**0**wrote:

Dear Bioconductors,

I recently used GSVA to get enrichment scores for three gene sets and four sample groups. From the enrichment scores, I am interested in determining if they are differentially expressed across several sample groups. I intend to do many sets of comparisons and thus I was planning to create separate contrast matrices for each set of comparisons. However, I am wondering if it is incorrect to break up these comparisons into separate matrices and if I instead should combine all comparisons for the study into one contrast matrix. Further, though I have used the Benjamini-Hochberg procedure for multiple comparisons, I think I have what is considered planned comparisons (i.e. only a few sensible comparisons which were decided before looking at the data). As such, is it incorrect to use the BH method or would you recommend using Bonferroni corretion?

Thanks,

SB

Does the gsva_es matrix that you enter to limma have only 3 rows?

39kYes, three rows since I am only interested in examining enrichment of 3 gene sets in the above samples.

0With only three rows, there's hardly any empirical Bayes moderation for limma to do. So the results from limma will be nearly the same as if you did a linear model or anova analysis for each row separately. There's no possible harm in using limma however if you find it convenient.

39k