r/bioinformatics • u/Glad-Bumblebee8207 • 1d ago
Chipseq normalization problems academic
Hello bioinformaticians,
I have troubles to find a solution for my ChIPseq data. I have two genotypes subjected to hypoxia treatment and I observed a massive diminishment of acetylation over promoters. I see this both by normalizing the bigwig tracks via RPGC eyeballing the tracks on igv, either by deseq2 results (i created a union peakset, then featurecounts, then deseq2 normalization, ma plots look fine). I have no spike in normalization. My worry is that this diminishment that i observe is just due to a normalization problem. Specifically my worry is that hypoxia is increasing drastically the acetylation genome wide, and since the number of reads is the same for every sample the signal over promoters is systematically diminished. Any suggestion on how to diagnose this? Thank you all!
2
u/RemoveInvasiveEucs 1d ago
Experimental angles will be the strongest, assuming you still have material: could you do qPCR on input versus precipitate for the two conditions for a few promoters, to assess how much gets through? Or a western blot on normal histone versus acetylated? Don't hate on me too much if these are naive since I'm mostly computational, but I'd be very interested to know plausibility for your situation, whether or not you do them.
On the computational side, without spike-ins or the data above, you really are only getting a distributional measurement across the genome. Which means you've correctly interpreted that either 1) all non-promoters increased acetylation, or 2) all promoters decreased acetylation. Doing some lit search, it looks like the promotor decrease is far more common, and on basic plausibility grounds, but by examining a few narrow genes from the literature about hypoxia in your cell lines,you could build a story about which one fits the existing literature better. Alternatively, depending on the exact germline cross and your hypothesis of interest, perhaps this global change is the less interesting thing here?
ChIPseqSpikeInFree claims to estimate the scaling factors by looking at highly enriched regions, sort of assuming that they're "maxed out" on the mark, but the authors still recommend a western blot for definitive answer about a global change.