[med-svn] [r-bioc-deseq2] 07/08: Refresh patches
Andreas Tille
tille at debian.org
Thu Oct 27 21:16:37 UTC 2016
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 0bdca4419a47d6209b115a0e007e9824df5082e2
Author: Andreas Tille <tille at debian.org>
Date: Thu Oct 27 18:40:07 2016 +0200
Refresh patches
---
debian/patches/remove-locfit | 148 +++++++++++++++++++++----------------------
1 file changed, 74 insertions(+), 74 deletions(-)
diff --git a/debian/patches/remove-locfit b/debian/patches/remove-locfit
index 5c53a4f..e796487 100644
--- a/debian/patches/remove-locfit
+++ b/debian/patches/remove-locfit
@@ -1,8 +1,8 @@
Author: Michael R. Crusoe <michael.crusoe at gmail.com>
Description: r-cran-locfit is non-free and not yet packaged for Debian
---- r-bioc-deseq2.orig/R/core.R
-+++ r-bioc-deseq2/R/core.R
-@@ -153,7 +153,7 @@
+--- a/R/core.R
++++ b/R/core.R
+@@ -153,7 +153,7 @@ 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 @@
+@@ -202,7 +202,6 @@ 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 @@
+@@ -234,14 +233,14 @@ 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 @@
+@@ -495,7 +494,7 @@ 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
-@@ -677,7 +676,7 @@
+@@ -694,7 +693,7 @@ 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)$allZero)) {
-@@ -694,7 +693,7 @@
+@@ -711,7 +710,7 @@ estimateDispersionsFit <- function(objec
...then continue with testing using nbinomWaldTest or nbinomLRT")
}
@@ -63,7 +63,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
stopifnot(length(fitType)==1)
stopifnot(length(minDisp)==1)
if (fitType == "parametric") {
-@@ -708,18 +707,18 @@
+@@ -725,18 +724,18 @@ estimateDispersionsFit <- function(objec
fitType <- "local"
}
}
@@ -88,7 +88,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
stop("unknown fitType")
}
-@@ -1828,16 +1827,17 @@
+@@ -1849,16 +1848,17 @@ parametricDispersionFit <- function( mea
# Local fit of dispersion to the mean intensity
# fitting is done on log dispersion, log mean scale
@@ -116,9 +116,9 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
# convenience function for testing the log likelihood
---- r-bioc-deseq2.orig/R/methods.R
-+++ r-bioc-deseq2/R/methods.R
-@@ -493,7 +493,7 @@
+--- a/R/methods.R
++++ b/R/methods.R
+@@ -493,7 +493,7 @@ estimateSizeFactors.DESeqDataSet <- func
setMethod("estimateSizeFactors", signature(object="DESeqDataSet"),
estimateSizeFactors.DESeqDataSet)
@@ -127,7 +127,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
maxit=100, quiet=FALSE, modelMatrix=NULL) {
# Temporary hack for backward compatibility with "old" DESeqDataSet
# objects. Remove once all serialized DESeqDataSet objects around have
-@@ -522,7 +522,7 @@
+@@ -522,7 +522,7 @@ this column could have come in during co
mcols(object) <- mcols(object)[,!(mcols(mcols(object))$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 @@
+@@ -615,7 +615,7 @@ 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 @@
+@@ -623,10 +623,6 @@ 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.
@@ -156,8 +156,8 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
#' \item mean - use the mean of gene-wise dispersion estimates.
#' }
#' @param maxit control parameter: maximum number of iterations to allow for convergence
---- r-bioc-deseq2.orig/R/vst.R
-+++ r-bioc-deseq2/R/vst.R
+--- a/R/vst.R
++++ b/R/vst.R
@@ -53,12 +53,6 @@
#' count data. The expression can be found in the file \file{vst.pdf}
#' which is distributed with the vignette.
@@ -171,7 +171,7 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
#' \code{fitType="mean"}, a VST is applied for Negative Binomial distributed counts, 'k',
#' with a fixed dispersion, 'a': ( 2 asinh(sqrt(a k)) - log(a) - log(4) )/log(2).
#'
-@@ -202,7 +196,7 @@
+@@ -202,7 +196,7 @@ getVarianceStabilizedData <- function(ob
vst <- function(q) ( 2 * asinh(sqrt(alpha * q)) - log(alpha) - log(4) ) / log(2)
return(vst(ncounts))
} else {
@@ -180,22 +180,22 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
}
}
---- r-bioc-deseq2.orig/inst/doc/DESeq2.Rnw
-+++ r-bioc-deseq2/inst/doc/DESeq2.Rnw
-@@ -936,9 +936,7 @@
- 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.
-
- The resulting variance stabilizing transformation is shown in Figure
- \ref{figure/vsd1-1}. The code that produces the figure is hidden from
---- r-bioc-deseq2.orig/tests/testthat/test_disp_fit.R
-+++ r-bioc-deseq2/tests/testthat/test_disp_fit.R
-@@ -78,7 +78,7 @@
+--- 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)
@@ -204,9 +204,9 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
ddsMean <- estimateDispersions(dds, fitType="mean")
ddsMed <- estimateDispersionsGeneEst(dds)
useForMedian <- mcols(ddsMed)$dispGeneEst > 1e-7
---- r-bioc-deseq2.orig/tests/testthat/test_vst.R
-+++ r-bioc-deseq2/tests/testthat/test_vst.R
-@@ -4,7 +4,7 @@
+--- 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)
@@ -215,44 +215,15 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
dds <- estimateDispersionsFit(dds, fitType="mean")
vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
-@@ -28,4 +28,4 @@
+@@ -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")
---- r-bioc-deseq2.orig/vignettes/DESeq2.Rnw
-+++ r-bioc-deseq2/vignettes/DESeq2.Rnw
-@@ -936,9 +936,7 @@
- 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.
-
- The resulting variance stabilizing transformation is shown in Figure
- \ref{figure/vsd1-1}. The code that produces the figure is hidden from
-@@ -1458,15 +1456,6 @@
- estimates used in testing (blue).
- }
-
--\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
---- r-bioc-deseq2.orig/DESCRIPTION
-+++ r-bioc-deseq2/DESCRIPTION
-@@ -13,7 +13,7 @@
+--- a/DESCRIPTION
++++ b/DESCRIPTION
+@@ -12,7 +12,7 @@ Description: Estimate variance-mean depe
License: LGPL (>= 3)
VignetteBuilder: knitr
Imports: BiocGenerics (>= 0.7.5), Biobase, BiocParallel, genefilter,
@@ -261,9 +232,9 @@ Description: r-cran-locfit is non-free and not yet packaged for Debian
Depends: S4Vectors (>= 0.9.25), IRanges, GenomicRanges,
SummarizedExperiment (>= 1.1.6)
Suggests: testthat, knitr, BiocStyle, vsn, pheatmap, RColorBrewer,
---- r-bioc-deseq2.orig/NAMESPACE
-+++ r-bioc-deseq2/NAMESPACE
-@@ -86,7 +86,6 @@
+--- a/NAMESPACE
++++ b/NAMESPACE
+@@ -86,7 +86,6 @@ importFrom(graphics,axis)
importFrom(graphics,hist)
importFrom(graphics,plot)
importFrom(graphics,points)
@@ -271,3 +242,32 @@ 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
--
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