Hi,
I have a experimental setup for a time-series as follows:
Treatment: time1 time2 time3 time4 time5
Control: time0 time4
So I have a timeseries, where after time 0 the cells are treatment and then there is RNA-seq at a set of time points after. Control at time 4 is there to look to see if there is any circadian changes w.r.t to the time course (this is not the main aim of the experiment). And I am trying to look for genes which change as a change over time in response to treatment. So if I ignore the control sample time4 this resolves down to the simple ANOVA/LRT with the full model as ~ time and the reduced model as ~1.
A simple pair-wise differential expression between control at time0 and control at time 4 reveals only a few differentially expressed genes (and they're all circadian cycle related). And these samples clusters strongly with the samples at control:time0.
Is it ok for me to merge these samples with the samples at time 0? Is there any problems that will arise from this or any further checks that I need to perform before I can definitely collapse this group down?
However, I feel like this may not be optimal as I'm throwing away information from control at time4 - which is some ways probably means I'm overestimating the variance for some of the genes by combining them using the method suggested above. Is there a better model which can take this into account that I am not considering?
Many thanks for your help,