[med-svn] [r-bioc-deseq2] 05/06: Adapt patches
Andreas Tille
tille at debian.org
Mon Oct 2 20:31:22 UTC 2017
This is an automated email from the git hooks/post-receive script.
tille pushed a commit to branch master
in repository r-bioc-deseq2.
commit 70bdf8f2f457b091c3b0c74bc94aadc6c292a00e
Author: Andreas Tille <tille at debian.org>
Date: Mon Oct 2 22:21:18 2017 +0200
Adapt patches
---
debian/patches/remove-locfit | 127 +++++++++++++++----------------------------
1 file changed, 43 insertions(+), 84 deletions(-)
diff --git a/debian/patches/remove-locfit b/debian/patches/remove-locfit
index e796487..649642d 100644
--- a/debian/patches/remove-locfit
+++ b/debian/patches/remove-locfit
@@ -2,7 +2,7 @@ Author: Michael R. Crusoe <michael.crusoe at gmail.com>
Description: r-cran-locfit is non-free and not yet packaged for Debian
--- a/R/core.R
+++ b/R/core.R
-@@ -153,7 +153,7 @@ NULL
+@@ -156,7 +156,7 @@ NULL
#' Wald significance tests (defined by \code{\link{nbinomWaldTest}}),
#' or the likelihood ratio test on the difference in deviance between a
#' full and reduced model formula (defined by \code{\link{nbinomLRT}})
@@ -11,7 +11,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
#' for the type of fitting of dispersions to the mean intensity.
#' See \code{\link{estimateDispersions}} for description.
#' @param betaPrior whether or not to put a zero-mean normal prior on
-@@ -202,7 +202,6 @@ NULL
+@@ -206,7 +206,6 @@ NULL
#' Michael I Love, Wolfgang Huber, Simon Anders: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 2014, 15:550. \url{http://dx.doi.org/10.1186/s13059-014-0550-8}
#' @import BiocGenerics BiocParallel S4Vectors IRanges GenomicRanges SummarizedExperiment Biobase Rcpp methods
#'
@@ -19,7 +19,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
#' @importFrom genefilter rowVars filtered_p
#' @importFrom Hmisc wtd.quantile
#'
-@@ -234,14 +233,14 @@ NULL
+@@ -242,14 +241,14 @@ NULL
#'
#' @export
DESeq <- function(object, test=c("Wald","LRT"),
@@ -36,7 +36,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
stopifnot(is.logical(quiet))
stopifnot(is.numeric(minReplicatesForReplace))
stopifnot(is.logical(parallel))
-@@ -495,7 +494,7 @@ estimateSizeFactorsForMatrix <- function
+@@ -507,7 +506,7 @@ estimateSizeFactorsForMatrix <- function
#' examples below.
#'
#' @param object a DESeqDataSet
@@ -45,7 +45,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
#' for the type of fitting of dispersions to the mean intensity.
#' See \code{\link{estimateDispersions}} for description.
#' @param outlierSD the number of standard deviations of log
-@@ -694,7 +693,7 @@ estimateDispersionsGeneEst <- function(o
+@@ -721,7 +720,7 @@ estimateDispersionsGeneEst <- function(o
#' @rdname estimateDispersionsGeneEst
#' @export
@@ -54,7 +54,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
minDisp=1e-8, quiet=FALSE) {
if (is.null(mcols(object)$allZero)) {
-@@ -711,7 +710,7 @@ estimateDispersionsFit <- function(objec
+@@ -738,7 +737,7 @@ estimateDispersionsFit <- function(objec
...then continue with testing using nbinomWaldTest or nbinomLRT")
}
@@ -63,7 +63,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
stopifnot(length(fitType)==1)
stopifnot(length(minDisp)==1)
if (fitType == "parametric") {
-@@ -725,18 +724,18 @@ estimateDispersionsFit <- function(objec
+@@ -752,18 +751,18 @@ estimateDispersionsFit <- function(objec
fitType <- "local"
}
}
@@ -88,7 +88,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
stop("unknown fitType")
}
-@@ -1849,16 +1848,17 @@ parametricDispersionFit <- function( mea
+@@ -1838,16 +1837,17 @@ parametricDispersionFit <- function( mea
# Local fit of dispersion to the mean intensity
# fitting is done on log dispersion, log mean scale
@@ -118,7 +118,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
# convenience function for testing the log likelihood
--- a/R/methods.R
+++ b/R/methods.R
-@@ -493,7 +493,7 @@ estimateSizeFactors.DESeqDataSet <- func
+@@ -506,7 +506,7 @@ estimateSizeFactors.DESeqDataSet <- func
setMethod("estimateSizeFactors", signature(object="DESeqDataSet"),
estimateSizeFactors.DESeqDataSet)
@@ -127,7 +127,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
maxit=100, quiet=FALSE, modelMatrix=NULL) {
# Temporary hack for backward compatibility with "old" DESeqDataSet
# objects. Remove once all serialized DESeqDataSet objects around have
-@@ -522,7 +522,7 @@ this column could have come in during co
+@@ -535,7 +535,7 @@ this column could have come in during co
mcols(object) <- mcols(object)[,!(mcols(mcols(object))$type %in% c("intermediate","results")),drop=FALSE]
}
stopifnot(length(maxit)==1)
@@ -136,7 +136,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
noReps <- checkForExperimentalReplicates(object, modelMatrix)
if (noReps) {
-@@ -615,7 +615,7 @@ checkForExperimentalReplicates <- functi
+@@ -628,7 +628,7 @@ checkForExperimentalReplicates <- functi
#' @rdname estimateDispersions
#' @aliases estimateDispersions estimateDispersions,DESeqDataSet-method
#' @param object a DESeqDataSet
@@ -145,7 +145,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
#' for the type of fitting of dispersions to the mean intensity.
