Does DeSeq2 make comparisons between all samples vs. all controls (A), or between matched samples and controls in different groups (B)?
E.g. Groups: 1, 2, 3 (treated) Controls: 1C, 2C, 3C (untreated)
(A) [1 + 2 + 3 treated] vs [1C + 2C + 3C]
(B) [1 vs. 1C] + [2 vs. 2C] + [3 vs. 3C]
The vignette states 'Typically, we recommend users to run samples from all groups together, and then use the contrast argument of the results function to extract comparisons of interest after fitting the model using DESeq.', so does this mean that method (A) above will be how this works, once the contrast is defined?
The reason I ask/want to understand how this is working is that I am working with a large bulk RNAseq dataset with hundreds of samples. I am wondering what the impact will be of removing individual low quality samples from the dataset on the running/output of DESeq2. Removal of individual sample will leave me with a mix of samples, some with associated/paired controls and some without; would it be better to remove all samples that do not have a matching treated sample or control in this case?