.73772 3.95541 3.76124
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+929 rs929 0.209212 0.0156069 5.25065e-32
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+932 rs932 0.664095 0.334116 0.823042
+933 rs933 0.321893 0.00721629 1.07858
+934 rs934 1.71 1.62366 0.41678
+935 rs935 0.400819 0.29156 0.18101
+936 rs936 0.0810492 0.424472 0.961765
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+939 rs939 1.21706 1.26709 1.37602
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+943 rs943 0.0276281 0.107018 0.0730257
+944 rs944 0.00566944 0.318826 1.00925
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+946 rs946 0.0182044 0.0179015 0.000217162
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+948 rs948 2.22348 1.16053 0.566984
+949 rs949 1.92272e-05 0.112401 0.580034
+950 rs950 0.312339 0.13625 1.56287
+951 rs951 0.0069953 0.00817502 0.273339
+952 rs952 0.000514081 0.0203327 0.00221989
+953 rs953 0.0658379 0.00695113 0.273968
+954 rs954 0.197771 0.0118909 0.292103
+955 rs955 0.915665 0.92883 0.445184
+956 rs956 0.244035 1.00585 0.00305047
+957 rs957 1.99093 3.75429 0.72079
+958 rs958 6.60835 5.76427 0.0376046
+959 rs959 0.0862763 0.207914 0.108058
+960 rs960 1.50987 0.989178 0.273339
+961 rs961 2.96332 4.21354 0.139158
+962 rs962 1.39285 1.30129 8.17018
+963 rs963 2.89876 2.35235 5.04573
+964 rs964 0.549831 0.386309 0.346598
+965 rs965 0.0355887 0.0951165 0.00190739
+966 rs966 1.26449 2.78986 1.15162
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+968 rs968 0.00496441 0 3.12652
+969 rs969 0.0456499 0.00311514 0.326842
+970 rs970 0.483112 0.841087 0.0273209
+971 rs971 1.74642 1.85971 0.442453
+972 rs972 0.809071 0.459845 1.61214
+973 rs973 0.350022 0.26989 0.000460409
+974 rs974 0.116741 0 0.14499
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+976 rs976 0.31947 0.139361 1.79944
+977 rs977 0.0560139 0.0246071 0.0967163
+978 rs978 0.460468 3.23808 0.513441
+979 rs979 2.22915 0.842476 1.00166
+980 rs980 5.86999 5.0233 2.15255
+981 rs981 0.00783474 0.00915603 0.0562298
+982 rs982 2.29892 1.88595 0.885757
+983 rs983 0.0154123 0.171676 0.263577
+984 rs984 1.89025 1.83938 0.293212
+985 rs985 5.61041 7.60482 0.0892536
+986 rs986 0.295876 0.22814 0.591954
+987 rs987 0.249216 0.0550878 0.0868479
+988 rs988 0.0275463 0.00825462 0.0324442
+989 rs989 0.492887 0.0282477 0.444102
+990 rs990 3.49731 1.98774 0.979973
+991 rs991 0.884205 0.74498 0.632886
+992 rs992 1.39373 0.913087 0.00514925
+993 rs993 1.62167 1.35461 0.00301824
+994 rs994 1.16526 0.468789 0.0199928
+995 rs995 3.17879 1.66907 0.628494
+996 rs996 0.969221 1.86973 6.62528
+997 rs997 0.168285 0.273496 0.0101606
+998 rs998 0.0393197 0.0863311 0.196974
+999 rs999 0.93193 1.8233 1.66133
+1000 rs1000 0.0275419 0.116009 0.01603
diff --git a/ROADTRIPStest.top.ex b/ROADTRIPStest.top.ex
new file mode 100644
index 0000000..4d0bd4d
--- /dev/null
+++ b/ROADTRIPStest.top.ex
@@ -0,0 +1,80 @@
+Below is a list of the top 20 markers with the smallest p-values using the RM test statistic
+
+**************************************************
+
+MARKER 678: rs678 has a p-value of 0.0019572
+MARKER 228: rs228 has a p-value of 0.00252806
+MARKER 375: rs375 has a p-value of 0.00299978
+MARKER 505: rs505 has a p-value of 0.00368594
+MARKER 635: rs635 has a p-value of 0.00487029
+MARKER 57: rs57 has a p-value of 0.00605775
+MARKER 669: rs669 has a p-value of 0.00695729
+MARKER 272: rs272 has a p-value of 0.00711711
+MARKER 612: rs612 has a p-value of 0.00785038
+MARKER 343: rs343 has a p-value of 0.00936649
+MARKER 958: rs958 has a p-value of 0.0101502
+MARKER 252: rs252 has a p-value of 0.0104924
+MARKER 712: rs712 has a p-value of 0.0122139
+MARKER 867: rs867 has a p-value of 0.013312
+MARKER 602: rs602 has a p-value of 0.0134373
+MARKER 401: rs401 has a p-value of 0.0140439
+MARKER 246: rs246 has a p-value of 0.0147129
+MARKER 980: rs980 has a p-value of 0.0154012
+MARKER 785: rs785 has a p-value of 0.0155091
+MARKER 449: rs449 has a p-value of 0.016115
+
+
+###############################################
+
+Below is a list of the top 20 markers with the smallest p-values using the RCHI test statistic
+
+**************************************************
+
+MARKER 505: rs505 has a p-value of 0.00101803
+MARKER 678: rs678 has a p-value of 0.00227348
+MARKER 635: rs635 has a p-value of 0.00437555
+MARKER 645: rs645 has a p-value of 0.00484646
+MARKER 375: rs375 has a p-value of 0.00484808
+MARKER 612: rs612 has a p-value of 0.0057479
+MARKER 985: rs985 has a p-value of 0.00582126
+MARKER 272: rs272 has a p-value of 0.00707712
+MARKER 436: rs436 has a p-value of 0.00763829
+MARKER 867: rs867 has a p-value of 0.00882606
+MARKER 228: rs228 has a p-value of 0.0106383
+MARKER 669: rs669 has a p-value of 0.012155
+MARKER 785: rs785 has a p-value of 0.012506
+MARKER 343: rs343 has a p-value of 0.0132034
+MARKER 57: rs57 has a p-value of 0.0145404
+MARKER 641: rs641 has a p-value of 0.0147421
+MARKER 458: rs458 has a p-value of 0.0181297
+MARKER 246: rs246 has a p-value of 0.0190611
+MARKER 858: rs858 has a p-value of 0.0197223
+MARKER 741: rs741 has a p-value of 0.0200999
+
+
+###############################################
+
+Below is a list of top 20 markers with the smallest p-values using the RW test statistic
+
+**************************************************
+
+MARKER 252: rs252 has a p-value of 0.000904457
+MARKER 224: rs224 has a p-value of 0.00127753
+MARKER 900: rs900 has a p-value of 0.00280583
+MARKER 962: rs962 has a p-value of 0.00425847
+MARKER 528: rs528 has a p-value of 0.00522043
+MARKER 612: rs612 has a p-value of 0.00522203
+MARKER 708: rs708 has a p-value of 0.00761769
+MARKER 380: rs380 has a p-value of 0.00789545
+MARKER 155: rs155 has a p-value of 0.00992364
+MARKER 996: rs996 has a p-value of 0.0100541
+MARKER 869: rs869 has a p-value of 0.0104148
+MARKER 757: rs757 has a p-value of 0.0122276
+MARKER 842: rs842 has a p-value of 0.0122934
+MARKER 564: rs564 has a p-value of 0.0125389
+MARKER 179: rs179 has a p-value of 0.0130302
+MARKER 821: rs821 has a p-value of 0.0132595
+MARKER 275: rs275 has a p-value of 0.0136566
+MARKER 381: rs381 has a p-value of 0.013952
+MARKER 50: rs50 has a p-value of 0.0153009
+MARKER 228: rs228 has a p-value of 0.0162479
diff --git a/cholesky.c b/cholesky.c
new file mode 100644
index 0000000..3ef9bde
--- /dev/null
+++ b/cholesky.c
@@ -0,0 +1,75 @@
+/* file: choesky.c */
+
+/* Take the cholesky decomposition in the manner described in FA Graybill
+ (1976).
