Bayesian ChIP-seq Peak Calling — Probabilistic Enrichment Detection in Epigenomic Data

Bayesian ChIP-seq peak calling is a method that uses probabilistic models—typically Poisson, negative binomial, or hidden Markov models with Bayesian inference—to identify genomic regions with enriched binding of a protein of interest in chromatin immunoprecipitation followed by sequencing (ChIP-seq) experiments. By explicitly modelling read-count noise and incorporating prior distributions, Bayesian callers provide posterior probabilities of enrichment rather than simple p-values, offering a principled framework for quantifying uncertainty across the genome.