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I am using DESeq2 to normalize data for some microbiome and eDNA metabarcoding projects. My datasets are observational/ecological and there are many factors that I am interested in assessing with downstream analyses. For example, with my microbiome dataset, I am interested in understanding differences between sexes, age groups, reproductive status, and season of certain wildlife species.
When running DESeq2, should I incorporate all factors of interest in the design (e.g., ~ sex + age + reproductive status + season)? Or is there a way to run the design on a different factor (like sequencing run) so that I can then use the data that has been normalized across runs to do my downstream analyses on the other factors?
