As far as I understand, The process by which DESeq2 models a batch effect is close to : Subtracting the arithmetic mean of the batches' expression values from the genes, on a per-gene basis.
Is it possible in DESeq2 instead of modelling only an additive batch effect, to model a multiplicative one as well? For example, divide the expression levels per gene by the batch-specific geometric mean?
This is the context for my question: I have tried to visualize batch effect removal via ComBat. After that, the different conditions were plotted on a PCA, separating very nicely. Later, I tried performing differential expression (I do not pass the ComBat values into DESeq2, but rather model the batch effect using the formula "~ batch + condition" as the design ). Despite the separation in the PCA, there was a very low number of genes passing FDR (about 30). I suspect that the reason is that ComBat estimates both additive and multiplicative batch effects, while DESeq2 models only additive ones. Judging by the low number of DE genes, I suspect that multiplicative batch effects exist in my data.
P.S. However, each of the compared conditions has only two samples; that might be an alternative explanation for the low number of DE genes.