{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Sakaue S"],"funding":["U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)","Doris Duke Charitable Foundation","NIAID NIH HHS","Rheumatology Research Foundation","U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI)","U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases","NHGRI NIH HHS","Uehara Memorial Foundation","U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute","NIAMS NIH HHS"],"pagination":["615-626"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11456345"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["56(4)"],"pubmed_abstract":["Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 dis"],"journal":["Nature genetics"],"pubmed_title":["Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles."],"pmcid":["PMC11456345"],"funding_grant_id":["K08 AR077037","T32AR007530","R01 AR063759","R56 HG013083","UC2 AR081023","U01 HG012009","T32 AR007530","R00 HG012203","UH2 AR067677","U01HG012009","R01AR063759","UC2AR081023","K08AR077037","T32 HG002295","P01 AI148102"],"pubmed_authors":["Zhang F","Mandelin AM","Robinson WH","Liao KP","Raychaudhuri S","Dunn P","Gravallese EM","Ishigaki K","Bykerk VP","Gurajala S","Rangel-Moreno J","Accelerating Medicines Partnership® RA/SLE Program and Network","Meednu N","Scheel-Toellner D","Maybury M","Boyle DL","Firestein GS","Gutierrez-Arcelus M","Hughes LB","Raza K","DiCarlo E","Moreland LW","Reshef Y","James JA","Nathan A","Rivellese F","Price AL","Smith MH","Sahbudin I","Li Y","Nerviani A","Mantel I","Filer A","Brenner MB","Rumker L","Kanai M","Utz PJ","Michael Holers V","Geraldino-Pardilla L","Orange DE","Korsunsky I","Isaac S","Zhu Z","Banda N","Ivashkiv LB","Barnas JL","Weinand K","Watts GFM","Guthridge JM","Li ZJ","Keras G","Albrecht J","Lederer JA","Ritchlin C","Weisenfeld D","Dey KK","Donlin LT","Goodman SM","Horowitz D","Apruzzese W","Chicoine A","Wei K","Bathon JM","Gregersen PK","Jagadeesh K","Carr HL","Seifert JA","Sakaue S","Deane KD","Slowikowski K","Cordle A","Forbess L","Lakhanpal A","Rao DA","Anolik JH","Boyce BF","Perlman H","Millard N","Curtis M","Xiao Q","Mears J","Ben-Artzi A","Bridges SL","Campbell D","McDavid A","Tabechian D","Pitzalis C","Ceponis A","Jonsson AH","Kang JB","Weisman MH"],"additional_accession":[]},"is_claimable":false,"name":"Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles.","description":"Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 dis","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Apr","modification":"2026-06-02T22:16:21.976Z","creation":"2026-04-21T03:14:29.723Z"},"accession":"S-EPMC11456345","cross_references":{"pubmed":["38594305"],"doi":["10.1038/s41588-024-01682-1"]}}