Hi,
We have performed a ChIP-seq experiment in S. cerevisiae with two conditions (control and mutant) using S.pombe as a spike-in (because the antibody works in both organisms). The reason because we add spike-in is that the antibody is not very efficient so we wanted to normalise the immunoprecipitation efficiency between samples in some way. But we would like to add another normalization step as TMM because the library size is very different between conditions (mutant condition accumulate most of the reads in repetitive regions that we are no able to map) and we expect a small portion of regions to be differentially enriched.
Does anyone knows how should we proceed?
Thanks in advance
First of all, thank you so much for your reply. It was really useful!
The change of where the reads are mapped is massive but also very located in certain regions (rDNA, tRNA, snRNA,...). I was not aware that edgeR always normalize for library size, then my problem is solved I think.
Taking into account all this new information, I think TMM is the method that suits better my experiment.
Thanks again!