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"?

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