Comparing chromatin contact maps at scale: methods and insights

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, methods often disagree, and no gold standard exists for comparing pairs of maps. Here, we evaluate 25 ways to compare contact maps using Micro-C and Hi-C data from two cell types and in silico-generated contact maps. We identify similarities and differences between the methods and quantify their robustness to common sources of biological and technical variation, including losses and gains of CTCF-binding sites, changes in contact intensity or patterns, and noise. We find that global comparison methods, such as mean squared error, are suitable for initial screening; however, biologically informed methods are necessary for identifying how maps diverge and for proposing specific functional hypotheses. We provide a reference guide, codebase, and thorough evaluation for rapidly comparing chromatin contact maps at scale to enable biological insights into 3D genome organization.

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Publication Details

Journal
Nature Methods
Published
2025-03-19
DOI
https://doi.org/10.1038/s41592-025-02630-5
Citations
2
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
1.61

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article

Comparing chromatin contact maps at scale: methods and insights

Evonne McArthur, Katherine S. Pollard, Laura M. Gunsalus, Shuzhen Kuang et al.
2 citations
Nature Methods
Genomics and Chromatin Dynamics
1.61
article

Comparing chromatin contact maps at scale: methods and insights

Evonne McArthur, Katherine S. Pollard, Laura M. Gunsalus, Shuzhen Kuang, John A. Capra, Ketrin Gjoni, Maureen Pittman
article en
2 citations

Abstract

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, methods often disagree, and no gold standard exists for comparing pairs of maps. Here, we evaluate 25 ways to compare contact maps using Micro-C and Hi-C data from two cell types and in silico-generated contact maps. We identify similarities and differences between the methods and quantify their robustness to common sources of biological and technical variation, including losses and gains of CTCF-binding sites, changes in contact intensity or patterns, and noise. We find that global comparison methods, such as mean squared error, are suitable for initial screening; however, biologically informed methods are necessary for identifying how maps diverge and for proposing specific functional hypotheses. We provide a reference guide, codebase, and thorough evaluation for rapidly comparing chromatin contact maps at scale to enable biological insights into 3D genome organization.

Nature MethodsVol. 22(4)
Gladstone Institutes (US), University of California, San Francisco (US), University of Washington (US), Chan Zuckerberg Initiative (United States) (US), Vanderbilt University Medical Center (US)
Gladstone Institutes, Additional Ventures, National Institutes of Health, University of California, San Francisco, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, NIH Office of the Director, National Institute of General Medical Sciences
Openalex Percentile: Top 18%
Genomics and Chromatin Dynamics
1.61
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