I was wondering... how do you specify edgeR that you want to obtain only the DE genes in Treatment B compared to Treatment A and Controls. I thought about using the mean of Control and Treatment A like:
But I guess that I would loose tones of genes due to possible high deviation between Control and Treatment A. Any idea how to overcome this issue?
Thanks!
First you need to decide what you mean by "Treatment B compared to Treatment A and Controls". If you want to find genes that are DE in B vs A and in B vs Controls, then you should do two separate contrasts and intersect the results (presumably also filtering on consistent sign of the log-fold change).
Your proposed approach is to find genes that are DE between B and the average of the A and Control groups. This is also an acceptable strategy. It's a more relaxed approach than taking the intersection, and so will yield more DE genes; but at the cost of interpretability, as you don't know whether the genes from this contrast are DE (or even in the same direction) against both of A and control.
Note that deviation between Control and A is not directly relevant to power. The dispersion is still being estimated using your full design matrix, edgeR is not treating Control and A as replicates of one another. So you won't necessarily "lose tons of genes" from using this approach.
Just following up Aaron's answer, the contrast you have given is a very powerful way of finding genes DE in Treatment B compared to the average of A and Controls. You will definitely not lose genes that you would have wanted to detect because of deviations between Control and Treatment.