[med-svn] [r-bioc-limma] 01/04: New upstream version 3.34.0+dfsg
Andreas Tille
tille at debian.org
Fri Nov 10 15:30:10 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-limma.
commit b46630dcbc0e0e2bb109a6e49d79ec65104b1255
Author: Andreas Tille <tille at debian.org>
Date: Fri Nov 10 16:24:24 2017 +0100
New upstream version 3.34.0+dfsg
---
DESCRIPTION | 6 +-
R/goana.R | 187 +++++++++++++++++++++++++------------------------
R/kegga.R | 9 +--
inst/NEWS.Rd | 62 ++++++++++++++++
inst/doc/changelog.txt | 36 +++++++---
inst/doc/intro.pdf | Bin 43301 -> 43301 bytes
man/goana.Rd | 6 +-
man/normalizeVSN.Rd | 2 +-
man/wsva.Rd | 2 +-
9 files changed, 196 insertions(+), 114 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
old mode 100755
new mode 100644
index 8f65beb..40736d8
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: limma
-Version: 3.32.10
-Date: 2017-10-12
+Version: 3.34.0
+Date: 2017-10-11
Title: Linear Models for Microarray Data
Description: Data analysis, linear models and differential expression for microarray data.
Author: Gordon Smyth [cre,aut], Yifang Hu [ctb], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Davis McCarthy [ctb], Di Wu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Aaron Lun [ctb], Natalie Thorne [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yunshun Chen [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb]
@@ -21,4 +21,4 @@ biocViews: ExonArray, GeneExpression, Transcription,
MultipleComparison, Normalization, Preprocessing,
QualityControl
NeedsCompilation: yes
-Packaged: 2017-10-12 22:15:31 UTC; biocbuild
+Packaged: 2017-10-30 22:37:20 UTC; biocbuild
diff --git a/R/goana.R b/R/goana.R
index 3335a64..e84af7f 100644
--- a/R/goana.R
+++ b/R/goana.R
@@ -77,38 +77,8 @@ goana.MArrayLM <- function(de, coef = ncol(de), geneid = rownames(de), FDR = 0.0
goana.default <- function(de, universe = NULL, species = "Hs", prior.prob = NULL, covariate=NULL, plot=FALSE, ...)
# Gene ontology analysis of DE genes
# Gordon Smyth and Yifang Hu
-# Created 20 June 2014. Last modified 23 June 2016.
+# Created 20 June 2014. Last modified 16 July 2017.
{
-# Ensure de is a list
- if(!is.list(de)) de <- list(DE = de)
-
-# Stop if components of de are not vectors
- if(!all(vapply(de,is.vector,TRUE))) stop("components of de should be vectors")
-
-# Ensure gene IDs are of character mode
- de <- lapply(de, as.character)
- if(!is.null(universe)) universe <- as.character(universe)
-
-# Ensure all gene sets have unique names
- nsets <- length(de)
- names(de) <- trimWhiteSpace(names(de))
- NAME <- names(de)
- i <- which(NAME == "" | is.na(NAME))
- NAME[i] <- paste0("DE",i)
- names(de) <- makeUnique(NAME)
-
-# Fit trend in DE with respect to the covariate, combining all de lists
- if(!is.null(covariate)) {
- covariate <- as.numeric(covariate)
- if(length(covariate) != length(covariate)) stop("universe and covariate must have same length")
- isDE <- as.numeric(universe %in% unlist(de))
- o <- order(covariate)
- prior.prob <- covariate
- span <- approx(x=c(20,200),y=c(1,0.5),xout=sum(isDE),rule=2)$y
- prior.prob[o] <- tricubeMovingAverage(isDE[o],span=span)
- if(plot) barcodeplot(covariate, index=(isDE==1), worm=TRUE, span.worm=span)
- }
-
# Get access to package of GO terms
suppressPackageStartupMessages(OK <- requireNamespace("GO.db",quietly=TRUE))
if(!OK) stop("GO.db package required but not installed (or can't be loaded)")
@@ -127,91 +97,126 @@ goana.default <- function(de, universe = NULL, species = "Hs", prior.prob = NULL
egGO2ALLEGS <- tryCatch(getFromNamespace(obj,orgPkg), error=function(e) FALSE)