+*/
+
+#include <math.h>
+#include <stdio.h>
+#include <stdlib.h>
+
+
+int cholesky(double **orig, int n, double **aug, int mcol,double **chol, double **cholaug, int ofs)
+ /*
+ Do the augmented cholesky decomposition as described in FA Graybill
+ (1976) Theory and Application of the Linear Model. The original matrix
+ must be symmetric positive definite. The augmentation matrix, or
+ series of column vectors, are multiplied by C^-t, where C is the
+ upper triangular cholesky matrix, ie C^t * C = M and M is the original
+ matrix. Returns with a value of 0 if M is a non-positive definite
+ matrix. Returns with a value of 1 with succesful completion.
+
+ Arguments:
+
+ orig (input) double n x n array. The matrix to take the Cholesky
+ decomposition of.
+ n (input) integer. Number of rows and columns in orig.
+ aug (input) double n x mcol array. The matrix for the augmented
+ part of the decomposition.
+ mcol (input) integer. Number of columns in aug.
+ chol (output) double n x n array. Holds the upper triangular matrix
+ C on output. The lower triangular portion remains unchanged.
+ This maybe the same as orig, in which case the upper triangular
+ portion of orig is overwritten.
+ cholaug (output) double n x mcol array. Holds the product C^-t * aug.
+ May be the same as aug, in which case aug is over written.
+ ofs (input) integer. The index of the first element in the matrices.
+ Normally this is 0, but commonly is 1 (but may be any integer).
+ */
+{
+ int i, j, k, l;
+ int retval = 1;
+
+ for (i=ofs; i<n+ofs; i++) {
+ chol[i][i] = orig[i][i];
+ for (k=ofs; k<i; k++)
+ chol[i][i] -= chol[k][i]*chol[k][i];
+ if (chol[i][i] <= 0) {
+ fprintf(stderr,"\nERROR: non-positive definite matrix!\n");
+ printf("\nproblem from %d %f\n",i,chol[i][i]);
+ retval = 0;
+ return retval;
+ }
+ chol[i][i] = sqrt(chol[i][i]);
+
+ /*This portion multiplies the extra matrix by C^-t */
+ for (l=ofs; l<mcol+ofs; l++) {
+ cholaug[i][l] = aug[i][l];
+ for (k=ofs; k<i; k++) {
+ cholaug[i][l] -= cholaug[k][l]*chol[k][i];
+ }
+ cholaug[i][l] /= chol[i][i];
+ }
+
+ for (j=i+1; j<n+ofs; j++) {
+ chol[i][j] = orig[i][j];
+ for (k=ofs; k<i; k++)
+ chol[i][j] -= chol[k][i]*chol[k][j];
+ chol[i][j] /= chol[i][i];
+ }
+ }
+
+ return retval;
+}
+
+
diff --git a/genofile b/genofile
new file mode 100644
index 0000000..2add532
--- /dev/null
+++ b/genofile
@@ -0,0 +1,1000 @@
+1 rs1 0 10 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 1 1 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 2 1 1 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 2 1 2 2 2 2 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 [...]
+1 rs2 0 20 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 1 2 2 2 2 1 2 2 2 1 2 1 2 1 1 1 1 1 2 1 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 2 2 2 2 1 1 1 2 1 2 2 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 1 2 1 1 1 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 1 2 1 2 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 1 1 1 2 2 1 1 1 1 2 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 [...]
+1 rs3 0 30 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 2 1 1 2 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 2 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 2 2 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 2 2 2 1 1 1 1 1 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 2 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 1 1 2 2 2 2 2 2 2 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 1 1 [...]
+1 rs4 0 40 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 2 2 2 1 1 1 1 1 1 1 2 1 1 2 2 1 2 2 2 1 2 1 2 2 2 1 2 1 1 1 1 1 2 2 2 1 2 1 2 1 2 2 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 2 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 2 2 1 2 1 2 1 [...]
+1 rs5 0 50 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 2 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [...]
+1 rs6 0 60 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 2 2 1 2 1 2 2 2 1 1 1 2 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 1 2 1 1 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 2 1 1 1 1 1 1 2 2 1 2 2 2 1 2 1 1 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 1 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2 1 2 1 1 1 1 1 1 1 2 1 2 2 2 1 1 1 2 1 2 1 1 1 2 2 [...]
+1 rs7 0 70 1 2 1 2 1 2 1 2 1 1 1 2 1 1 2 2 2 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 1 2 2 1 1 1 1 2 2 1 1 1 1 1 2 1 1 1 1 2 2 2 2 2 2 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 [...]
+1 rs8 0 80 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 1 2 2 1 2 1 1 1 2 1 1 1 2 2 2 1 1 1 2 1 1 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 1 1 1 2 2 2 1 2 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 2 2 1 1 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 2 2 1 2 1 1 1 1 1 2 2 2 2 2 1 1 1 2 2 2 2 2 2 2 2 [...]
+1 rs9 0 90 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 [...]
+1 rs10 0 100 1 2 1 2 1 1 1 1 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 1 2 2 1 2 1 2 1 2 1 1 1 2 1 2 2 2 2 2 1 2 1 1 2 2 2 2 2 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 2 2 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 2 2 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 2 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [...]
+1 rs11 0 110 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 [...]
+1 rs12 0 120 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 1 2 1 1 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 1 1 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 1 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 1 2 1 2 1 2 2 2 2 2 1 2 1 1 1 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 1 2 2 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 [...]
+1 rs13 0 130 1 1 1 2 1 2 1 2 2 2 1 1 1 2 1 2 1 1 1 1 1 1 2 2 2 2 2 2 2 2 1 2 1 1 1 1 2 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 1 1 1 1 1 1 2 2 2 2 2 1 1 1 2 1 1 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 2 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 2 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 2 2 1 2 1 1 1 2 1 2 [...]
+1 rs14 0 140 1 2 2 2 1 1 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2 2 2 1 1 1 1 1 1 1 2 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 2 2 1 1 2 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 1 1 1 2 1 1 1 2 [...]
+1 rs15 0 150 2 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 2 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [...]
+1 rs16 0 160 1 1 1 2 2 2 1 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 2 2 1 1 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 2 2 2 1 2 2 2 1 2 1 1 1 1 1 2 1 2 2 2 1 2 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 2 2 1 2 2 2 1 2 1 1 1 1 1 2 1 2 1 1 1 1 2 2 1 2 2 2 1 2 1 1 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 [...]
+1 rs17 0 170 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 1 1 1 1 2 2 2 2 1 2 1 1 1 2 2 2 2 2 2 2 1 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 1 2 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 1 2 1 1 2 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 2 2 1 1 1 2 1 2 1 1 1 2 1 2 2 2 1 1 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 2 2 1 2 1 1 2 2 1 2 1 1 1 2 1 2 1 1 2 2 2 2 1 2 1 2 1 2 [...]
+1 rs18 0 180 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 [...]
+1 rs19 0 190 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 [...]
