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## GENESET.R
geneSetTest <- function(index,statistics,alternative="mixed",type="auto",ranks.only=TRUE,nsim=9999)
# Competitive gene set test using either rank sum test or simulation.
# Gordon Smyth
# 3 September 2004. Last modified 11 Feb 2012.
{
alternative <- match.arg(alternative,c("mixed","either","down","up","less","greater","two.sided"))
if(alternative=="two.sided") alternative <- "either"
if(alternative=="less") alternative <- "down"
if(alternative=="greater") alternative <- "up"
type <- match.arg(tolower(type),c("auto","t","f"))
allsamesign <- all(statistics >= 0) || all(statistics <= 0)
if(type=="auto") {
if(allsamesign)
type <- "f"
else
type <- "t"
}
if(type=="f" & alternative!="mixed") stop("Only alternative=\"mixed\" is possible with F-like statistics.")
if(alternative=="mixed") statistics <- abs(statistics)
if(alternative=="down") {
statistics <- -statistics
alternative <- "up"
}
if(ranks.only) {
# The test statistic is the mean rank of the selected genewise statistics
# and the p-value is obtained explicitly from the rank sum test
pvalues <- rankSumTestWithCorrelation(index=index,statistics=statistics,df=Inf)
p.value <- switch(alternative,
"down" = pvalues["less"],
"up" = pvalues["greater"],
"either" = 2*min(pvalues),
"mixed" = pvalues["greater"])
} else {
# The global test statistic is the mean of the selected genewise statistics
# and the p-value is obtained by random permutation
ssel <- statistics[index]
ssel <- ssel[!is.na(ssel)]
nsel <- length(ssel)
if(nsel==0) return(1)
stat <- statistics[!is.na(statistics)]
msel <- mean(ssel)
if(alternative=="either")
posstat <- abs
else
posstat <- function(x) x
msel <- posstat(msel)
ntail <- 1
for (i in 1:nsim) if(posstat(mean(sample(stat,nsel))) >= msel) ntail <- ntail+1
p.value <- ntail/(nsim+1)
}
as.vector(p.value)
}
wilcoxGST <- function(index,statistics,...)
# Mean-rank gene set test using Wilcox test.
# Gordon Smyth
# 27 July 2009. Last modified 3 Sep 2011.
geneSetTest(index=index,statistics=statistics,...,ranks.only=TRUE)
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