if(is.logical(egGO2ALLEGS)) stop("Can't find gene ontology mappings in package ",orgPkg)
-# Convert gene-GOterm mappings to data.frame and remove duplicate entries
+# Convert gene-GOterm mappings to data.frame
+# Remove duplicate entries from both mappings and universe
if(is.null(universe)) {
- EG.GO <- AnnotationDbi::toTable(egGO2ALLEGS)
- d <- duplicated(EG.GO[,c("gene_id", "go_id", "Ontology")])
- EG.GO <- EG.GO[!d, ]
- universe <- unique(EG.GO$gene_id)
- universe <- as.character(universe)
+ GeneID.PathID <- AnnotationDbi::toTable(egGO2ALLEGS)[,c("gene_id","go_id","Ontology")]
+ i <- !duplicated(GeneID.PathID[,c("gene_id", "go_id")])
+ GeneID.PathID <- GeneID.PathID[i, ]
+ universe <- unique(GeneID.PathID[,1])
+ prior.prob <- covariate <- NULL
} else {
-
universe <- as.character(universe)
-
- dup <- duplicated(universe)
- if(!is.null(prior.prob)) {
- if(length(prior.prob)!=length(universe)) stop("length(prior.prob) must equal length(universe)")
- prior.prob <- rowsum(prior.prob,group=universe,reorder=FALSE)
- n <- rowsum(rep_len(1L,length(universe)),group=universe,reorder=FALSE)
- prior.prob <- prior.prob/n
+ lu <- length(universe)
+ if(!is.null(prior.prob) && length(prior.prob)!=lu) stop("universe and prior.prob must have same length")
+ if(!is.null(covariate) && length(covariate)!=lu) stop("universe and covariate must have same length")
+ if(anyDuplicated(universe)) {
+ i <- !duplicated(universe)
+ if(!is.null(covariate)) covariate <- covariate[i]
+ if(!is.null(prior.prob)) prior.prob <- prior.prob[i]
+ universe <- universe[i]
}
- universe <- universe[!dup]
-
- m <- match(AnnotationDbi::Lkeys(egGO2ALLEGS),universe,0L)
- universe <- universe[m]
- if(!is.null(prior.prob)) prior.prob <- prior.prob[m]
-
+ universe <- intersect(AnnotationDbi::Lkeys(egGO2ALLEGS),universe)
AnnotationDbi::Lkeys(egGO2ALLEGS) <- universe
- EG.GO <- AnnotationDbi::toTable(egGO2ALLEGS)
- d <- duplicated(EG.GO[,c("gene_id", "go_id", "Ontology")])
- EG.GO <- EG.GO[!d, ]
+ GeneID.PathID <- AnnotationDbi::toTable(egGO2ALLEGS)[,c("gene_id","go_id","Ontology")]
+ d <- duplicated(GeneID.PathID[,c("gene_id", "go_id")])
+ GeneID.PathID <- GeneID.PathID[!d, ]
}
- Total <- length(unique(EG.GO$gene_id))
- if(Total<1L) stop("No genes found in universe")
+# From here, code is mostly the same as kegga.default
-# Check prior probabilities
- if(!is.null(prior.prob)) {
- if(length(prior.prob)!=length(universe)) stop("length(prior.prob) must equal length(universe)")
- }
+# Ensure de is a list
+ if(!is.list(de)) de <- list(DE = de)
+ nsets <- length(de)
+
+# Stop if components of de are not vectors
+ if(!all(vapply(de,is.vector,TRUE))) stop("components of de should be vectors")
+
+# Ensure de gene IDs are unique and of character mode
+ for (s in 1:nsets) de[[s]] <- unique(as.character(de[[s]]))
+
+# Ensure de components have unique names
+ names(de) <- trimWhiteSpace(names(de))
+ NAME <- names(de)
+ i <- which(NAME == "" | is.na(NAME))
+ NAME[i] <- paste0("DE",i)
+ names(de) <- makeUnique(NAME)
-# Overlap with DE genes
- isDE <- lapply(de, function(x) EG.GO$gene_id %in% x)
- TotalDE <- lapply(isDE, function(x) length(unique(EG.GO$gene_id[x])))
- nDE <- length(isDE)
+# Check universe isn't empty
+ NGenes <- length(universe)
+ if(NGenes<1L) stop("No annotated genes found in universe")
- if(length(prior.prob)) {
- # Probability weight for each gene
- m <- match(EG.GO$gene_id, universe)
- PW2 <- list(prior.prob[m])
- X <- do.call(cbind, c(N=1, isDE, PW=PW2))
- } else
- X <- do.call(cbind, c(N=1, isDE))
+# Restrict DE genes to universe
+ for (s in 1:nsets) de[[s]] <- de[[s]][de[[s]] %in% universe]
- group <- paste(EG.GO$go_id, EG.GO$Ontology, sep=".")
