ArticleBriefings in bioinformatics2023
SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data.
Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- CellLoop: Identifying single-cell 3D genome chromatin loops.Nature communications · 2026Article
- Differential analysis of image-based chromatin tracing data with Dory.bioRxiv : the preprint server for biology · 2026Article
- Recent advances in single-cell bioinformatics for inferring higher-order chromatin contact maps.BMB reports · 2025Review
- PB-DiffHiC: a statistical framework for detecting differential chromatin interactions from high resolution pseudo-bulk Hi-C data.BMC genomics · 2025Article
- Brain Region-Specific Epigenomic Reorganization and Altered Cell States in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025Article
- Navigating the 3D genome at single-cell resolution: techniques, computation, and mechanistic landscapes.Briefings in bioinformatics · 2025Review
- scHiCcompare: An R Package for Differential Analysis of Single-cell Hi-C Data.Journal of molecular biology · 2025Article
- Deciphering single-cell genomic architecture: insights into cellular heterogeneity and regulatory dynamics.Genomics & informatics · 2025Review
- A deep learning-based method enables the automatic and accurate assembly of chromosome-level genomes.Nucleic acids research · 2024Article
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Authors and funding
11 authors at 7 institutions in 2 countries.
Funding
Abstract
Single-cell high-throughput chromatin conformation capture technologies (scHi-C) has been used to map chromatin spatial organization in complex tissues. However, computational tools to detect differential chromatin contacts (DCCs) from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify DCCs between two scHi-C datasets. Compared to methods designed for bulk Hi-C data, SnapHiC-D detects DCCs with high sensitivity and accuracy. We used SnapHiC-D to identify cell-type-specific chromatin contacts at 10 Kb resolution in mouse hippocampal and human prefrontal cortical tissues, demonstrating that DCCs detected in the hippocampal and cortical cell types are generally associated with cell-type-specific gene expression patterns and epigenomic features. SnapHiC-D is freely available at https://github.com/HuMingLab/SnapHiC-D.
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Registered trials
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