Consider a big population of ChIP-seq experiments (not necessarily replicates). For instance, all belonging to same tissue under similar condition (e.g., all are ALL) but belonging to different people. Lets suppose all these samples are sequenced similarly, and peaks are called all using one software with same parameter setup.
How would you interpret overlapping peaks?
Some sites may have few overlapping peaks, and some sites may have at least one peak from all the samples; how do you read this?
Any research article explaining such (at least vaguely similar experiment)?