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
