[BioC] statistics for differential expression: adjusted p-values<0.05 BUT negative B-odds?

[Paolo Innocenti]

> What makes me worry is that in my statistics I have low adj.p-value 0.03
> together with negative B-values.
> How do I have to handle this discrepance? Is this a hint that something is
> wrong with my normalization?

In the limma userguide they also say:

"The B-statistic is automatically adjusted for multiple testing by 
assuming that 1% of the genes, or some other percentage specified by the 
user in the call to eBayes(), are expected to be differentially expressed."

and

"The B-statistic probabilities depend on the same assumptions but 
require in addition a prior guess for the proportion of differentially 
expressed genes."

So I think your problem is that the number of differentially expressed 
genes in your experiment is higher that the proportion eBayes assumes 
(proportion=0.01)

Try to specify it in eBayes like this:

fit <- eBayes(fit, proportion= <proportion of d.e. genes>)

and see if you get an improvement, and look at ?eBayes for more information.
I never used limmaGUI though, so I don't know how to do it with this 
interface.

I hope this helps.
Best,
paolo


-- 
Paolo Innocenti
Department of Animal Ecology, EBC
Uppsala University
Norbyvägen 18D
75236 Uppsala, Sweden