Computes a similarity metric between two ChIP-seq datasets to quantify chromatin interactions. In contrast to a basic count of overlaps between two Transcription Factor Binding Sites, IntervalStats allows to compute an exact P-value on their similarity metric. This metric is asymmetric and they demonstrate that it can highlight particular behaviour such as "co-factor" function of a protein. For every query interval, this method produces the closest reference interval, the distance between them and P-value. Their method is insensitive to non-biological variation in datasets (peak width for example). Furthermore, IntervalStats similarity computation can be restricted to a set of genomic regions (such as mappable genome, promoters, open chromatin regions). So it can model peak location biases.