- S <- rowsum(X, group=group, reorder=FALSE)
+# Restrict pathways to universe
+ i <- GeneID.PathID[,1] %in% universe
+ if(sum(i)==0L) stop("Pathways do not overlap with universe")
+ GeneID.PathID <- GeneID.PathID[i,]
- P <- matrix(0, nrow = nrow(S), ncol = nsets)
+# Get prior.prob trend in DE with respect to the covariate, combining all de lists
+ if(!is.null(covariate)) {
+ if(!is.null(prior.prob)) message("prior.prob being recomputed from covariate")
+ covariate <- as.numeric(covariate)
+ isDE <- (universe %in% unlist(de))
+ o <- order(covariate)
+ prior.prob <- covariate
+ span <- approx(x=c(20,200),y=c(1,0.5),xout=sum(isDE),rule=2)$y
+ prior.prob[o] <- tricubeMovingAverage(isDE[o],span=span)
+ if(plot) barcodeplot(covariate, index=isDE, worm=TRUE, span.worm=span, main="DE status vs covariate")
+ }
- if(length(prior.prob)) {
+# Overlap pathways with DE genes
+# Create incidence matrix (X) of gene.pathway by DE sets
+ if(is.null(prior.prob)) {
+ X <- matrix(1,nrow(GeneID.PathID),nsets+1)
+ colnames(X) <- c("N",names(de))
+ } else {
+ names(prior.prob) <- universe
+ X <- matrix(1,nrow(GeneID.PathID),nsets+2)
+ X[,nsets+2] <- prior.prob[GeneID.PathID[,1]]
+ colnames(X) <- c("N",names(de),"PP")
+ }
+ for (s in 1:nsets) X[,s+1] <- (GeneID.PathID[,1] %in% de[[s]])
-# Calculate average prior prob for each set
- PW.ALL <- sum(prior.prob[universe %in% EG.GO$gene_id])
- AVE.PW <- S[,"PW"]/S[,"N"]
- W <- AVE.PW*(Total-S[,"N"])/(PW.ALL-S[,"N"]*AVE.PW)
+# Count #genes and #DE genes and sum prior.prob for each pathway
+ S <- rowsum(X, group=GeneID.PathID[,2], reorder=FALSE)
+
+# Overlap tests
+ PValue <- matrix(0,nrow=nrow(S),ncol=nsets)
+ colnames(PValue) <- paste("P", names(de), sep=".")
+ nde <- lengths(de, use.names=FALSE)
+ if(!is.null(prior.prob)) {
+
+# Probability ratio for each pathway vs rest of universe
+ SumPP <- sum(prior.prob)
+ M2 <- NGenes-S[,"N"]
+ Odds <- S[,"PP"] / (SumPP-S[,"PP"]) * M2 / S[,"N"]
# Wallenius' noncentral hypergeometric test
+# Note that dWNCHypergeo() is more accurate than pWNCHypergeo(), hence use of 2-terms
if(!requireNamespace("BiasedUrn",quietly=TRUE)) stop("BiasedUrn package required but is not installed (or can't be loaded)")
- for(j in 1:nsets) for(i in 1:nrow(S))
- P[i,j] <- BiasedUrn::pWNCHypergeo(S[i,1+j], S[i,"N"], Total-S[i,"N"], TotalDE[[j]], W[i],lower.tail=FALSE) + BiasedUrn::dWNCHypergeo(S[i,1+j], S[i,"N"], Total-S[i,"N"], TotalDE[[j]], W[i])
+ for(j in seq_len(nsets)) for(i in seq_len(nrow(S)))
+ PValue[i,j] <- BiasedUrn::pWNCHypergeo(S[i,1L+j], S[i,"N"], M2[i], nde[j], Odds[i], lower.tail=FALSE) +
+ BiasedUrn::dWNCHypergeo(S[i,1L+j], S[i,"N"], M2[i], nde[j], Odds[i])
+
+# Remove sum of prob column, not needed for output
S <- S[,-ncol(S)]
} else {
- # Fisher's exact test
- for(j in 1:nsets)
- P[,j] <- phyper(q=S[,1+j]-0.5,m=TotalDE[[j]],n=Total-TotalDE[[j]], k=S[,"N"],lower.tail=FALSE)
+# Fisher's exact test
+ for(j in seq_len(nsets))
+ PValue[,j] <- phyper(S[,1L+j]-0.5, nde[j], NGenes-nde[j], S[,"N"], lower.tail=FALSE)
}
# Assemble output
- g <- strsplit2(rownames(S),split="\\.")
