Evidence map›Paper›PMID 38809952›Full record

ArticlePLoS computational biology2024

Pairtools: From sequencing data to chromosome contacts.

Open2C, Nezar Abdennur, Geoffrey Fudenberg, Ilya M Flyamer, Aleksandra A Galitsyna, Anton Goloborodko, Maxim Imakaev, Sergey V Venev

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 215 papers.

0numbers the graph read from it
0cells of the map it votes in
215citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

215 citing papers in PubMed.

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  13. Developmental expression of the skeletal muscle determination gene,bioRxiv : the preprint server for biology · 2026
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  14. Evolution of compound eye cell types shapes visual behaviors acrossbioRxiv : the preprint server for biology · 2026
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  18. CAD-C: An engineered nuclease enables repair-freebioRxiv : the preprint server for biology · 2026
    Article
  19. Article
  20. Article

155 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Open2C
Nezar AbdennurProgram in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America.
Geoffrey FudenbergDepartment of Computational and Quantitative Biology, University of Southern California, Los Angeles, California, United States of America.
Ilya M FlyamerFriedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
Aleksandra A GalitsynaInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-8969-5694
Anton GoloborodkoInstitute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria.ORCID https://orcid.org/0000-0002-2210-8616
Maxim ImakaevInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.
Sergey V VenevDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America.

Funding

Structural Annotation of the Human GenomeR01HG003143 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI Job Dekker · 2003 to 2026
$15.4M
Center for 3D Structure and Physics of the GenomeUM1HG011536 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI DEKKER, JOB, MIRNY, LEONID A · 2020 to 2024
$11.8M
Genomes in 3D: from maps to mechanismsR35GM143116 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FUDENBERG, GEOFFREY · 2021 to 2025
$2.1M
NHGRI NIH HHS R01 HG003143NHGRI NIH HHS UM1 HG011536NIGMS NIH HHS R35 GM143116
6 · The paper itself

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. 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.

Indexed as

ChromosomesComputational BiologySoftwareChromosome MappingHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNA

Identifiers

PMID38809952
PMCPMC11164360

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.