I'm analyzing a dataset with DESeq, which consists of two time-points and two genotypes. I am not very knowledgeable in statistics, sadly, and I am a bit lost as to whether I should use DESeq under the "standard" comparison mode, or make use of the more "advanced" GLM regressions facet.
The comparisons are between :
GenotypeA/Timepoint1 VS GenotypeA/Timepoint2 GenotypeB/Timepoint1 VS GenotypeB/Timepoint1 GenotypeA/Timepoint1 VS GenotypeB/Timepoint1 GenotypeA/Timepoint2 VS GenotypeB/Timepoint2
My understanding is that although my experimental design involves two factors (genotype and timepoint), since my comparisons are only changing one factor at a time, I have nothing to do performing Linear Regressions / Model Fitting, but I am not sure of this. Perhaps it would make sense to use the multi-factorial design analysis ONLY if I were to compare
GenotypeA/Timpepoint1 VS GenotypeB/Timepoint 2? (This changing two factors at a time in a single comparison)
Also, what if I want to create a PCA plot of the libraries? Is that a sensible reason to use a GLM fit?
Thanks, and sorry for the extreme confusion.