[BioC] Extract microarray data for genes identified by GO analysis

[Mark Ebbert]

Hi,

I am using GOstats to identify molecular functions that are over represented. I'm getting conflicting results between a method from an example I found in the lumi vignette and using probeSetSummary. Specifically, to get the list of significant categories, I was using the following code:

mfOver1 <- hyperGTest(params.mf1)
mf.gGhyp.pv1 <- pvalues(mfOver1)
mf.sigGO.ID.pv1 <- names(mf.gGhyp.pv1[mf.gGhyp.pv1 < 0.05])
mf.sigGO.Term.pv1 <- getGOTerm(mf.sigGO.ID.pv1)[["MF"]]
length(mf.sigGO.Term.pv1)

The number of resulting GO terms based on this code is 105. If I use probeSetSummary, however, I only get 92 significant GO terms. Here is the code I'm using:

ps1<-probeSetSummary(mfOver1,0.05,sigProbesets=probeList)
length(ps1)



My understanding is that both methods should select only those categories with a p-value < 0.05, but I have no doubt misunderstood something.

Thanks for your help!

Mark