I would like advise about how to make a design for my experiment using DEseq2. In principle my question is straightforward, I'd simply like to find differentially expressed genes between two conditions. However, I've noticed that I have a large batch effect (I have two batches) and also large differences due to gender. Thus, I think I should include the two factors in my design:
> dds <- DESeqDataSetFromTximport(txi, sampleTable, ~BATCH + GENDER + Condition) ... > resultsNames(dds)  "Intercept" "Batch_2_vs_1"  "GENDER_MALE_vs_FEMALE" "Condition_T_vs_N"
Q1: if my question is which are the DE genes between conditions taking into account the batch and gender effects, which is the better option:
dds <-DESeq(dds) res <- results(dds) summary(res, name="Condition_T_vs_N")
dds_LRT <- DESeq(dds, test="LRT", reduced=~BATCH + GENDER) res_LRT <- results(dds_LRT) summary(res_LRT)
Q2: if I add an interaction term to the design, to which question am I answering?
dds <- DESeqDataSetFromTximport(txi, sampleTable, ~BATCH + GENDER + Condition:GENDER)
Many thanks for your comments, Cinta