HiCRep.py: fast comparison of Hi-C contact matrices in Python

Motivation: Hi-C is the most widely used assay for investigating genome-wide 3D organization of chromatin. When working with Hi-C data, it is often useful to calculate the similarity between contact matrices in order to assess experimental reproducibility or to quantify relationships among Hi-C data from related samples. The HiCRep algorithm has been widely adopted for this task, but the existing R implementation suffers from run time limitations on high-resolution Hi-C data or on large single-cell Hi-C datasets. Results: We introduce a Python implementation of HiCRep and demonstrate that it is much faster and consumes much less memory than the existing R implementation. Furthermore, we give examples of HiCRep's ability to accurately distinguish replicates from non-replicates and to reveal cell type structure among collections of Hi-C data.

Automated summary

The article introduces a Python implementation of the HiCRep algorithm, showing that it is faster and consumes less memory than the existing R implementation. It also demonstrates the algorithm's ability to accurately distinguish replicates from non-replicates and reveal cell type structure in collections of Hi-C data.