+1 rs20 0 200 1 1 1 2 1 2 2 2 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 1 1 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 2 2 2 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 2 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 2 1 2 2 2 1 2 1 1 1 1 1 2 2 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 2 2 1 2 1 1 2 2 1 2 1 2 1 2 1 1 1 2 1 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 [...]
+1 rs21 0 210 1 2 1 1 1 2 1 2 2 2 1 2 1 2 1 2 1 1 2 2 1 1 1 2 1 1 2 2 2 2 1 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 1 1 2 2 1 2 2 2 2 2 1 1 1 2 1 1 2 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 2 2 2 2 1 2 1 1 1 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 1 1 2 1 2 1 1 2 2 1 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 [...]
+1 rs22 0 220 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 2 2 1 1 2 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 [...]
+1 rs23 0 230 1 1 1 2 2 2 2 2 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 1 2 1 1 2 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 2 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 2 2 1 2 1 1 1 2 2 2 1 1 1 1 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 2 2 2 2 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 2 2 2 1 2 1 2 2 2 1 2 2 2 2 2 [...]
+1 rs24 0 240 1 2 2 2 1 2 1 2 2 2 2 2 1 2 2 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 1 1 1 1 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 1 2 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 2 2 1 2 2 2 2 2 1 1 1 2 2 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 1 2 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 2 2 2 1 2 2 2 1 2 1 1 2 2 1 2 2 2 2 2 [...]
+1 rs25 0 250 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 1 2 2 1 2 1 2 2 2 1 1 2 2 1 2 2 2 2 2 2 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 1 1 1 1 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 1 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 [...]
+1 rs26 0 260 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 2 2 1 2 1 2 2 2 2 2 1 2 1 1 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 1 2 2 2 1 1 1 2 2 2 1 1 1 1 1 2 1 2 1 1 1 2 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2 2 1 2 1 2 1 2 1 2 1 1 2 2 1 2 1 2 [...]
+1 rs27 0 270 1 1 2 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 2 2 1 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 1 1 2 2 2 1 2 2 2 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 2 2 2 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 2 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 [...]
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+1 rs178 0 1780 2 2 1 2 1 1 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 1 1 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 2 2 1 1 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 1 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 1 2 1 1 1 2 2 2 2 2 2 2 1 2 2 2 1 1 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 2 2 1 1 1 2 1 [...]
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+1 rs184 0 1840 1 2 2 2 1 1 1 2 2 2 1 2 1 2 2 2 1 1 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 1 1 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 1 1 2 2 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 2 2 1 2 1 2 2 2 2 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 1 1 2 2 1 1 1 1 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 2 2 1 2 1 [...]
+1 rs185 0 1850 2 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 2 2 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 2 2 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 2 2 1 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 2 2 2 1 1 1 1 1 2 2 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 1 1 2 1 2 2 2 1 2 1 1 1 2 2 2 1 2 1 1 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 2 2 2 2 2 [...]
+1 rs186 0 1860 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 2 2 2 2 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 1 2 1 2 2 2 1 1 1 1 1 2 1 2 1 1 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 1 1 2 2 2 2 2 1 1 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 1 2 2 2 2 1 1 2 2 1 2 1 2 1 [...]
+1 rs187 0 1870 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 2 1 2 1 2 1 [...]
+1 rs188 0 1880 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 1 2 2 2 2 1 1 2 2 2 2 1 1 1 2 1 1 2 2 2 2 1 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 2 1 1 1 2 1 1 2 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 2 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 2 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 1 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 1 2 2 [...]
+1 rs189 0 1890 1 2 1 1 1 2 1 2 1 1 1 2 1 2 1 1 2 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 1 2 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 2 2 1 1 2 2 2 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 2 2 1 1 1 1 1 1 1 2 2 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 2 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 1 2 2 2 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 [...]
+1 rs190 0 1900 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [...]
+1 rs191 0 1910 1 2 1 2 1 1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 2 2 1 2 1 2 1 1 2 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 1 1 2 2 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 1 2 2 1 2 2 2 1 1 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 1 1 2 2 1 1 1 2 1 2 1 2 1 2 1 [...]
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+1 rs193 0 1930 1 2 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 2 1 2 1 1 1 [...]
+1 rs194 0 1940 2 2 1 1 1 2 2 2 2 2 1 2 1 2 1 2 1 1 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 1 1 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 2 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 1 1 1 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 1 2 1 2 2 2 2 2 2 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 1 2 2 [...]
+1 rs195 0 1950 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 2 1 1 2 2 2 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 1 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 1 1 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 1 1 1 1 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 2 2 2 2 1 2 2 2 1 2 2 2 2 2 1 2 1 [...]
+1 rs196 0 1960 1 1 1 2 1 1 1 2 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 2 2 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 2 2 2 2 2 1 1 1 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 1 1 1 1 1 2 2 1 2 2 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 2 2 2 1 1 1 2 1 1 1 2 1 [...]
+1 rs197 0 1970 1 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 1 2 2 2 1 1 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 2 1 2 2 2 1 1 1 1 1 2 1 1 1 2 2 2 1 2 1 1 2 2 1 2 2 2 2 [...]
+1 rs198 0 1980 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 2 2 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 1 1 1 1 1 2 2 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 2 2 2 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 2 2 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 2 2 2 1 2 1 2 2 2 1 1 1 2 1 2 1 1 2 2 1 2 2 2 2 2 1 1 1 1 1 2 2 2 2 2 1 2 2 2 1 1 1 1 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 [...]
+1 rs199 0 1990 1 1 2 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 2 2 1 2 1 1 1 2 1 2 2 2 2 2 1 1 1 2 2 2 1 2 1 2 2 2 2 2 2 2 1 1 1 1 1 2 1 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 2 2 1 1 2 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 2 2 1 2 2 2 1 1 1 2 2 2 2 2 2 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 1 1 1 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 2 2 1 2 1 2 2 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 1 [...]
+1 rs200 0 2000 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 2 2 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 [...]
+1 rs201 0 2010 1 1 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 2 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 2 2 2 1 1 1 2 1 1 2 2 2 2 1 1 1 2 1 1 1 1 1 1 1 1 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 2 2 1 2 2 [...]
+1 rs202 0 2020 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 [...]
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+1 rs205 0 2050 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 [...]
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+1 rs988 0 9880 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 1 1 2 1 2 2 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 2 2 2 2 2 1 2 1 2 2 2 1 1 2 2 1 2 2 2 2 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 2 2 2 2 1 [...]
+1 rs989 0 9890 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [...]
+1 rs990 0 9900 1 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 1 1 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 1 2 1 2 1 [...]
+1 rs991 0 9910 1 2 2 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 1 1 1 1 2 2 1 2 1 2 2 2 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 1 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 2 1 2 1 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 1 2 1 2 2 2 1 1 1 2 1 2 1 1 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 1 [...]
+1 rs992 0 9920 1 2 1 1 2 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 2 2 2 2 1 1 1 2 1 2 1 1 1 2 1 2 2 2 1 1 1 2 1 1 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 1 1 1 2 1 1 1 2 1 2 2 2 1 2 1 2 1 1 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 1 1 2 2 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 2 1 [...]
+1 rs993 0 9930 1 2 1 2 2 2 1 2 2 2 1 1 1 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2 2 1 2 1 2 1 2 2 2 1 1 1 2 1 2 1 2 2 2 1 2 1 1 1 2 1 2 1 2 2 2 1 1 2 2 1 2 2 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 2 1 1 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 2 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 2 2 1 2 2 [...]
