I used bamCompare (from deepTools) to compute the log2 ratio and see differences in the read coverage between pairs of samples. I have found that some regions the log2 ratio is very high (or low), now I would like to compute a p-values for the log2 ratios to get those that are actually statistically significant higher (or lower), but I am not sure how to proceed. I first thought about assuming a normal distribution of my log2ratio values but after performing some normality tests I've seen that it does not fit a normal distribution (very high peak and very long tails). Does someone know how can I proceed with the computation of the p-value to get the significant log2ratios?
Many thanks!
In essence it's the ratio of two Poisson distributions, but I haven't a clue what that is (and I imagine computing it would be annoying given the presence of zeros). Realistically, you're probably interested in just doing some peak calling.
Edit: Actually, it's probably be more like the ratio of mixed Poisson distributions (I imagine this is an over simplification in practice), since an IP will have background and signal.
Thanks for the reply, I guess I'll try another approach than bamCompare.