Dear Bioc Users,

I'm using the limma library for differential gene expression analysis. I
have a question about how to choose the p-value.

These are my contrasts:

T1 - Control
T2 - Control
T3 - Control
T4 - Control
T5 - Control

Then I applied: fit2 <- contrasts.fit(fit, contrast.matrix); eb <-
eBayes(fit2)

Now I should choose all those genes differentially expressed either by using
topTable or decideTests. However I wouldn't like to choose the p-value
arbitrarily.  I did:

 results <- decideTests(eb, p.value=0.05, method="global",
adjust.method="BH")

I know it means I will get an FDR < 0.05 for the whole set. However I have
no idea about which "method" (from the arguments) would be the right one...
I'm still getting many genes differentially expressed, that's why I'm
wondering whether this is correct or not.

Thank for your help in advance.

Yours,

Avhena

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