differential analysis of chip-seq data
For sharing, you can test the proportion of overlapping peaks using bedtools intersect or the find.overlap function in GenomicRanges packages in R.
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.