+1 rs994 0 9940 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 2 2 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 2 2 1 1 2 2 2 2 1 1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 2 2 1 2 1 2 1 1 2 2 1 2 1 2 1 2 1 1 1 2 1 1 1 1 1 2 2 2 1 2 2 2 1 2 1 2 1 1 1 1 1 2 1 1 1 2 2 2 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 2 2 1 2 1 [...]
+1 rs995 0 9950 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 1 2 2 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 1 1 2 1 2 1 1 1 2 1 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 2 2 2 2 1 1 1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 1 1 2 1 2 2 2 2 2 1 1 1 2 1 2 1 2 1 1 1 2 1 2 2 2 1 2 1 [...]
+1 rs996 0 9960 1 1 1 2 2 2 1 1 1 2 1 2 1 1 1 1 2 2 2 2 1 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2 2 2 1 1 1 1 1 1 2 2 1 1 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 1 1 1 1 2 2 2 1 2 1 2 1 2 1 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 1 2 2 1 2 1 2 2 2 1 2 1 2 1 2 1 1 1 2 2 2 2 2 2 2 1 2 2 2 2 2 1 1 1 2 2 2 1 2 2 2 2 2 2 2 2 2 1 1 1 1 2 2 2 2 1 2 2 2 2 2 1 2 2 2 1 1 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 1 1 [...]
+1 rs997 0 9970 1 1 2 2 2 2 2 2 1 1 1 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 1 1 1 2 1 2 1 1 2 2 1 2 2 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 1 1 2 2 2 2 2 2 1 2 1 1 1 1 1 2 2 2 1 2 2 2 1 2 1 2 2 2 1 2 1 2 2 2 2 2 2 2 1 2 1 1 1 2 1 1 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 2 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 2 2 1 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 1 [...]
+1 rs998 0 9980 1 1 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 1 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 2 1 1 1 2 2 2 1 2 1 1 1 1 1 1 1 2 1 2 1 1 2 2 2 2 1 2 1 2 1 2 1 1 1 2 1 1 1 2 2 2 2 2 1 2 1 2 2 2 1 2 1 2 1 1 1 2 2 2 1 2 2 2 2 2 1 2 2 2 1 2 1 1 1 2 1 2 1 2 1 1 1 2 2 2 2 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 1 1 1 2 2 1 2 1 2 1 2 1 1 1 2 1 2 1 2 2 2 2 2 2 2 1 2 1 2 1 1 1 2 1 2 1 1 2 2 1 2 1 1 1 2 1 2 1 2 1 [...]
+1 rs999 0 9990 1 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 1 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 1 2 1 1 1 2 2 2 2 2 1 2 1 2 1 2 2 2 2 2 1 1 1 2 2 2 1 2 1 2 1 2 1 2 2 2 1 2 2 2 2 2 1 2 1 1 1 1 1 2 2 2 1 2 2 2 2 2 2 2 1 2 1 2 2 2 1 2 2 2 1 2 1 2 1 2 2 2 2 2 2 2 1 2 2 2 1 1 1 2 2 2 2 2 2 2 1 [...]
+1 rs1000 0 10000 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 1 1 1 1 1 1 2 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 1 2 2 1 2 1 1 1 1 1 1 2 2 2 2 2 2 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 2 1 1 1 2 2 2 1 2 1 2 1 1 1 1 1 1 1 2 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 2 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 2 1 2 2 2 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 1 1 2 2 1 2 2 2 1 1 2 2 2 2 1 2 [...]
diff --git a/gpl.txt b/gpl.txt
new file mode 100644
index 0000000..94a9ed0
--- /dev/null
+++ b/gpl.txt
@@ -0,0 +1,674 @@
+ GNU GENERAL PUBLIC LICENSE
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+
+ How to Apply These Terms to Your New Programs
+
+ If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+ To do so, attach the following notices to the program. It is safest
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+
+ <one line to give the program's name and a brief idea of what it does.>
+ Copyright (C) <year> <name of author>
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+ but WITHOUT ANY WARRANTY; without even the implied warranty of
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+
+ You should have received a copy of the GNU General Public License
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+
+Also add information on how to contact you by electronic and paper mail.
+
+ If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+ <program> Copyright (C) <year> <name of author>
+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+ This is free software, and you are welcome to redistribute it
+ under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License. Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<http://www.gnu.org/licenses/>.
+
+ The GNU General Public License does not permit incorporating your program
+into proprietary programs. If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
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+Public License instead of this License. But first, please read
+<http://www.gnu.org/philosophy/why-not-lgpl.html>.
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diff --git a/nrutil.c b/nrutil.c
new file mode 100644
index 0000000..6d9e217
--- /dev/null
+++ b/nrutil.c
@@ -0,0 +1,614 @@
+#if defined(__STDC__) || defined(ANSI) || defined(NRANSI) /* ANSI */
+
+#include <stdio.h>
+#include <stddef.h>
+#include <stdlib.h>
+#define NR_END 1
+#define FREE_ARG char*
+
+void nrerror(char error_text[])
+/* Numerical Recipes standard error handler */
+{
+ fprintf(stderr,"Numerical Recipes run-time error...\n");
+ fprintf(stderr,"%s\n",error_text);
+ fprintf(stderr,"...now exiting to system...\n");
+ exit(1);
+}
+
+float *vector(long nl, long nh)
+/* allocate a float vector with subscript range v[nl..nh] */
+{
+ float *v;
+
+ v=(float *)malloc((size_t) ((nh-nl+1+NR_END)*sizeof(float)));
+ if (!v) nrerror("allocation failure in vector()");
+ return v-nl+NR_END;
+}
+
+int *ivector(long nl, long nh)
+/* allocate an int vector with subscript range v[nl..nh] */
+{
+ int *v;
+
+ v=(int *)malloc((size_t) ((nh-nl+1+NR_END)*sizeof(int)));
+ if (!v) nrerror("allocation failure in ivector()");
+ return v-nl+NR_END;
+}
+
+unsigned char *cvector(long nl, long nh)
+/* allocate an unsigned char vector with subscript range v[nl..nh] */
+{
+ unsigned char *v;
+
+ v=(unsigned char *)malloc((size_t) ((nh-nl+1+NR_END)*sizeof(unsigned char)));
+ if (!v) nrerror("allocation failure in cvector()");
+ return v-nl+NR_END;
+}
+
+unsigned long *lvector(long nl, long nh)
+/* allocate an unsigned long vector with subscript range v[nl..nh] */
+{
+ unsigned long *v;
+
+ v=(unsigned long *)malloc((size_t) ((nh-nl+1+NR_END)*sizeof(long)));
+ if (!v) nrerror("allocation failure in lvector()");
+ return v-nl+NR_END;
+}
+
+double *dvector(long nl, long nh)
+/* allocate a double vector with subscript range v[nl..nh] */
+{
+ double *v;
+
+ v=(double *)malloc((size_t) ((nh-nl+1+NR_END)*sizeof(double)));
+ if (!v) nrerror("allocation failure in dvector()");
+ return v-nl+NR_END;
+}
+
+float **matrix(long nrl, long nrh, long ncl, long nch)
