Dear Michael, 

first of all I apologize if my questions sound silly, because I am bench researchers, but I am trying to learn R. I have help from programmer in the lab but I want to understand the analysis. I have to analyze experiment where I have 4 genotypes: wt, mutA, mutB, and double mutant mutAmutB, thus I would like to identify genes that are differentially expressed between the single mutants and interaction between the two genes. First I thought that with DESeq2 I can only normalize the counts and extract the normalized counts and do 2-anova afterwards, but as trying to reading the complete list of your publications I realize that I have to to all with DESeq2, and thus I wanted to confirm the most appropriate design. The programmer used HTSeq before so, I was thinking of: 

dds <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory, design = ~ mutA + mutB + mutA:mutB)

please let me know if this is the right formula or which example should I follow from your tutorials.

Many thanks!

Dani

hi,

Sorry I missed this post because it didn't have a "deseq2" tag (it had "anova deseq2", but the support site only uses exact tags to notify maintainers).

If it's not too late, the recommended design would be the above and then use a LRT with a reduced design of ~mutA + mutB.

dds <- DESeq(dds, test="LRT", reduced=~mutA + mutB)