Hello, I have a short question about decideTests. I've read a few postings on this topic and I thought that I understood the difference between "global" and "separate". My understanding is that "global" considers all the contrasts which means it is considering many more hypothesis tests than "separate". I ran some analysis using "global" and then I realized that since my gene lists of interest were different for each contrast, I decided that "separate" may be the better choice. What puzzled me is that I found more differential expression using "global" than I did with "separate". I thought that more tests would always lead to higher adjusted p-values and fewer inferences of differential expression. There was a note of caution from Gordon Smyth posted on the list about being careful not to include spurious contrasts. In my case, the other contrasts are not really spurious, they just not the contrasts of interest for that particular subset. The subsets do overlap and probably by a large fraction, that was why I chose "global" at first. So here is some example code: > filtered_results_global_ref <- decideTests(fit2_tissues,method="global",adjust.method="BH",p.value=0. 05,lfc=log2(1.2))[names(which(selected)), 1] > standard_DE_down_global <- which (filtered_results_global_ref== -1) > length(standard_DE_down_global) [1] 274 repeating the above using "separate" gives me fewer significant down-regulated genes. [1] 244 filtered_results_global_ref <- decideTests(fit2_tissues [names(which(selected)), 1],method="global",adjust.method="BH",p.value=0.05,lfc=log2(1.2)) #This one is the same as using method "separate" because I really am only considering one contrast. > standard_DE_down_global <- which (filtered_results_global_ref== -1) > length(standard_DE_down_global) [1] 244 My questions are 1. Why are there fewer significant results for "separate" than for "global"? [[alternative HTML version deleted]]