+/* allocate a float matrix with subscript range m[nrl..nrh][ncl..nch] */
+{
+ long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ float **m;
+
+ /* allocate pointers to rows */
+ m=(float **) malloc((size_t)((nrow+NR_END)*sizeof(float*)));
+ if (!m) nrerror("allocation failure 1 in matrix()");
+ m += NR_END;
+ m -= nrl;
+
+ /* allocate rows and set pointers to them */
+ m[nrl]=(float *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(float)));
+ if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
+ m[nrl] += NR_END;
+ m[nrl] -= ncl;
+
+ for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+double **dmatrix(long nrl, long nrh, long ncl, long nch)
+/* allocate a double matrix with subscript range m[nrl..nrh][ncl..nch] */
+{
+ long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ double **m;
+
+ /* allocate pointers to rows */
+ m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
+ if (!m) nrerror("allocation failure 1 in matrix()");
+ m += NR_END;
+ m -= nrl;
+
+ /* allocate rows and set pointers to them */
+ m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
+ if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
+ m[nrl] += NR_END;
+ m[nrl] -= ncl;
+
+ for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+int **imatrix(long nrl, long nrh, long ncl, long nch)
+/* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
+{
+ long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ int **m;
+
+ /* allocate pointers to rows */
+ m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
+ if (!m) nrerror("allocation failure 1 in matrix()");
+ m += NR_END;
+ m -= nrl;
+
+
+ /* allocate rows and set pointers to them */
+ m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
+ if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
+ m[nrl] += NR_END;
+ m[nrl] -= ncl;
+
+ for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+float **submatrix(float **a, long oldrl, long oldrh, long oldcl, long oldch,
+ long newrl, long newcl)
+/* point a submatrix [newrl..][newcl..] to a[oldrl..oldrh][oldcl..oldch] */
+{
+ long i,j,nrow=oldrh-oldrl+1,ncol=oldcl-newcl;
+ float **m;
+
+ /* allocate array of pointers to rows */
+ m=(float **) malloc((size_t) ((nrow+NR_END)*sizeof(float*)));
+ if (!m) nrerror("allocation failure in submatrix()");
+ m += NR_END;
+ m -= newrl;
+
+ /* set pointers to rows */
+ for(i=oldrl,j=newrl;i<=oldrh;i++,j++) m[j]=a[i]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+float **convert_matrix(float *a, long nrl, long nrh, long ncl, long nch)
+/* allocate a float matrix m[nrl..nrh][ncl..nch] that points to the matrix
+declared in the standard C manner as a[nrow][ncol], where nrow=nrh-nrl+1
+and ncol=nch-ncl+1. The routine should be called with the address
+&a[0][0] as the first argument. */
+{
+ long i,j,nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ float **m;
+
+ /* allocate pointers to rows */
+ m=(float **) malloc((size_t) ((nrow+NR_END)*sizeof(float*)));
+ if (!m) nrerror("allocation failure in convert_matrix()");
+ m += NR_END;
+ m -= nrl;
+
+ /* set pointers to rows */
+ m[nrl]=a-ncl;
+ for(i=1,j=nrl+1;i<nrow;i++,j++) m[j]=m[j-1]+ncol;
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+float ***f3tensor(long nrl, long nrh, long ncl, long nch, long ndl, long ndh)
+/* allocate a float 3tensor with range t[nrl..nrh][ncl..nch][ndl..ndh] */
+{
+ long i,j,nrow=nrh-nrl+1,ncol=nch-ncl+1,ndep=ndh-ndl+1;
+ float ***t;
+
+ /* allocate pointers to pointers to rows */
+ t=(float ***) malloc((size_t)((nrow+NR_END)*sizeof(float**)));
+ if (!t) nrerror("allocation failure 1 in f3tensor()");
+ t += NR_END;
+ t -= nrl;
+
+ /* allocate pointers to rows and set pointers to them */
+ t[nrl]=(float **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(float*)));
+ if (!t[nrl]) nrerror("allocation failure 2 in f3tensor()");
+ t[nrl] += NR_END;
+ t[nrl] -= ncl;
+
+ /* allocate rows and set pointers to them */
+ t[nrl][ncl]=(float *) malloc((size_t)((nrow*ncol*ndep+NR_END)*sizeof(float)));
+ if (!t[nrl][ncl]) nrerror("allocation failure 3 in f3tensor()");
+ t[nrl][ncl] += NR_END;
+ t[nrl][ncl] -= ndl;
+
+ for(j=ncl+1;j<=nch;j++) t[nrl][j]=t[nrl][j-1]+ndep;
+ for(i=nrl+1;i<=nrh;i++) {
+ t[i]=t[i-1]+ncol;
+ t[i][ncl]=t[i-1][ncl]+ncol*ndep;
+ for(j=ncl+1;j<=nch;j++) t[i][j]=t[i][j-1]+ndep;
+ }
+
+ /* return pointer to array of pointers to rows */
+ return t;
+}
+
+void free_vector(float *v, long nl, long nh)
+/* free a float vector allocated with vector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_ivector(int *v, long nl, long nh)
+/* free an int vector allocated with ivector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_cvector(unsigned char *v, long nl, long nh)
+/* free an unsigned char vector allocated with cvector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_lvector(unsigned long *v, long nl, long nh)
+/* free an unsigned long vector allocated with lvector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_dvector(double *v, long nl, long nh)
+/* free a double vector allocated with dvector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_matrix(float **m, long nrl, long nrh, long ncl, long nch)
+/* free a float matrix allocated by matrix() */
+{
+ free((FREE_ARG) (m[nrl]+ncl-NR_END));
+ free((FREE_ARG) (m+nrl-NR_END));
+}
+
+void free_dmatrix(double **m, long nrl, long nrh, long ncl, long nch)
+/* free a double matrix allocated by dmatrix() */
+{
+ free((FREE_ARG) (m[nrl]+ncl-NR_END));
+ free((FREE_ARG) (m+nrl-NR_END));
+}
+
+void free_imatrix(int **m, long nrl, long nrh, long ncl, long nch)
+/* free an int matrix allocated by imatrix() */
+{
+ free((FREE_ARG) (m[nrl]+ncl-NR_END));
+ free((FREE_ARG) (m+nrl-NR_END));
+}
+
+void free_submatrix(float **b, long nrl, long nrh, long ncl, long nch)
+/* free a submatrix allocated by submatrix() */
+{
+ free((FREE_ARG) (b+nrl-NR_END));
+}
+
+void free_convert_matrix(float **b, long nrl, long nrh, long ncl, long nch)
+/* free a matrix allocated by convert_matrix() */
+{
+ free((FREE_ARG) (b+nrl-NR_END));
+}
+
+void free_f3tensor(float ***t, long nrl, long nrh, long ncl, long nch,
+ long ndl, long ndh)
+/* free a float f3tensor allocated by f3tensor() */
+{
+ free((FREE_ARG) (t[nrl][ncl]+ndl-NR_END));
+ free((FREE_ARG) (t[nrl]+ncl-NR_END));
+ free((FREE_ARG) (t+nrl-NR_END));
+}
+
+#else /* ANSI */
+/* traditional - K&R */
+
+#include <stdio.h>
+#define NR_END 1
+#define FREE_ARG char*
+
+void nrerror(error_text)
+char error_text[];
+/* Numerical Recipes standard error handler */
+{
+ void exit();
+
