I have a full factorial experimental design with 2 factors that have 2 levels each, a total of 4 combinations.
I am interested in the interaction between those two factor and that is the reason why I used the following command:
dds <- DESeqDataSetFromMatrix(countData= reads,colData = Design, design = ~ Factor1 + Factor2 + Factor1: Factor2).
Afterward I got a list of contigs that are significantly interacting between the two factors.
My questions are:
1) is there a way to test within the same model the independent effect of each factor or shall I rerun another model without the interaction?
2) with this complete model I can get lists of differentially expressed contigs from the comparison between two level of one factor within each level of the other factor separately and reciprocally (total of 4 comparisons). This looks like a post hoc multiple comparison test (which is allowed only if the interaction is significant). So shall I substract from those lists of contigs the ones that are absent from the list of interacting contigs or not?
Than you for your help.