Evidence map›Paper›PMID 42525289›Full record

ArticleBioinformatics (Oxford, England)2026

map3C: a computational tool for processing multiomic single-cell Hi-C data.

Joseph Galasso, Ye Wang, Frank Alber, Jason Ernst, Chongyuan Luo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Joseph GalassoBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, United States.ORCID 0000-0002-9013-359X
Ye WangBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, United States.ORCID 0000-0001-6823-9040
Frank AlberInstitute of Quantitative and Computational Biosciences (QCBio), University of California, Los Angeles, Los Angeles, CA 90095, United States.
Jason ErnstBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, United States.ORCID 0000-0003-4026-7853
Chongyuan LuoBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, United States.ORCID 0000-0002-8541-0695

Funding

Multiscale Analyses of 4D Nucleome Structure and Function by Comprehensive Multimodal Data IntegrationUM1HG011593 · NHGRI · CARNEGIE-MELLON UNIVERSITY · PI ALBER, FRANK, BELMONT, ANDREW STEVEN · 2020 to 2024
$10.4M
Training Grant in Genomic Analysis and InterpretationT32HG002536 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Valerie A Arboleda, Harold Pimentel · 2002 to 2026
$8.6M
Leveraging genetic variation to dissect gene regulatory networks of reprogramming to pluripotencyU01HG012079 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Chongyuan Luo, Kathrin Plath · 2021 to 2026
$6.9M
Spatiotemporal epigenomic and chromosomal architectural cell atlas of developing human brainsU01MH130995 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Chongyuan Luo, Mercedes Paredes · 2022 to 2026
$4.4M
SINGLE-CELL MULTI-OMIC APPROACHES TO MECHANISTICALLY CHARACTERIZE PSYCHIATRIC DISORDER RISK LOCI IN THE HUMAN BRAINR01MH125252 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LUO, CHONGYUAN · 2021 to 2025
$3.7M
NHGRI NIH HHS T32 HG002536NHGRI NIH HHS U01 HG012079NHGRI NIH HHS UM1 HG011593NIH HHS R01MH125252NIH HHS T32HG002536NIH HHS U01HG012079NIH HHS U01MH130995NIH HHS UM1HG011593NIMH NIH HHS R01 MH125252NIMH NIH HHS U01 MH130995the Congressionally Directed Medical Research Programs W81XWH-22-1-0569
6 · The paper itself

Abstract

summaryThe emergence of multiomic single-cell Hi-C (scHi-C) methods, which simultaneously profile chromatin conformation and other modalities such as gene expression or DNA methylation, creates tremendous opportunities for studying the genome's structure-function relationships. Existing tools for processing multiomic scHi-C datasets lack certain key functions for downstream bioinformatics analysis. We present map3C, a software tool that incorporates additional key functions. Specifically, we demonstrate that map3C facilitates multiomic scHi-C processing, quality control, and identification of structural variant locations in the genome. AVAILABILITY AND IMPLEMENTATION: map3C is available at https://github.com/luogenomics/map3C and is archived at https://doi.org/10.5281/zenodo.20724719.

Indexed as

Computational BiologyGenomicsSingle-Cell AnalysisSoftwareChromatinHumansMultiomicsChromatin

Identifiers

PMID42525289
PMCPMC13446223

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.