##create example data - a set of 500 genes normally distributed across 40 patients
eset = matrix(rnorm(500*40),500,40, dimnames=list(1:500,1:40))
labels = rep(c("A","B","C","D"),each=10)
##create a number of gene sets with varying levels of differential expression.
geneSets = list()
for(i in 0:10){
genes = ((30*i)+1):(30*(i+1))
eset[genes,labels=="B"] = eset[genes,labels=="B"] + 2 + rnorm(1)
eset[genes,labels=="D"] = eset[genes,labels=="D"] + 1 + rnorm(1)
geneSets[[paste("Set",i)]] = genes
}
##calculate qusage results
qsList = lapply(c("B-A","D-C"), function(comparison){
qusage(eset,labels, comparison, geneSets)
})
##combine the two QSarrays
qsComb = combinePDFs(qsList)
plot(qsComb, path.index=1)
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