+ fprintf(stderr,"Numerical Recipes run-time error...\n");
+ fprintf(stderr,"%s\n",error_text);
+ fprintf(stderr,"...now exiting to system...\n");
+ exit(1);
+}
+
+float *vector(nl,nh)
+long nh,nl;
+/* allocate a float vector with subscript range v[nl..nh] */
+{
+ float *v;
+
+ v=(float *)malloc((unsigned int) ((nh-nl+1+NR_END)*sizeof(float)));
+ if (!v) nrerror("allocation failure in vector()");
+ return v-nl+NR_END;
+}
+
+int *ivector(nl,nh)
+long nh,nl;
+/* allocate an int vector with subscript range v[nl..nh] */
+{
+ int *v;
+
+ v=(int *)malloc((unsigned int) ((nh-nl+1+NR_END)*sizeof(int)));
+ if (!v) nrerror("allocation failure in ivector()");
+ return v-nl+NR_END;
+}
+
+unsigned char *cvector(nl,nh)
+long nh,nl;
+/* allocate an unsigned char vector with subscript range v[nl..nh] */
+{
+ unsigned char *v;
+
+ v=(unsigned char *)malloc((unsigned int) ((nh-nl+1+NR_END)*sizeof(unsigned char)));
+ if (!v) nrerror("allocation failure in cvector()");
+ return v-nl+NR_END;
+}
+
+unsigned long *lvector(nl,nh)
+long nh,nl;
+/* allocate an unsigned long vector with subscript range v[nl..nh] */
+{
+ unsigned long *v;
+
+ v=(unsigned long *)malloc((unsigned int) ((nh-nl+1+NR_END)*sizeof(long)));
+ if (!v) nrerror("allocation failure in lvector()");
+ return v-nl+NR_END;
+}
+
+double *dvector(nl,nh)
+long nh,nl;
+/* allocate a double vector with subscript range v[nl..nh] */
+{
+ double *v;
+
+ v=(double *)malloc((unsigned int) ((nh-nl+1+NR_END)*sizeof(double)));
+ if (!v) nrerror("allocation failure in dvector()");
+ return v-nl+NR_END;
+}
+
+float **matrix(nrl,nrh,ncl,nch)
+long nch,ncl,nrh,nrl;
+/* allocate a float matrix with subscript range m[nrl..nrh][ncl..nch] */
+{
+ long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ float **m;
+
+ /* allocate pointers to rows */
+ m=(float **) malloc((unsigned int)((nrow+NR_END)*sizeof(float*)));
+ if (!m) nrerror("allocation failure 1 in matrix()");
+ m += NR_END;
+ m -= nrl;
+
+ /* allocate rows and set pointers to them */
+ m[nrl]=(float *) malloc((unsigned int)((nrow*ncol+NR_END)*sizeof(float)));
+ if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
+ m[nrl] += NR_END;
+ m[nrl] -= ncl;
+
+ for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+double **dmatrix(nrl,nrh,ncl,nch)
+long nch,ncl,nrh,nrl;
+/* allocate a double matrix with subscript range m[nrl..nrh][ncl..nch] */
+{
+ long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ double **m;
+
+ /* allocate pointers to rows */
+ m=(double **) malloc((unsigned int)((nrow+NR_END)*sizeof(double*)));
+ if (!m) nrerror("allocation failure 1 in matrix()");
+ m += NR_END;
+ m -= nrl;
+
+ /* allocate rows and set pointers to them */
+ m[nrl]=(double *) malloc((unsigned int)((nrow*ncol+NR_END)*sizeof(double)));
+ if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
+ m[nrl] += NR_END;
+ m[nrl] -= ncl;
+
+ for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+int **imatrix(nrl,nrh,ncl,nch)
+long nch,ncl,nrh,nrl;
+/* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
+{
+ long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ int **m;
+
+ /* allocate pointers to rows */
+ m=(int **) malloc((unsigned int)((nrow+NR_END)*sizeof(int*)));
+ if (!m) nrerror("allocation failure 1 in matrix()");
+ m += NR_END;
+ m -= nrl;
+
+
+ /* allocate rows and set pointers to them */
+ m[nrl]=(int *) malloc((unsigned int)((nrow*ncol+NR_END)*sizeof(int)));
+ if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
+ m[nrl] += NR_END;
+ m[nrl] -= ncl;
+
+ for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+float **submatrix(a,oldrl,oldrh,oldcl,oldch,newrl,newcl)
+float **a;
+long newcl,newrl,oldch,oldcl,oldrh,oldrl;
+/* point a submatrix [newrl..][newcl..] to a[oldrl..oldrh][oldcl..oldch] */
+{
+ long i,j,nrow=oldrh-oldrl+1,ncol=oldcl-newcl;
+ float **m;
+
+ /* allocate array of pointers to rows */
+ m=(float **) malloc((unsigned int) ((nrow+NR_END)*sizeof(float*)));
+ if (!m) nrerror("allocation failure in submatrix()");
+ m += NR_END;
+ m -= newrl;
+
+ /* set pointers to rows */
+ for(i=oldrl,j=newrl;i<=oldrh;i++,j++) m[j]=a[i]+ncol;
+
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+float **convert_matrix(a,nrl,nrh,ncl,nch)
+float *a;
+long nch,ncl,nrh,nrl;
+/* allocate a float matrix m[nrl..nrh][ncl..nch] that points to the matrix
+declared in the standard C manner as a[nrow][ncol], where nrow=nrh-nrl+1
+and ncol=nch-ncl+1. The routine should be called with the address
+&a[0][0] as the first argument. */
+{
+ long i,j,nrow=nrh-nrl+1,ncol=nch-ncl+1;
+ float **m;
+
+ /* allocate pointers to rows */
+ m=(float **) malloc((unsigned int) ((nrow+NR_END)*sizeof(float*)));
+ if (!m) nrerror("allocation failure in convert_matrix()");
+ m += NR_END;
+ m -= nrl;
+
+ /* set pointers to rows */
+ m[nrl]=a-ncl;
+ for(i=1,j=nrl+1;i<nrow;i++,j++) m[j]=m[j-1]+ncol;
+ /* return pointer to array of pointers to rows */
+ return m;
+}
+
+float ***f3tensor(nrl,nrh,ncl,nch,ndl,ndh)
+long nch,ncl,ndh,ndl,nrh,nrl;
+/* allocate a float 3tensor with range t[nrl..nrh][ncl..nch][ndl..ndh] */
+{
+ long i,j,nrow=nrh-nrl+1,ncol=nch-ncl+1,ndep=ndh-ndl+1;
+ float ***t;
+
+ /* allocate pointers to pointers to rows */
+ t=(float ***) malloc((unsigned int)((nrow+NR_END)*sizeof(float**)));
+ if (!t) nrerror("allocation failure 1 in f3tensor()");
+ t += NR_END;
+ t -= nrl;
+
+ /* allocate pointers to rows and set pointers to them */
+ t[nrl]=(float **) malloc((unsigned int)((nrow*ncol+NR_END)*sizeof(float*)));
+ if (!t[nrl]) nrerror("allocation failure 2 in f3tensor()");
+ t[nrl] += NR_END;
+ t[nrl] -= ncl;
+
+ /* allocate rows and set pointers to them */
+ t[nrl][ncl]=(float *) malloc((unsigned int)((nrow*ncol*ndep+NR_END)*sizeof(float)));
+ if (!t[nrl][ncl]) nrerror("allocation failure 3 in f3tensor()");
+ t[nrl][ncl] += NR_END;
+ t[nrl][ncl] -= ndl;
+
+ for(j=ncl+1;j<=nch;j++) t[nrl][j]=t[nrl][j-1]+ndep;
+ for(i=nrl+1;i<=nrh;i++) {
+ t[i]=t[i-1]+ncol;
+ t[i][ncl]=t[i-1][ncl]+ncol*ndep;
+ for(j=ncl+1;j<=nch;j++) t[i][j]=t[i][j-1]+ndep;
+ }
+
+ /* return pointer to array of pointers to rows */
+ return t;
+}
+
+void free_vector(v,nl,nh)
+float *v;
+long nh,nl;
+/* free a float vector allocated with vector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_ivector(v,nl,nh)
+int *v;
+long nh,nl;
+/* free an int vector allocated with ivector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_cvector(v,nl,nh)
+long nh,nl;
+unsigned char *v;
+/* free an unsigned char vector allocated with cvector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_lvector(v,nl,nh)
