Im running DESeq2 on RNAseq data and my experimental design has 2 factors, A and B. A is categorical and has 4 different levels, B is categorical and has 2 different levels

I ran DE with the following design: ~ A + B + A:B I am interested solely in the effect of B, I want to extract genes with a significant effect of B but NO EFFECT of the interaction A:B. I wonder if this is what would report a LRT with the reduced design ~ A + A:B or would it be better to check the output of the lfcShrink for the specific contrast of B I want to look at (i.e. do the significant genes in this output are significant only for the effect B but not for the other variables?)

Some statisticians who work on linear models wouldn't think it's appropriate to include A:B in the reduced design because it is an interaction with a factor you've removed.

If you want to find genes with no interaction, I would first define that set by testing ~A + B + A:B vs ~A + B.

Then if you want to examine the effect of B, I would use lfcShrink on the B coefficient in ~A + B. You can examine that coefficient for the genes in the first set.

Thank you for these advises ! It makes things clearer on how I should design my analysis,