With the current genome coverage of most ChIP-Seq experiments, tag distribution along the genome could be modeled by a Poisson distribution [7]. The advantage of this model is that one parameter, λBG, can capture both the mean and the variance of the distribution. After MACS shifts every tag by d/2, it slides 2d windows across the genome to find candidate peaks with a significant tag enrichment (Poisson distribution p-value based on λBG, default 10-5). Overlapping enriched peaks are merged, and each tag position is extended d bases from its center. The location with the highest fragment pileup, hereafter referred to as the summit, is predicted as the precise binding location.
