{"doi":"10.1038/s41592-021-01231-2","title":"SnapHiC: a computational pipeline to identify chromatin loops from single-cell Hi-C data","abstract":"Single-cell Hi-C (scHi-C) analysis has been increasingly used to map chromatin architecture in diverse tissue contexts, but computational tools to define chromatin loops at high resolution from scHi-C data are still lacking. Here, we describe Single-Nucleus Analysis Pipeline for Hi-C (SnapHiC), a method that can identify chromatin loops at high resolution and accuracy from scHi-C data. Using scHi-C data from 742 mouse embryonic stem cells, we benchmark SnapHiC against a number of computational tools developed for mapping chromatin loops and interactions from bulk Hi-C. We further demonstrate its use by analyzing single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells, which uncovers cell type-specific chromatin loops and predicts putative target genes for noncoding sequence variants associated with neuropsychiatric disorders. Our results indicate that SnapHiC could facilitate the analysis of cell type-specific chromatin architecture and gene regulatory programs in complex tissues.","journal":"Nature Methods","year":2021,"id":150191,"datarank":0.687745121800586,"base_score":4.584967478670572,"endowment":4.584967478670572,"self_citation_contribution":0.687745121800586,"citation_network_contribution":0.0,"self_endowment_contribution":0.687745121800586,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":97,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8444,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":254650,"name":"Armen Abnousi","orcid":"0000-0003-1822-0928","position":1,"is_corresponding":false},{"id":21276,"name":"Yanxiao Zhang","orcid":"0000-0001-9618-637X","position":2,"is_corresponding":false},{"id":21274,"name":"Guoqiang Li","orcid":"0000-0001-5303-5707","position":3,"is_corresponding":false},{"id":638491,"name":"Lindsay Lee","orcid":"0000-0001-5591-6233","position":4,"is_corresponding":false},{"id":638492,"name":"Ziyin Chen","orcid":"0000-0002-5760-4177","position":5,"is_corresponding":false},{"id":21279,"name":"Rongxin Fang","orcid":"0000-0003-0107-7504","position":6,"is_corresponding":false},{"id":639519,"name":"Taylor M. Lagler","orcid":null,"position":7,"is_corresponding":false},{"id":307169,"name":"Yuchen Yang","orcid":"0000-0001-5977-1617","position":8,"is_corresponding":false},{"id":254652,"name":"Jia Wen","orcid":"0000-0003-3273-7704","position":9,"is_corresponding":false},{"id":11263,"name":"Quan Sun","orcid":"0000-0001-8324-2803","position":10,"is_corresponding":false},{"id":24805,"name":"Yun Li","orcid":"0000-0002-9275-4189","position":11,"is_corresponding":false},{"id":136223,"name":"Bing Ren","orcid":"0000-0002-5435-1127","position":12,"is_corresponding":false},{"id":254661,"name":"Ming Hu","orcid":"0000-0003-0987-2916","position":13,"is_corresponding":false},{"id":227587,"name":"Miao Yu","orcid":"0009-0008-3981-7284","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T23:43:01.325389Z","pmid":"34446921","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}