- TERM <- suppressMessages(AnnotationDbi::select(GO.db::GO.db,keys=g[,1],columns="TERM"))
- Results <- data.frame(Term = TERM[[2]], Ont = g[,2], S, P, stringsAsFactors=FALSE)
- rownames(Results) <- g[,1]
-
-# Name p-value columns
- colnames(Results)[3+nsets+(1L:nsets)] <- paste0("P.", names(de))
+ GOID <- rownames(S)
+ TERM <- suppressMessages(AnnotationDbi::select(GO.db::GO.db,keys=GOID,columns="TERM"))
+ m <- match(GOID,GeneID.PathID[,2])
+ Ont <- GeneID.PathID[m,3]
+ Results <- data.frame(Term=TERM[,2], Ont=Ont, S, PValue, stringsAsFactors=FALSE)
Results
}
diff --git a/R/kegga.R b/R/kegga.R
index 5d04fca..7d642cc 100644
--- a/R/kegga.R
+++ b/R/kegga.R
@@ -74,7 +74,7 @@ kegga.MArrayLM <- function(de, coef = ncol(de), geneid = rownames(de), FDR = 0.0
kegga(de=DEGenes, universe = universe, ...)
}
-kegga.default <- function(de, universe=NULL, restrict.universe=TRUE, species="Hs", species.KEGG=NULL, convert=FALSE, gene.pathway=NULL, pathway.names = NULL,prior.prob=NULL, covariate=NULL, plot=FALSE, ...)
+kegga.default <- function(de, universe=NULL, restrict.universe=FALSE, species="Hs", species.KEGG=NULL, convert=FALSE, gene.pathway=NULL, pathway.names = NULL,prior.prob=NULL, covariate=NULL, plot=FALSE, ...)
# KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis of DE genes
# Gordon Smyth and Yifang Hu
# Created 18 May 2015. Modified 14 Jul 2016.
@@ -173,11 +173,7 @@ kegga.default <- function(de, universe=NULL, restrict.universe=TRUE, species="H
if(NGenes<1L) stop("No annotated genes found in universe")
# Restrict DE genes to universe
- nde <- rep_len(0L,nsets)
- for (s in 1:nsets) {
- de[[s]] <- de[[s]][de[[s]] %in% universe]
- nde[s] <- length(de[[s]])
- }
+ for (s in 1:nsets) de[[s]] <- de[[s]][de[[s]] %in% universe]
# Restrict pathways to universe
i <- GeneID.PathID[,1] %in% universe
@@ -215,6 +211,7 @@ kegga.default <- function(de, universe=NULL, restrict.universe=TRUE, species="H
# Overlap tests
PValue <- matrix(0,nrow=nrow(S),ncol=nsets)
colnames(PValue) <- paste("P", names(de), sep=".")
+ nde <- lengths(de, use.names=FALSE)
if(!is.null(prior.prob)) {
# Probability ratio for each pathway vs rest of universe
diff --git a/inst/NEWS.Rd b/inst/NEWS.Rd
index a73fe0d..59d051f 100644
--- a/inst/NEWS.Rd
+++ b/inst/NEWS.Rd
@@ -3,6 +3,68 @@
\encoding{UTF-8}
+\section{Version 3.34.0}{\itemize{
+
+\item
+read.idat() can now handle idat files in SNP format.
+
+\item
+New argument 'sort.by' for topSplice().
+
+\item
+diffSplice() now treats any NA geneid as a separate gene with one
+ exon. Previously all NA geneids were treated as the same gene.
+
+\item
+Bug fixes for plotSplice() which, in some circumstances, was not
+ highlight significant exons.
