{"doi":"10.1101/2021.05.17.444465","title":"<i>Compartmap</i>\n                  enables inference of higher-order chromatin structure in individual cells from scRNA-seq and scATAC-seq","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>\n                  Single-cell profiling of chromatin structure remains a challenge due to cost, throughput, and resolution. We introduce\n                  <jats:italic>compartmap</jats:italic>\n                  to reconstruct higher-order chromatin domains in individual cells from transcriptomic (RNAseq) and epigenomic (ATACseq) assays. In cell lines and primary human samples,\n                  <jats:italic>compartmap</jats:italic>\n                  infers higher-order chromatin structure comparable to specialized chromatin capture methods, and identifies clinically relevant structural alterations in single cells. This provides a common lens to integrate transcriptional and epigenomic results, linking higher-order chromatin architecture to gene regulation and to clinically relevant phenotypes in individual cells.\n                </jats:p>","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":null,"id":33042,"datarank":0.1262050998566693,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.02223302277267749,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.02223302277267749,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":1,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":173744,"name":"Jean-Philippe Fortin","orcid":"0000-0001-6786-0599","position":1,"is_corresponding":false},{"id":29385,"name":"Kasper D. Hansen","orcid":"0000-0003-0086-0687","position":2,"is_corresponding":false},{"id":14040,"name":"Hui Shen","orcid":"0000-0001-9767-4084","position":3,"is_corresponding":false},{"id":1837,"name":"Timothy J. Triche","orcid":"0000-0001-5665-946X","position":4,"is_corresponding":false},{"id":69080,"name":"Benjamin K. Johnson","orcid":"0000-0003-2997-1604","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"24523987","pmcid":null,"openalex_id":"https://openalex.org/W3160486573","authors":[],"funders":[{"funder_name":"National Institutes of Health","grant_id":"4R37CA230748-06","title":"High-throughput Epigenomic Mapping of Regulatory Elements in Ovarian Cancer at Basepair Resolution"}],"total_grants":1,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2021,"count":1}],"oa_status":"green","license":"cc-by","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2021/05/18/2021.05.17.444465.full.pdf","host_type":"repository"},{"url":"https://doi.org/10.1101/2021.05.17.444465","host_type":"GREEN"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2021/05/18/2021.05.17.444465.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2021.05.17.444465","host_type":"publisher"},{"url":"https://dx.doi.org/10.1101/2021.05.17.444465","host_type":""}],"fields_of_study":["Single-cell and spatial transcriptomics","Genomics and Chromatin Dynamics","Cancer Genomics and Diagnostics","Biology","Computer Science","Medicine","0301 basic medicine","0303 health sciences","03 medical and health sciences"],"mesh_terms":[],"keywords":["Chromatin","Epigenomics","Computational biology","Biology","Transcriptome","Phenotype","Chromosome conformation capture","Gene","Genetics","Gene expression","Enhancer","DNA methylation"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-09T15:26:50.291176Z","pmid":null,"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":[]}