Nothing
############################################
# Step 2 - remove flat genes
############################################
removeFlatGenes <- function(eSet, cellTypeTag, contrasts=NULL, limma.cutoff=0.05, ...){
dat.fr <- exprs(eSet)
class.vector <- as.factor(pData(eSet)[,colnames(pData(eSet)) %in% cellTypeTag])
#require(limma)
design <- model.matrix(~0+class.vector)
lev <- levels(class.vector)
colnames(design) <- lev
fit <- lmFit(dat.fr, design)
if( is.null(contrasts) ){
my.contrasts <- NULL
for( i in 1:(length(lev)-1) ){
my.contrasts <- c(my.contrasts, paste(lev[i], lev[i+1], sep=" - "))
}
cont.diff <- makeContrasts(contrasts=my.contrasts, levels=design)
}
else{
my.contrasts <- contrasts
# should probably check that if contrasts is supplied, it's a valid contrast vector
cont.diff <- makeContrasts(contrasts=contrasts, levels=lev)
}
fit2 <- contrasts.fit(fit, cont.diff)
fit2 <- eBayes(fit2)
fit2$genes <- rownames(dat.fr)
tt.all <- topTable(fit2, coef=(1:(length(my.contrasts))), adjust="fdr", n=nrow(dat.fr))
remove.genes <- tt.all[tt.all$adj.P.Val > limma.cutoff,1]
return(remove.genes)
}
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