+
+\item
+Default value for 'style' in volcanoplot() changed to "p-value"
+ instead of "p". This doesn't change the behavior of the function.
+
+\item
+volcanoplot() didn't work with MArrayLM objects produced by
+ treat(). Now fixed.
+
+\item
+The gene.info.file argument of alias2SymbolUsingNCBI() will now
+ optionally accept a data.frame instead of a file name.
+
+\item
+alias2SymbolUsingNCBI() now always produces a data.frame.
+ Previously a single-column data.frame was returned as a vector.
+
+\item
+Bug fixes to camera() and cameraPR() when 'index' contains character row names.
+
+\item
+New argument 'restrict.universe' for the default kegga() method.
+ The default is now not to the restrict the universe to genes with
+ KEGG annotation.
+
+\item
+goana.default() code is rewritten to more closely match
+ kegga.default. Slight speed improvement. Prior probabilities are now
+ computed using the restricted universe with GO annotation instead of
+ the whole universe.
+
+\item
+Bug fix for kegga() when trend=TRUE or a prior.prob or covariate is
+ specified. Previously the Down p-values were substantially too small
+ and the Up p-values were too large.
+
+\item
+plotWithHighlights() checks whether 'status' is a factor and
+ converts to character.
+
+\item
+Bug fixes for beadCountWeights(). Default is now set correct for
+ 'design' and the function now works correctly when 'y' is an EList
+ object contain bead standard errors but not standard deviations.
+}}
+
+
\section{Version 3.32.0}{\itemize{
\item
diff --git a/inst/doc/changelog.txt b/inst/doc/changelog.txt
index 2ecd58a..798ed48 100755
--- a/inst/doc/changelog.txt
+++ b/inst/doc/changelog.txt
@@ -1,30 +1,36 @@
- 4 Oct 2017: limma 3.32.8
-
+ 4 Oct 2017: limma 3.33.13
+
- Bug fixes for beadCountWeights(). Default is now set correct for
'design' and the function now works correctly when 'y' is an EList
object contain bead standard errors but not standard deviations.
+29 Sep 2017: limma 3.33.12
+
- Bug fixes for plotSplice() which, in some circumstances, was not
highlight significant exons.
+29 Sep 2017: limma 3.33.11
+
- New argument 'sort.by' for topSplice().
-21 Sep 2017: limma 3.32.7
-
+21 Sep 2017: limma 3.33.10
+
- volcanoplot() didn't work with MArrayLM objects produced by
treat(). Now fixed.
-10 Sep 2017: limma 3.32.6
+10 Sep 2017: limma 3.33.9
- read.idat() can now handle idat files in SNP format.
+
+10 Sep 2017: limma 3.33.8
- Bug fix to cameraPR() when 'index' contains character row names.
-30 Jul 2017: limma 3.32.5
+30 Jul 2017: limma 3.33.7
- Bug fix to camera() when 'index' contains character row names.
-25 Jul 2017: limma 3.32.4
+25 Jul 2017: limma 3.33.6
- alias2SymbolUsingNCBI() now always produces a data.frame.
Previously a single-column data.frame was returned as a vector.
@@ -32,7 +38,14 @@
- Default value for 'style' in volcanoplot() changed to "p-value"
instead of "p". This doesn't change the behavior of the function.
-15 Jul 2017: limma 3.32.3
+16 Jul 2017: limma 3.33.5
+
+- goana.default() code is rewritten to more closely match
+ kegga.default. Slight speed improvement. Prior probabilities are now
+ computed using the restricted universe with GO annotation instead of
+ the whole universe.
+
+15 Jul 2017: limma 3.33.4
- New argument 'restrict.universe' for the default kegga() method.
The default is now not to the restrict the universe to genes with
@@ -42,19 +55,22 @@
specified. Previously the Down p-values were substantially too small
and the Up p-values were too large.
+12 May 2017: limma 3.33.3
+
- plotWithHighlights() checks whether 'status' is a factor and
converts to character.
- 1 May 2017: limma 3.32.2
+ 1 May 2017: limma 3.33.2
- The gene.info.file argument of alias2SymbolUsingNCBI() will now
optionally accept a data.frame instead of a file name.
-25 Apr 2017: limma 3.32.1
+25 Apr 2017: limma 3.33.1
- diffSplice() now treats any NA geneid as a separate gene with one
exon. Previously all NA geneids were treated as the same gene.
