BioinformaticsBioinformaticsPeer-reviewed journal article
HiCRep.py: Fast comparison of Hi-C contact matrices in Python
Abstract
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 asses 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. We introduce a Python implementation of HiCRep and demonstrate that it is much faster than the existing R implementation. Furthermore, we give examples of HiCReps ability to accurately distinguish replicates from non-replicates and to reveal cell type structure among collections of Hi-C data. HiCRep.py and its documentation are available with a GPL license at https://github.com/Noble-Lab/hicrep. The software may be installed automatically using the pip package installer.
- Citations
- 41
- FWCI
- 2.35
- Field percentile
- top 9%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- HiC-Spector: A matrix library for spectral and reproducibility analysis of Hi-C contact maps
Koon‐Kiu Yan, Galip Gürkan Yardımcı, … Mark Gerstein·BioinformaticsPeer-reviewed·Mar 21, 2017
- HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient
Tao Yang, Feipeng Zhang, … Qunhua Li·Genome ResearchPeer-reviewed·Nov 1, 2017
- HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking
Charalampos Lazaris, Stephen Kelly, … Aristotelis Tsirigos·BMC GenomicsPeer-reviewed·Jan 5, 2017
- HiChIA-Rep quantifies the similarity between enrichment-based chromatin interactions datasets
Sion Kim, Joseph T Jackson, … Minji Kim·bioRxiv·Feb 3, 2026
- Measuring the reproducibility and quality of Hi-C data
Galip Gürkan Yardımcı, Hakan Özadam, … William Stafford Noble·Genome biologyPeer-reviewed·Mar 19, 2019
- hictk: blazing fast toolkit to work with .hic and .cool files
Roberto Rossini, Jonas Paulsen·BioinformaticsPeer-reviewed·Jun 21, 2024