I have 2 questions. The first one is regarding the sizeFactors.
I have the following sample groups:
1. control = no treatment: 5 biol. replicates
2. after 1h of treatment: 5 biol. replicates
3. after 2 h of the same treatment: 5 biol. replicates.
(summa summarum: 1 factor, 3 levels, 15 animals)
My task was to find DE genes between the groups. So I did pairwise comparisons: i.1 vs.2, ii.1vs.3 and iii.2 vs.3.
The sizeFactors were computed for the each comparison: it means that the normalized counts for samples from group1 can be different in e.g. comparisons i and ii.
My question is: is this wrong? Should I instead compute the sizeFactors for the all samples before testing, and not just for the compared ones?
The second question is regarding the analysis without an intercept, which I did here. Before 3-4 weeks, I did not get any error message when my design was without an intercept. But today, when I repeated the analysis, I got an error message:
betaPrior=TRUE can only be used if the design has an intercept.
if specifying + 0 in the design formula, use betaPrior=FALSE
So, I added in DESeq function an argument betaPrior=FALSE, and got the extended/different set of genes (e.g. under 5% FDR).
My 2nd question is just for sanity check: is there something changed in the code during this period of time, since my input hasn't changed, and I used the same code? If so, why betaPrior has to be =FALSE when the design is without an intercept?
Thank you in advance!