+long nh,nl;
+unsigned long *v;
+/* free an unsigned long vector allocated with lvector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_dvector(v,nl,nh)
+double *v;
+long nh,nl;
+/* free a double vector allocated with dvector() */
+{
+ free((FREE_ARG) (v+nl-NR_END));
+}
+
+void free_matrix(m,nrl,nrh,ncl,nch)
+float **m;
+long nch,ncl,nrh,nrl;
+/* free a float matrix allocated by matrix() */
+{
+ free((FREE_ARG) (m[nrl]+ncl-NR_END));
+ free((FREE_ARG) (m+nrl-NR_END));
+}
+
+void free_dmatrix(m,nrl,nrh,ncl,nch)
+double **m;
+long nch,ncl,nrh,nrl;
+/* free a double matrix allocated by dmatrix() */
+{
+ free((FREE_ARG) (m[nrl]+ncl-NR_END));
+ free((FREE_ARG) (m+nrl-NR_END));
+}
+
+void free_imatrix(m,nrl,nrh,ncl,nch)
+int **m;
+long nch,ncl,nrh,nrl;
+/* free an int matrix allocated by imatrix() */
+{
+ free((FREE_ARG) (m[nrl]+ncl-NR_END));
+ free((FREE_ARG) (m+nrl-NR_END));
+}
+
+void free_submatrix(b,nrl,nrh,ncl,nch)
+float **b;
+long nch,ncl,nrh,nrl;
+/* free a submatrix allocated by submatrix() */
+{
+ free((FREE_ARG) (b+nrl-NR_END));
+}
+
+void free_convert_matrix(b,nrl,nrh,ncl,nch)
+float **b;
+long nch,ncl,nrh,nrl;
+/* free a matrix allocated by convert_matrix() */
+{
+ free((FREE_ARG) (b+nrl-NR_END));
+}
+
+void free_f3tensor(t,nrl,nrh,ncl,nch,ndl,ndh)
+float ***t;
+long nch,ncl,ndh,ndl,nrh,nrl;
+/* free a float f3tensor allocated by f3tensor() */
+{
+ free((FREE_ARG) (t[nrl][ncl]+ndl-NR_END));
+ free((FREE_ARG) (t[nrl]+ncl-NR_END));
+ free((FREE_ARG) (t+nrl-NR_END));
+}
+
+#endif /* ANSI */
diff --git a/nrutil.h b/nrutil.h
new file mode 100644
index 0000000..0f96cce
--- /dev/null
+++ b/nrutil.h
@@ -0,0 +1,104 @@
+#ifndef _NR_UTILS_H_
+#define _NR_UTILS_H_
+
+static float sqrarg;
+#define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 : sqrarg*sqrarg)
+
+static double dsqrarg;
+#define DSQR(a) ((dsqrarg=(a)) == 0.0 ? 0.0 : dsqrarg*dsqrarg)
+
+static double dmaxarg1,dmaxarg2;
+#define DMAX(a,b) (dmaxarg1=(a),dmaxarg2=(b),(dmaxarg1) > (dmaxarg2) ?\
+ (dmaxarg1) : (dmaxarg2))
+
+static double dminarg1,dminarg2;
+#define DMIN(a,b) (dminarg1=(a),dminarg2=(b),(dminarg1) < (dminarg2) ?\
+ (dminarg1) : (dminarg2))
+
+static float maxarg1,maxarg2;
+#define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1) > (maxarg2) ?\
+ (maxarg1) : (maxarg2))
+
+static float minarg1,minarg2;
+#define FMIN(a,b) (minarg1=(a),minarg2=(b),(minarg1) < (minarg2) ?\
+ (minarg1) : (minarg2))
+
+static long lmaxarg1,lmaxarg2;
+#define LMAX(a,b) (lmaxarg1=(a),lmaxarg2=(b),(lmaxarg1) > (lmaxarg2) ?\
+ (lmaxarg1) : (lmaxarg2))
+
+static long lminarg1,lminarg2;
+#define LMIN(a,b) (lminarg1=(a),lminarg2=(b),(lminarg1) < (lminarg2) ?\
+ (lminarg1) : (lminarg2))
+
+static int imaxarg1,imaxarg2;
+#define IMAX(a,b) (imaxarg1=(a),imaxarg2=(b),(imaxarg1) > (imaxarg2) ?\
+ (imaxarg1) : (imaxarg2))
+
+static int iminarg1,iminarg2;
+#define IMIN(a,b) (iminarg1=(a),iminarg2=(b),(iminarg1) < (iminarg2) ?\
+ (iminarg1) : (iminarg2))
+
+#define SIGN(a,b) ((b) >= 0.0 ? fabs(a) : -fabs(a))
+
+#if defined(__STDC__) || defined(ANSI) || defined(NRANSI) /* ANSI */
+
+void nrerror(char error_text[]);
+float *vector(long nl, long nh);
+int *ivector(long nl, long nh);
+unsigned char *cvector(long nl, long nh);
+unsigned long *lvector(long nl, long nh);
+double *dvector(long nl, long nh);
+float **matrix(long nrl, long nrh, long ncl, long nch);
+double **dmatrix(long nrl, long nrh, long ncl, long nch);
+int **imatrix(long nrl, long nrh, long ncl, long nch);
+float **submatrix(float **a, long oldrl, long oldrh, long oldcl, long oldch,
+ long newrl, long newcl);
+float **convert_matrix(float *a, long nrl, long nrh, long ncl, long nch);
+float ***f3tensor(long nrl, long nrh, long ncl, long nch, long ndl, long ndh);
+int ***i3tensor(long nrl, long nrh, long ncl, long nch, long ndl, long ndh);
+void free_vector(float *v, long nl, long nh);
+void free_ivector(int *v, long nl, long nh);
+void free_cvector(unsigned char *v, long nl, long nh);
+void free_lvector(unsigned long *v, long nl, long nh);
+void free_dvector(double *v, long nl, long nh);
+void free_matrix(float **m, long nrl, long nrh, long ncl, long nch);
+void free_dmatrix(double **m, long nrl, long nrh, long ncl, long nch);
+void free_imatrix(int **m, long nrl, long nrh, long ncl, long nch);
+void free_submatrix(float **b, long nrl, long nrh, long ncl, long nch);
+void free_convert_matrix(float **b, long nrl, long nrh, long ncl, long nch);
+void free_f3tensor(float ***t, long nrl, long nrh, long ncl, long nch,
+ long ndl, long ndh);
+void free_i3tensor(int ***t, long nrl, long nrh, long ncl, long nch,
+ long ndl, long ndh);
+
+#else /* ANSI */
+/* traditional - K&R */
+
+void nrerror();
+float *vector();
+float **matrix();
+float **submatrix();
+float **convert_matrix();
+float ***f3tensor();
+double *dvector();
+double **dmatrix();
+int *ivector();
+int **imatrix();
+unsigned char *cvector();
+unsigned long *lvector();
+void free_vector();
+void free_dvector();
+void free_ivector();
+void free_cvector();
+void free_lvector();
+void free_matrix();
+void free_submatrix();
+void free_convert_matrix();
+void free_dmatrix();
+void free_imatrix();
+void free_f3tensor();
+
+#endif /* ANSI */
+
+#endif /* _NR_UTILS_H_ */
diff --git a/phenofile b/phenofile
new file mode 100644
index 0000000..6b4fdca
--- /dev/null
+++ b/phenofile
@@ -0,0 +1,320 @@
+1 1 0 0 2 1
+1 2 0 0 1 1
+1 3 0 0 2 2
+1 4 0 0 1 1
+1 5 0 0 1 1
+1 6 2 1 1 1
+1 7 2 1 2 2
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+2 8 2 1 2 1
+2 9 6 3 1 2
+2 10 6 3 2 1
+2 11 6 3 1 2
+2 12 4 7 2 1
+2 13 4 7 1 1
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+3 1 0 0 2 1
+3 2 0 0 1 1
+3 3 0 0 2 2
+3 4 0 0 1 1
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+3 6 2 1 1 1
+3 7 2 1 2 2
+3 8 2 1 2 1
+3 9 6 3 1 2
+3 10 6 3 2 1
+3 11 6 3 1 2
+3 12 4 7 2 1
+3 13 4 7 1 1
+3 14 5 8 2 1
+3 15 5 8 1 1
+3 16 5 8 2 1
+4 1 0 0 2 1
+4 2 0 0 1 1
+4 3 0 0 2 2
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diff --git a/pnorms2.c b/pnorms2.c
new file mode 100644
index 0000000..1f75cac
--- /dev/null
+++ b/pnorms2.c
@@ -0,0 +1,207 @@
+#include<stdio.h>
+#include<math.h>
+
+/*
+ * R : A Computer Langage for Statistical Data Analysis
+ * Copyright (C) 1995, 1996 Robert Gentleman and Ross Ihaka
+ *
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
+ */
+
+/* Reference:
+ * Cody, W.D. (1993). ALGORITHM 715: SPECFUN - A Portable FORTRAN
+ * Package of Special Function Routines and Test Drivers"
+ * ACM Transactions on Mathematical Software. 19, 22-32.
