Pairtools: from sequencing data to chromosome contacts [preprint]

Abdennur, Nezar; Fudenberg, Geoffrey; Flyamer, Ilya M; Galitsyna, Aleksandra A; Goloborodko, Anton; Imakaev, Maxim; Venev, Sergey V

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2023.02.13.528389v1.full.pdf

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Authors

Abdennur, Nezar
Fudenberg, Geoffrey
Flyamer, Ilya M
Galitsyna, Aleksandra A
Goloborodko, Anton
Imakaev, Maxim
Venev, Sergey V

UMass Chan Affiliations

Program in Bioinformatics and Integrative Biology
Systems Biology

Document Type

Preprint

Publication Date

2023-02-15

Abstract

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. Pairtools provides both crucial core tools as well as 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 multi-way contacts, 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.

Source

Open2C; Abdennur N, Fudenberg G, Flyamer IM, Galitsyna AA, Goloborodko A, Imakaev M, Venev SV. Pairtools: from sequencing data to chromosome contacts. bioRxiv [Preprint]. 2023 Feb 15:2023.02.13.528389. doi: 10.1101/2023.02.13.528389. PMID: 36824968; PMCID: PMC9949071.

DOI

10.1101/2023.02.13.528389

Permanent Link to this Item

http://hdl.handle.net/20.500.14038/52870

PubMed ID

36824968

Notes

This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.

Related Resources

Now published in PLoS Computational Biology, https://doi.org/10.1371/journal.pcbi.1012164.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.; Attribution 4.0 International

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

Except where otherwise noted, this item's license is described as The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.