I have a fluidigm (or other array) experiment which consists of 4 groups: A, B, C, and D.
The experimentalist I am helping wants to compare B to A and D to C,
but not B to D or B to C, etc.
1. Run all 4 groups together in Limma and then analyze the individual contrasts
2. do I compare B to A and D to C in 2 separate Limma runs?
I believe that 1 is correct, because in an ANOVA one should take into account
the variability of all of the samples, Furthermore, as I understand Limma, more
samples improves the empirical Bayesian estimate of the variance. However, this
approach has recently been questioned by 3 different experimental collaborators,
from 3 different labs, in 3 different contexts, so, I think that it would be prudent to ask the list.
Thanks and best wishes,