Hi,

I have data with 4 levels group: condition1, treat1, condition2, treat2.

I am trying to use DESeq2 to identify differentially expressed genes between two levels: treat1 vs condition1.

I tried two methods. First, I only use subset of all data, condition1 and treat1 to get the differentially expressed genes between treat1 vs condition1. Second, I use all the data including condition1, treat1, condition2 and treat2; but I extract the differentially expressed genes between treat1 vs condition1 by `results(dds, contrast("group","treat1","condition1"))`.

Interestingly, the identified differentially expressed genes are completely different. When I checked size factors for each sample in these two different methods, they are also completely different. Is this an expected behavior for DESeq2 pipeline? If so, which method should I use?

Thank you.
<p>This is not surprising, because the model estimates (size factors, dispersion, priors, etc) use all samples. I suggest exploring a PCA plot to see the relationships between samples (see vignette).</p>