+25 Apr 2017: limma 3.33.0 (Bioconductor 3.6 Developmental Branch)
25 Apr 2017: limma 3.32.0 (Bioconductor 3.5 Release Branch)
22 Apr 2017: limma 3.31.22
diff --git a/inst/doc/intro.pdf b/inst/doc/intro.pdf
index 5ed4444..60dfe12 100644
Binary files a/inst/doc/intro.pdf and b/inst/doc/intro.pdf differ
diff --git a/man/goana.Rd b/man/goana.Rd
index b48ac5e..f8d4c52 100644
--- a/man/goana.Rd
+++ b/man/goana.Rd
@@ -18,7 +18,7 @@ Test for over-representation of gene ontology (GO) terms or KEGG pathways in one
\method{kegga}{MArrayLM}(de, coef = ncol(de), geneid = rownames(de), FDR = 0.05, trend = FALSE, \dots)
\method{goana}{default}(de, universe = NULL, species = "Hs", prior.prob = NULL, covariate=NULL,
plot=FALSE, \dots)
-\method{kegga}{default}(de, universe = NULL, restrict.universe = TRUE, species = "Hs", species.KEGG = NULL,
+\method{kegga}{default}(de, universe = NULL, restrict.universe = FALSE, species = "Hs", species.KEGG = NULL,
convert = FALSE, gene.pathway = NULL, pathway.names = NULL,
prior.prob = NULL, covariate=NULL, plot=FALSE, \dots)
getGeneKEGGLinks(species.KEGG = "hsa", convert = FALSE)
@@ -56,7 +56,7 @@ getKEGGPathwayNames(species.KEGG = NULL, remove.qualifier = FALSE)
\item{universe}{vector specifying the set of Entrez Gene identifiers to be the background universe.
If \code{NULL} then all Entrez Gene IDs associated with any gene ontology term will be used as the universe.}
- \item{restrict.universe}{logical, should the \code{universe} be restricted to gene identifiers found in \code{gene.pathway}?}
+ \item{restrict.universe}{logical, should the \code{universe} be restricted to gene identifiers found in at least one pathway in \code{gene.pathway}?}
\item{prior.prob}{optional numeric vector of the same length as \code{universe} giving the prior probability that each gene in the universe appears in a gene set.
Will be computed from \code{covariate} if the latter is provided.
@@ -117,6 +117,8 @@ While \code{\link{tricubeMovingAverage}} does not enforce monotonicity, it has t
The default for \code{kegga} with \code{species="Dm"} changed from \code{convert=TRUE} to \code{convert=FALSE} in limma 3.27.8.
Users wanting to use Entrez Gene IDs for Drosophila should set \code{convert=TRUE}, otherwise fly-base IDs are assumed.
+The default for \code{restrict.universe=TRUE} in \code{kegga} changed from \code{TRUE} to \code{FALSE} in limma 3.33.4.
+
Bug fix: results from \code{kegga} with \code{trend=TRUE} or with non-NULL \code{covariate} were incorrect prior to limma 3.32.3.
The results were biased towards significant Down p-values and against significant Up p-values.
}
diff --git a/man/normalizeVSN.Rd b/man/normalizeVSN.Rd
index 8309ae8..baff26b 100644
--- a/man/normalizeVSN.Rd
+++ b/man/normalizeVSN.Rd
@@ -46,7 +46,7 @@ Bioinformatics 18 Supplement 1, S96-S104.
\seealso{
An overview of LIMMA functions for normalization is given in \link{05.Normalization}.
- See also \code{\link[vsn:vsn]{vsn}} and \code{\link[vsn:vsn2]{vsnMatrix}} in the vsn package.
+ See also \code{\link[vsn:vsn2]{vsnMatrix}} in the vsn package.
}
\examples{
diff --git a/man/wsva.Rd b/man/wsva.Rd
index 67beeee..d3b5db9 100644
--- a/man/wsva.Rd
+++ b/man/wsva.Rd
@@ -36,5 +36,5 @@ If \code{weight.by.sd=FALSE}, then the method is a simplification of the approac
\references{
Leek, JT, Storey, JD (2007).
Capturing heterogeneity in gene expression studies by surrogate variable analysis.
-PLoS Genetics 3, 1724-1735.
+\emph{PLoS Genetics} 3, 1724-1735.
}
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