ArticleNature methods2025
Comparing chromatin contact maps at scale: methods and insights.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Identification of differential topologically associating domains from low sequencing depth and pseudobulk chromatin contact maps.Genome research · 2026Article
- Machine learning reveals sequence and genomic context features underlyingbioRxiv : the preprint server for biology · 2026Article
- De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genes.Genome research · 2026Article
- hicream: A flexible framework to identify significantly different regions in Hi-C data.Bioinformatics (Oxford, England) · 2026Article
- Epigenetic remodeling during UV exposure: high resolution analysis of histone post-translational modifications in a DNA binding protein 2 mutant model.Histochemistry and cell biology · 2026Article
- Transcription clusters and developmental pathways - nature, nurture, noise.Journal of cell science · 2026Review
- A low-input Micro-C protocol for high-resolution 3D genome mapping.Biology methods & protocols · 2026Article
- DNA shape and epigenomics distinguish the mechanistic origin of human genomic structural variations.Nucleic acids research · 2025Article
- Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence.bioRxiv : the preprint server for biology · 2025Article
- ChromInSight: Revealing DNA Double-Strand Breaks Through Chromatin Structural Insights With an Interpretable Graph Neural Network Framework.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- A comprehensive review and benchmark of differential analysis tools for Hi-C data.Briefings in bioinformatics · 2025Review
- Sequence-Based Machine Learning Reveals 3D Genome Differences between Bonobos and Chimpanzees.Genome biology and evolution · 2024Article
- Machine Learning Reveals the Diversity of Human 3D Chromatin Contact Patterns.Molecular biology and evolution · 2024Article
- Exploring the roles of RNAs in chromatin architecture using deep learning.Nature communications · 2024Article
- SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models.Bioinformatics (Oxford, England) · 2024Article
- Machine learning reveals the diversity of human 3D chromatin contact patterns.bioRxiv : the preprint server for biology · 2023Article
- ChromaFactor: deconvolution of single-molecule chromatin organization with non-negative matrix factorization.bioRxiv : the preprint server for biology · 2023Article
- SuPreMo: a computational tool for streamliningbioRxiv : the preprint server for biology · 2023Article
- Sequence-based machine learning reveals 3D genome differences between bonobos and chimpanzees.bioRxiv : the preprint server for biology · 2023Article
- Exploring the Roles of RNAs in Chromatin Architecture Using Deep Learning.bioRxiv : the preprint server for biology · 2023Article
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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.
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