#' \itemize{
#' \item parametric - fit a dispersion-mean relation of the form:
-@@ -623,10 +623,6 @@ checkForExperimentalReplicates <- functi
+@@ -636,10 +636,6 @@ checkForExperimentalReplicates <- functi
#' via a robust gamma-family GLM. The coefficients \code{asymptDisp} and \code{extraPois}
#' are given in the attribute \code{coefficients} of the \code{\link{dispersionFunction}}
#' of the object.
@@ -180,47 +180,6 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
}
}
---- a/inst/doc/DESeq2.Rnw
-+++ b/inst/doc/DESeq2.Rnw
-@@ -961,9 +961,7 @@ Above, we used a parametric fit for the
- closed-form expression for the variance stabilizing transformation is
- used by \Rfunction{varianceStabilizingTransformation}, which is
- derived in the file \texttt{vst.pdf}, that is distributed in the
--package alongside this vignette. If a local fit is used (option
--\Robject{fitType="locfit"} to \Rfunction{estimateDispersions}) a
--numerical integration is used instead.
-+package alongside this vignette.
-
- <<vsd1, echo=FALSE, fig.width=4.5, fig.height=4.5, fig.show="asis", fig.small=TRUE, fig.pos="!bt", fig.cap="VST and log2. Graphs of the variance stabilizing transformation for sample 1, in blue, and of the transformation $f(n) = \\log_2(n/s_1)$, in black. $n$ are the counts and $s_1$ is the size factor for the first sample.\\label{figure/vsd1-1}">>=
- px <- counts(dds)[,1] / sizeFactors(dds)[1]
---- a/tests/testthat/test_disp_fit.R
-+++ b/tests/testthat/test_disp_fit.R
-@@ -78,7 +78,7 @@ expect_equal(dispD2DESeq, dispD2Num, tol
- # test fit alternative
- dds <- makeExampleDESeqDataSet()
- dds <- estimateSizeFactors(dds)
--ddsLocal <- estimateDispersions(dds, fitType="local")
-+#ddsLocal <- estimateDispersions(dds, fitType="local")
- ddsMean <- estimateDispersions(dds, fitType="mean")
- ddsMed <- estimateDispersionsGeneEst(dds)
- useForMedian <- mcols(ddsMed)$dispGeneEst > 1e-7
---- a/tests/testthat/test_vst.R
-+++ b/tests/testthat/test_vst.R
-@@ -4,7 +4,7 @@ dds <- estimateSizeFactors(dds)
- dds <- estimateDispersionsGeneEst(dds)
- dds <- estimateDispersionsFit(dds, fitType="parametric")
- vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
--dds <- estimateDispersionsFit(dds, fitType="local")
-+#dds <- estimateDispersionsFit(dds, fitType="local")
- vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
- dds <- estimateDispersionsFit(dds, fitType="mean")
- vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
-@@ -28,4 +28,4 @@ vsd <- vst(counts(dds))
- dds <- makeExampleDESeqDataSet(n=100, m=10, betaSD=1.5)
- nf <- matrix(exp(rnorm(1000,0,.2)),ncol=10)
- normalizationFactors(dds) <- nf
--vsd <- varianceStabilizingTransformation(dds, fitType="local")
-+#vsd <- varianceStabilizingTransformation(dds, fitType="local")
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -12,7 +12,7 @@ Description: Estimate variance-mean depe
@@ -231,10 +190,10 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
+ methods, geneplotter, ggplot2, Hmisc, Rcpp (>= 0.11.0)
Depends: S4Vectors (>= 0.9.25), IRanges, GenomicRanges,
SummarizedExperiment (>= 1.1.6)
- Suggests: testthat, knitr, BiocStyle, vsn, pheatmap, RColorBrewer,
+ Suggests: testthat, knitr, BiocStyle, vsn, pheatmap, RColorBrewer, IHW,
--- a/NAMESPACE
+++ b/NAMESPACE
-@@ -86,7 +86,6 @@ importFrom(graphics,axis)
