Evidence map›Paper›PMID 38709825›Full record

ArticlePLoS computational biology2024

Cooltools: Enabling high-resolution Hi-C analysis in Python.

Open2C, Nezar Abdennur, Sameer Abraham, Geoffrey Fudenberg, Ilya M Flyamer, Aleksandra A Galitsyna, Anton Goloborodko, Maxim Imakaev, Betul A Oksuz, Sergey V Venev and 1 more

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 221 papers.

0numbers the graph read from it
0cells of the map it votes in
221citing 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

221 citing papers in PubMed.

  1. Review
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  10. Influence of Histone Acetylation on Chromatin 3D Organization inInternational journal of molecular sciences · 2026
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161 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Open2C
Nezar AbdennurDepartment of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America.
Sameer AbrahamInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.
Geoffrey FudenbergDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, United States of America.ORCID https://orcid.org/0000-0001-5905-6517
Ilya M FlyamerFriedrich Miescher Institute for Biomedical Research, Basel, Switzerland.ORCID https://orcid.org/0000-0002-4892-4208
Aleksandra A GalitsynaInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.
Anton GoloborodkoInstitute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria.
Maxim ImakaevInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America.
Betul A OksuzDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America.
Sergey V VenevDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America.
Yao XiaoDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, California, 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

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers' time; however, analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.

Indexed as

Computational BiologySoftwareChromosome MappingGenomeGenomicsHumansProgramming Languages

Identifiers

PMID38709825
PMCPMC11098495

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.