[R] 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 
expression set has been imported from GeneSpring using GSload.expBC 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 are <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