+@@ -88,7 +88,6 @@ importFrom(graphics,axis)
importFrom(graphics,hist)
importFrom(graphics,plot)
importFrom(graphics,points)
@@ -242,32 +201,32 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
importFrom(stats,Gamma)
importFrom(stats,as.formula)
importFrom(stats,coef)
---- a/vignettes/DESeq2.Rnw
-+++ b/vignettes/DESeq2.Rnw
-@@ -961,9 +961,7 @@ Above, we used a parametric fit for the
- closed-form expression for the variance stabilizing transformation is
- used by \Rfunction{varianceStabilizingTransformation}, which is
- derived in the file \texttt{vst.pdf}, that is distributed in the
--package alongside this vignette. If a local fit is used (option
--\Robject{fitType="locfit"} to \Rfunction{estimateDispersions}) a
--numerical integration is used instead.
-+package alongside this vignette.
-
- <<vsd1, echo=FALSE, fig.width=4.5, fig.height=4.5, fig.show="asis", fig.small=TRUE, fig.pos="!bt", fig.cap="VST and log2. Graphs of the variance stabilizing transformation for sample 1, in blue, and of the transformation $f(n) = \\log_2(n/s_1)$, in black. $n$ are the counts and $s_1$ is the size factor for the first sample.\\label{figure/vsd1-1}">>=
- px <- counts(dds)[,1] / sizeFactors(dds)[1]
-@@ -1450,15 +1448,6 @@ and the variability of the gene-wise est
- plotDispEsts(dds)
- @
-
--\subsubsection{Local or mean dispersion fit}
--
--A local smoothed dispersion fit is automatically substitited in the case that
--the parametric curve doesn't fit the observed dispersion mean relationship.
--This can be prespecified by providing the argument
--\Robject{fitType="local"} to either \Rfunction{DESeq} or \Rfunction{estimateDispersions}.
--Additionally, using the mean of gene-wise disperion estimates as the
--fitted value can be specified by providing the argument \Robject{fitType="mean"}.
--
- \subsubsection{Supply a custom dispersion fit}
-
- Any fitted values can be provided during dispersion estimation, using
+--- a/tests/testthat/test_disp_fit.R
++++ b/tests/testthat/test_disp_fit.R
+@@ -78,7 +78,7 @@ test_that("the fitting of dispersion giv
+ # test fit alternative
+ dds <- makeExampleDESeqDataSet()
+ dds <- estimateSizeFactors(dds)
+- ddsLocal <- estimateDispersions(dds, fitType="local")
++# ddsLocal <- estimateDispersions(dds, fitType="local")
+ ddsMean <- estimateDispersions(dds, fitType="mean")
+ ddsMed <- estimateDispersionsGeneEst(dds)
+ useForMedian <- mcols(ddsMed)$dispGeneEst > 1e-7
+--- a/tests/testthat/test_vst.R
++++ b/tests/testthat/test_vst.R
+@@ -6,7 +6,7 @@ test_that("vst works", {
+ dds <- estimateDispersionsGeneEst(dds)
+ dds <- estimateDispersionsFit(dds, fitType="parametric")
+ vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
+- dds <- estimateDispersionsFit(dds, fitType="local")
++# dds <- estimateDispersionsFit(dds, fitType="local")
+ vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
+ dds <- estimateDispersionsFit(dds, fitType="mean")
+ vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
+@@ -30,5 +30,5 @@ test_that("vst works", {
+ dds <- makeExampleDESeqDataSet(n=100, m=10, betaSD=1.5)
+ nf <- matrix(exp(rnorm(1000,0,.2)),ncol=10)
+ normalizationFactors(dds) <- nf
+- vsd <- varianceStabilizingTransformation(dds, fitType="local")
++# vsd <- varianceStabilizingTransformation(dds, fitType="local")
+ })
--
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