+ *
+ * This function evaluates the normal distribution function:
+ * The main computation evaluates near-minimax approximations
+ * derived from those in "Rational Chebyshev approximations for
+ * the error function" by W. J. Cody, Math. Comp., 1969, 631-637.
+ * This transportable program uses rational functions that
+ * theoretically approximate the normal distribution function to
+ * at least 18 significant decimal digits. The accuracy achieved
+ * depends on the arithmetic system, the compiler, the intrinsic
+ * functions, and proper selection of the machine-dependent
+ * constants.
+ *
+ *
+ * Mathematical Constants:
+ *
+ * sqrpi = 1 / sqrt(2*pi),
+ * root32 = sqrt(32),
+ * thrsh = the argument for which pnorm(thrsh,0,1) = 0.75.
+ */
+
+
+/*float.h:#define DBL_EPSILON 2.2204460492503131e-16*/
+/*float.h:#define DBL_MIN 2.2250738585072014e-308*/
+
+/*#include "Mathlib.h"*/
+#include <float.h>
+#include <math.h>
+
+static double c[9] = {
+ 0.39894151208813466764,
+ 8.8831497943883759412,
+ 93.506656132177855979,
+ 597.27027639480026226,
+ 2494.5375852903726711,
+ 6848.1904505362823326,
+ 11602.651437647350124,
+ 9842.7148383839780218,
+ 1.0765576773720192317e-8
+};
+
+static double d[8] = {
+ 22.266688044328115691,
+ 235.38790178262499861,
+ 1519.377599407554805,
+ 6485.558298266760755,
+ 18615.571640885098091,
+ 34900.952721145977266,
+ 38912.003286093271411,
+ 19685.429676859990727
+};
+
+static double p[6] = {
+ 0.21589853405795699,
+ 0.1274011611602473639,
+ 0.022235277870649807,
+ 0.001421619193227893466,
+ 2.9112874951168792e-5,
+ 0.02307344176494017303
+};
+
+static double q[5] = {
+ 1.28426009614491121,
+ 0.468238212480865118,
+ 0.0659881378689285515,
+ 0.00378239633202758244,
+ 7.29751555083966205e-5
+};
+
+static double a[5] = {
+ 2.2352520354606839287,
+ 161.02823106855587881,
+ 1067.6894854603709582,
+ 18154.981253343561249,
+ 0.065682337918207449113
+};
+
+static double b[4] = {
+ 47.20258190468824187,
+ 976.09855173777669322,
+ 10260.932208618978205,
+ 45507.789335026729956}
+;
+
+static double one = 1.0;
+static double half = 0.5;
+static double zero = 0.0;
+static double sixten = 1.6;
+static double sqrpi = 0.39894228040143267794;
+static double thrsh = 0.66291;
+static double root32 = 5.656854248;
+
+/*double pnorm(double x, double mean, double sd)*/
+double pnorms(x)
+double x;
+{
+ static double xden, temp, xnum, result, ccum;
+ static double del, min, eps, xsq;
+ static double y;
+ static int i;
+ double fint();
+
+/* if(sd <= 0.0)
+ DOMAIN_ERROR;
+ x = (x - mean) / sd;*/
+ eps = DBL_EPSILON * .5;
+ min = DBL_MIN;
+ y = fabs(x);
+ if (y <= thrsh) {
+ /* Evaluate pnorm for |z| <= 0.66291 */
+ xsq = zero;
+ if (y > eps) {
+ xsq = x * x;
+ }
+ xnum = a[4] * xsq;
+ xden = xsq;
+ for (i = 1; i <= 3; ++i) {
+ xnum = (xnum + a[i - 1]) * xsq;
+ xden = (xden + b[i - 1]) * xsq;
+ }
+ result = x * (xnum + a[3]) / (xden + b[3]);
+ temp = result;
+ result = half + temp;
+ ccum = half - temp;
+ }
+ else if (y <= root32) {
+ /* Evaluate pnorm for 0.66291 <= |z| <= sqrt(32) */
+ xnum = c[8] * y;
+ xden = y;
+ for (i = 1; i <= 7; ++i) {
+ xnum = (xnum + c[i - 1]) * y;
+ xden = (xden + d[i - 1]) * y;
+ }
+ result = (xnum + c[7]) / (xden + d[7]);
+ xsq = fint(y * sixten) / sixten;
+ del = (y - xsq) * (y + xsq);
+ result = exp(-xsq * xsq * half) * exp(-del * half) * result;
+ ccum = one - result;
+ if (x > zero) {
+ temp = result;
+ result = ccum;
+ ccum = temp;
+ }
+ }
+ else {
+ /* Evaluate pnorm for |z| > sqrt(32) */
+ result = zero;
+ xsq = one / (x * x);
+ xnum = p[5] * xsq;
+ xden = xsq;
+ for (i = 1; i <= 4; ++i) {
+ xnum = (xnum + p[i - 1]) * xsq;
+ xden = (xden + q[i - 1]) * xsq;
+ }
+ result = xsq * (xnum + p[4]) / (xden + q[4]);
+ result = (sqrpi - result) / y;
+ xsq = fint(x * sixten) / sixten;
+ del = (x - xsq) * (x + xsq);
+ result = exp(-xsq * xsq * half) * exp(-del * half) * result;
+ ccum = one - result;
+ if (x > zero) {
+ temp = result;
+ result = ccum;
+ ccum = temp;
+ }
+ }
+ if (result < min) {
+ result = 0.0;
+ }
+ if (ccum < min) {
+ ccum = 0.0;
+ }
+ return result;
+}
+
+/*double fint(double x)*/
+double fint(x)
+double x;
+{
+ return (x >= 0.0) ? floor(x) : -floor(-x);
+}
+
diff --git a/prevalence b/prevalence
new file mode 100644
index 0000000..46a2406
--- /dev/null
+++ b/prevalence
@@ -0,0 +1 @@
+0.085625
--
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