[BioC] Limma B-statistics

[Brian Lane]

Hi,
I need some help with the interpretation of B statistics generated by 
eBayes in the limma package.

I want to compare gene expression in three groups of Affy samples. The 
probe level data was generated from .cel files (ReadAffy()), an exprSet 
object was generated using mas5 (scaled to 100) and a linear model fitted 
to the data using a design based on the three groups (6, 5, and 5 samples 
in each group, respectively). I have then made 3 contrasts to cover all 
possible comparisons within the data set, and generated empirical Bayes 
statistics using eBayes. I've then used classifyTestsF to classify each 
gene according to the contrasts.

The results of all this are 23 significantly differentially expressed 
genes. The moderated t-values for all these 23 genes have p<0.01. However, 
all the B-values are <0 (average -3!). In fact, a volcano plot of log-odds 
and fold-change in the three contrasts show that all the B-values are 
negative.

My understanding is that B<0 implies the gene is more likely to not be 
differentially expressed than to be differentially expressed. If this is 
the case, should I take the "significant genes" seriously? If not, is there 
any reason why the B-values should all be negative or does this simply 
reflect the fact that there is little evidence of differential expression 
in the data set as a whole?

Regards,
Brian Lane
Dept of Haematology
Liverpool University