I've been doing a bit of reading regarding my experiment and I'm currently deciding what approach to take - I know that stats should be planned prior to experiments; however, I'm having a brain wobble.
I set out and completed a 2 time point RNA-seq analysis for 2 conditions. Control for each time point and a treatment.
I have two mind-frames:
1./ Two-way comparison - EdgeR classic Given I have two time points - a control for each; apply an EdgeR classic approach and do pairwise comparisons between conditions at individual time points. Why? We know organisms have different life stages and their regulation changes dynamically. The control samples of each time point are independent separate individuals from one another. They are not related. I feel that time-series analysis in this situation may be assuming too much stays constant?
2./ Apply an EdgeR GLM complex model for multi-factorate analysis.
My findings so far. If I conduct the classic approach, my BCV's are lower by doing inidivudal time points, than combining all conditions in a complex GLM. When I compare everything in the GLM, there are not many diff. expressed genes between comparisons on each day (Ctl Vs treat day 1) - (Ctl Vs treat day 6).
What I'm ultimately asking is, what the appropriate approach for this sort of set-up?