# differential analysis of chip-seq data

I have several sets of chip-seq data. I called the peaks using Macs2. I am pretty new to the field and I will appreciate any help. I wanted to annotate the peaks and see which peaks are shared between them and which ones are different. What is the best way to do this? which package should I use?

Many thanks

1. For sharing, you can test the proportion of overlapping peaks using bedtools intersect or the find.overlap function in GenomicRanges packages in R.
2. What makes more sense is perhaps to merge all the peaks together using bedtools merge, and then count the number of reads/fragments in each peak for each sample using featureCounts. The output of this is a matrix, which is very similar to gene expression results. Then you can do some differential tests on this data.
In a similar question, I recommended that directly comparing called peaks can be somewhat misleading. This topic is addressed in the documentation of the DiffBind R package on Bioconductor, in the "Comparison of occupancy and affinity based analyses" section.
But if you're just looking for genome annotation software, the annotatr package on Bioconductor is pretty useful