I have probably a basic question but I can't seem to wrap my mind around what is right. I have bulk RNA sequencing data from a design as follows:
Control cells differentiating and sampled on day 0, 2, 4, and 6. Treatment group had a treatment from day 2 to 4 and sampled on day 4 and day 6 (all n = 3). (So 4 time points for control and 2 time points for treatment group).
I don't think that this is a time series (cell culture, so each 'n' is a different well) and as such, in the deseq2 design, i designed it as design = ~ trx (where trx annotates both control or treatment and day e.g.: ctl0, ctl2, ctl4, ctl6, trx4, trx6). Does this sound right? or should I be supplying deseq with something like design = ~ condition + time + condition:time?
In addition, given that this is a differentiation dataset, I want to analyze the data by visualizing things with progression and not just day 2 versus day 0, day 4 versus day 0, etc. Is there a way to have a sort of pathway analysis progression or some alternative to show how things are progressing? I know this is done for single-cell data sets but I haven't found anything for bulk-RNA. I have tried using the 'gage' package but I'm not sure that is the correct way. Perhaps I should be sticking to simple comparisons? If you know of any literature or have any advice, I would greatly appreciate it!