ArticleComputational and structural biotechnology journal2022
SnapHiC2: A computationally efficient loop caller for single cell Hi-C data.
Article in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.Nature communications · 2026Article
- Predicting enhancer-gene links from single-cell multi-omics data by integrating prior Hi-C information.Nucleic acids research · 2026Article
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.bioRxiv : the preprint server for biology · 2026Article
- Trimodal single-cell profiling of transcriptome, epigenome and 3D genome in complex tissues with scHiCAR.Nature biotechnology · 2026Article
- Harmonizing single-cell 3D genome data with STARK and scNucleome.Genome biology · 2026Article
- PB-DiffHiC: a statistical framework for detecting differential chromatin interactions from high resolution pseudo-bulk Hi-C data.BMC genomics · 2025Article
- Unveiling Multi-Scale Architectural Features in Single-Cell Hi-C Data Using scCAFE.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Single-Cell Hi-C Technologies and Computational Data Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Deciphering single-cell genomic architecture: insights into cellular heterogeneity and regulatory dynamics.Genomics & informatics · 2025Review
- ChromaFactor: Deconvolution of single-molecule chromatin organization with non-negative matrix factorization.PLoS computational biology · 2025Article
- Can random walking on a Hi-C contact matrix lead to data quality improvement? An assessment.PloS one · 2025Article
- Topologically associating domains of chromatin on single-cell Hi-C data: a survey of bioinformatic tools and applications in the light of artificial intelligence.Frontiers in genetics · 2025Review
- Single-cell omics: experimental workflow, data analyses and applications.Science China. Life sciences · 2025Review
- SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model.Briefings in bioinformatics · 2024Article
- A Lightweight Framework For Chromatin Loop Detection at the Single-Cell Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data.Briefings in bioinformatics · 2023Article
- Interpreting non-coding disease-associated human variants using single-cell epigenomics.Nature reviews. Genetics · 2023Review
- Understanding the function of regulatory DNA interactions in the interpretation of non-coding GWAS variants.Frontiers in cell and developmental biology · 2022Review
- Every gene everywhere all at once: High-precision measurement of 3D chromosome architecture with single-cell Hi-C.Frontiers in molecular biosciences · 2022Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Single cell Hi-C (scHi-C) technologies enable the study of chromatin spatial organization directly from complex tissues at single cell resolution. However, the identification of chromatin loops from single cells is challenging, largely due to the extremely sparse data. Our recently developed SnapHiC pipeline provides the first tool to map chromatin loops from scHi-C data, but it is computationally intensive. Here we introduce SnapHiC2, which adapts a sliding window approximation when imputing missing contacts in each single cell and reduces both memory usage and computational time by 70%. SnapHiC2 can identify 5 Kb resolution chromatin loops with high sensitivity and accuracy and help to suggest target genes for GWAS variants in a cell-type-specific manner. SnapHiC2 is freely available at: https://github.com/HuMingLab/SnapHiC/releases/tag/v0.2.2.
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Registered trials
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.