ArticleGenome research2014
Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts.
Article in Genome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 319 papers, 1 of them a synthesis that pooled it.
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Who cites it
319 citing papers in PubMed, 1 synthesis or guideline pooled it, 561 citations in OpenAlex.
- Biological insights from multi-omic analysis of 31 genomic risk loci for adult hearing difficulty.PLoS genetics · 2020Pooled it
- Trial
- Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.Methods in molecular biology (Clifton, N.J.) · 2027Article
- LAWS-HiC: A Locally Adaptive Weighting and Screening (LAWS) Approach to Improve Detection of Long-Range Chromatin Interactions from Hi-C Data.Methods and protocols · 2026Article
- Assessing reproducibility of Hi-C chromatin interactions using stratum-adjusted irreproducible discovery rate.Bioinformatics (Oxford, England) · 2026Article
- Decoding 3D chromatin architecture reveals distinct enhancer classes underlying hierarchical gene regulation in prostate cancer.Genome biology · 2026Article
- Hi-C informed kernel association test for integrating 3D genome structure into variant-set analysis.Briefings in bioinformatics · 2026Article
- A chromatin-structure-guided framework for predictive and interpretable regulatory genomics.Briefings in bioinformatics · 2026Article
- A generalizable Hi-C foundation model for chromatin architecture, single-cell and multiomics analysis across species.Nature methods · 2026Article
- Annotating Interchromosomal Interactions at Sub-Megabase Resolution Using Network Clustering Coefficients.bioRxiv : the preprint server for biology · 2026Article
- Article
- TM-Loop: Transformer multi-omics hierarchical detection of chromatin loop.Scientific reports · 2026Article
- CTCF directly binds G-quadruplex structures to regulate genome topology and gene expression.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.Nature communications · 2026Article
- BandHiC: a memory-efficient and user-friendly Python package for organizing and analyzing Hi-C matrices down to sub-kilobase resolution.BMC genomics · 2026Article
- GraphLooper: predicting chromatin loops based on hierarchical multi-view graph pooling method.Briefings in bioinformatics · 2026Article
- CTCF Regulates Erythroid Differentiation Through Control of Core Erythroid Transcription Factors.Biomolecules · 2026Article
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.bioRxiv : the preprint server for biology · 2026Article
- Allele-specific chromatin dynamics underpin heterosis and shoot development in hybrid poplar 'Nanlin895'.Plant molecular biology · 2026Article
- CLAMP: predicting specific protein-mediated chromatin loops in diverse species with a chromatin accessibility language model.Genome biology · 2026Article
259 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Our current understanding of how DNA is packed in the nucleus is most accurate at the fine scale of individual nucleosomes and at the large scale of chromosome territories. However, accurate modeling of DNA architecture at the intermediate scale of ∼50 kb-10 Mb is crucial for identifying functional interactions among regulatory elements and their target promoters. We describe a method, Fit-Hi-C, that assigns statistical confidence estimates to mid-range intra-chromosomal contacts by jointly modeling the random polymer looping effect and previously observed technical biases in Hi-C data sets. We demonstrate that our proposed approach computes accurate empirical null models of contact probability without any distribution assumption, corrects for binning artifacts, and provides improved statistical power relative to a previously described method. High-confidence contacts identified by Fit-Hi-C preferentially link expressed gene promoters to active enhancers identified by chromatin signatures in human embryonic stem cells (ESCs), capture 77% of RNA polymerase II-mediated enhancer-promoter interactions identified using ChIA-PET in mouse ESCs, and confirm previously validated, cell line-specific interactions in mouse cortex cells. We observe that insulators and heterochromatin regions are hubs for high-confidence contacts, while promoters and strong enhancers are involved in fewer contacts. We also observe that binding peaks of master pluripotency factors such as NANOG and POU5F1 are highly enriched in high-confidence contacts for human ESCs. Furthermore, we show that pairs of loci linked by high-confidence contacts exhibit similar replication timing in human and mouse ESCs and preferentially lie within the boundaries of topological domains for human and mouse cell lines.
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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.