Maybe I am missing something, but when I run camera with any annotation I can find I never get any differently expressed gene sets, when I get so so many more with mroast and romer. For example this is running on my differentially expressed human microarray genes with GO gene sets.
results <- camera(rows.to.keep, c2.indices, design,contrast=2) results2 <- mroast(rows.to.keep, c2.indices,design,contrast=2,nrot=999) results3 <- romer(rows.to.keep, c2.indices,design,contrast=2,nrot=999) significant_up <- subset(results3, Up <= 0.05) significant_down <- subset(results3, Down <= 0.05) significant <- rbind(significant_up, significant_down) significant2 <- subset(results2, FDR <= 0.05) significant3 <- subset(results, FDR <= 0.05)
significant camera = 0
significant romer = 111
significant mroast = 502
So why is this? I guess cameras statistical method must be a lot more conservative, but it seems conservative to the extent where it is useless for all practical purposes. This seems a bit of a shame to me. Am I just using it in the wrong situation or something? I have not read the papers.