Evidence map›Paper›PMID 42298067›Full record

ArticleNature methods2026

A generalizable Hi-C foundation model for chromatin architecture, single-cell and multiomics analysis across species.

Xiao Wang, Yuanyuan Zhang, Suhita Ray, Anupama Jha, Tangqi Fang, Shengqi Hang, Sergei Doulatov, William S Noble, Sheng Wang

Abstract read
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In one paragraph

Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Xiao Wang *Department of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-4435-7098
Yuanyuan Zhang *Department of Computer Science, Purdue University, West Lafayette, IN, USA.ORCID http://orcid.org/0000-0002-0565-6813
Suhita RayDepartment of Physiology and Cellular Biophysics, Columbia University Irving Medical Center, New York, NY, USA.
Anupama JhaDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-3029-2086
Tangqi FangPaul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0009-0007-8471-3890
Shengqi HangPaul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-3279-2183
Sergei DoulatovDepartment of Physiology and Cellular Biophysics, Columbia University Irving Medical Center, New York, NY, USA. sd3923@cumc.columbia.edu.ORCID http://orcid.org/0000-0002-1328-364X
William S NobleDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. william-noble@uw.edu.ORCID http://orcid.org/0000-0001-7283-4715
Sheng WangPaul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA. swang@cs.washington.edu.ORCID http://orcid.org/0000-0002-0439-5199

Funding

Functional and molecular consequences of SF3B1 mutations in human hematopoietic stem cellsR01HL151651 · NHLBI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Robert K Bradley, Sergei Doulatov · 2020 to 2026
$4.0M
Deep integrative analysis of Hi-C dataR01HG013321 · NHGRI · UNIVERSITY OF WASHINGTON · PI Sheng Wang · 2024 to 2026
$1.5M
Super-resolution chemical imaging via a diffusion-based deep generative modelR21EB036205 · NIBIB · UNIVERSITY OF WASHINGTON · PI FU, DAN, WANG, SHENG · 2024 to 2025
$357k
NHGRI NIH HHS R01 HG013321NHLBI NIH HHS R01 HL151651NIBIB NIH HHS R21 EB036205U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) UM1 HG011531
6 · The paper itself

Abstract

Nuclear DNA is organized into a three-dimensional (3D) structure that impacts critical cellular processes. However, the integrative analysis of 3D structure (measured by high-throughput chromosome conformation capture (Hi-C)) and associated epigenomic regulation (for example, assay for transposase-accessible chromatin using sequencing (ATAC-seq) and chromatin immunoprecipitation followed by sequencing (ChIP-seq)) remains challenging due to the differences in data format, resolution and analytical pipelines. Here we propose HiCFoundation, a foundation model trained on massive Hi-C data for integrative analysis linking chromatin structure to downstream regulatory function. The model achieves state-of-the-art performance and generalizability across species on various 3D genome analysis, including reproducibility analysis, resolution enhancement and loop detection. Additionally, HiCFoundation can predict various epigenomic activities from Hi-C to reveal how 3D structure links to regulatory function. Finally, HiCFoundation can easily adapt to single-cell Hi-C data. HiCFoundation thus offers a general, interpretable framework for studying the 3D genome and its functional roles across cell types and species.

Indexed as

ChromatinSingle-Cell AnalysisAnimalsChromatin ImmunoprecipitationChromatin Immunoprecipitation SequencingEpigenomicsHigh-Throughput Nucleotide SequencingHumansMultiomicsChromatin

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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.