I have a chip-seq data set with three conditions (wt , KO1, KO2) and three time points (0h, 2h, 4h). For each condition and TP I have duplicated samples for IP and Input samples, which looks like that:
I would like not only to do a pairwise comparison of IP vs. Input, but also to be able to do a more complex comparisons. I would like for example to wee if there are any differential binding events based on the differences over time (something like a time-series analysis) within each condition (e.g. comparing
wt.0h - wt.2h - wt.4h).
But to make it even more complicated, I would also like to make a comparison of the different time-series against each other. What I mean by that is for example to compare differential binding events from the wt time-series to KO1 or to KO2. In this case I would like to see if there are peaks (= overlapping genes) in the
wt time-series which are significantly different than the peaks (or regions). in the KO sample time-series.
I know this is not so easy, as peaks in one conditions/time-point don't necessarily mean also peaks in a different samples. But these kind of behavior is exactly what i would like to catch. If there is a significant peak in the
wt sample, but no peak in the
KO I would like to see it. This would a normal peak calling, but when I have multiple crossing samples, I'm not sure how to do the analysis.
I would appreciate any advice.