[BioC] Application of multiple testing correction in the context of using Stouffer's method for combing p-values

[Ochsner, Scott A]

Dear BioC community,

I've been using a weighted Stouffer method to combing p-values (one-tailed) derived from six hgu133a microarray experiments performed by six different labs.  Each experiment roughly address the same null hypothesis:  addition of receptor ligand for 24h has no effect on gene expression.  I have then
taken the combined Stouffer z-score and transformed it back to a two-tailed p-value.   

#z is a vector of combined z-scores, one for each probe set in the hgu133a array.  
>combP<-2*(pnorm(abs(z),lower.tail=FALSE))

My question is:  Is it valid to apply multiple correction to combP similar to something like:
>FDRcombP<-p.adjust(combP,method="BH")

If I were doing a Venn overlap of significant probe sets from these six experiments I would be using probe sets which has passed an FDR corrected p-value threshold.  My gut is telling me to adjust the Stouffer derived significant score for multiple testing as well.

Thanks for any feedback...


Scott A. Ochsner, Ph.D.
NURSA Bioinformatics
Molecular and Cellular Biology
Baylor College of Medicine
Houston, TX. 77030
phone: 713-798-6227