Pairtools: From sequencing data to chromosome contacts.

Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE

Original Publication: San Francisco, CA : Public Library of Science, [2005]-

Software* ; Chromosomes*/genetics ; Chromosomes*/chemistry ; Computational Biology*/methods; Humans ; Sequence Analysis, DNA/methods ; High-Throughput Nucleotide Sequencing/methods ; Chromosome Mapping/methods

The field of 3D genome organization produces large amounts of sequencing data from Hi-C and a rapidly-expanding set of other chromosome conformation protocols (3C+). Massive and heterogeneous 3C+ data require high-performance and flexible processing of sequenced reads into contact pairs. To meet these challenges, we present pairtools-a flexible suite of tools for contact extraction from sequencing data. Pairtools provides modular command-line interface (CLI) tools that can be flexibly chained into data processing pipelines. The core operations provided by pairtools are parsing of.sam alignments into Hi-C pairs, sorting and removal of PCR duplicates. In addition, pairtools provides auxiliary tools for building feature-rich 3C+ pipelines, including contact pair manipulation, filtration, and quality control. Benchmarking pairtools against popular 3C+ data pipelines shows advantages of pairtools for high-performance and flexible 3C+ analysis. Finally, pairtools provides protocol-specific tools for restriction-based protocols, haplotype-resolved contacts, and single-cell Hi-C. The combination of CLI tools and tight integration with Python data analysis libraries makes pairtools a versatile foundation for a broad range of 3C+ pipelines.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2024 Open2C et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Update of: bioRxiv. 2023 Feb 15:2023.02.13.528389. doi: 10.1101/2023.02.13.528389. (PMID: 36824968)

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R01 HG003143 United States HG NHGRI NIH HHS; R35 GM143116 United States GM NIGMS NIH HHS; UM1 HG011536 United States HG NHGRI NIH HHS

Date Created: 20240529 Date Completed: 20240610 Latest Revision: 20240613

20240613

PMC11164360

10.1371/journal.pcbi.1012164

38809952