{"doi":"10.1038/s41588-024-01689-8","title":"Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis","abstract":"We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC-seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene-peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.","journal":"Nature Genetics","year":2024,"id":417441,"datarank":0.6394019815561974,"base_score":4.2626798770413155,"endowment":4.2626798770413155,"self_citation_contribution":0.6394019815561974,"citation_network_contribution":0.0,"self_endowment_contribution":0.6394019815561974,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":70,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9444,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1203089,"name":"Ro Malik","orcid":"0009-0001-7417-0403","position":1,"is_corresponding":false},{"id":652287,"name":"Wilfred Wong","orcid":"0000-0003-1363-5235","position":2,"is_corresponding":false},{"id":1203090,"name":"A. Rahman","orcid":"0009-0000-6877-705X","position":3,"is_corresponding":false},{"id":12940,"name":"Alexander J. Hartemink","orcid":"0000-0002-1292-2606","position":4,"is_corresponding":false},{"id":349760,"name":"Yuri Pritykin","orcid":"0000-0001-6589-981X","position":5,"is_corresponding":false},{"id":6116,"name":"Kushal K. Dey","orcid":"0000-0002-3520-2345","position":6,"is_corresponding":false},{"id":43058,"name":"Christina S. Leslie","orcid":"0000-0002-4571-5910","position":7,"is_corresponding":false},{"id":572207,"name":"Sneha Mitra","orcid":"0000-0002-7718-8721","position":0,"is_corresponding":true}],"reference_count":75,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:56:50.743370Z","pmid":"38514783","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":[]}