scTraitReg: a single-cell multi-omic database of trait-relevant transcription factor eRegulons
4 affiliations
- 1Jiangsu Key Laboratory for Biomedical Electromagnetic Precision Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University , Nanjing, Jiangsu 211166 ,
- 2Department of Transfusion Medicine, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing , Jiangsu 210022 ,
- 3Clinical Medical Research Center, Children’s Hospital of Nanjing Medical University , Nanjing, Jiangsu 210008 ,
- 4Cardiovascular Center, The Second Affiliated Hospital of Nanjing Medical University , Nanjing, Jiangsu 210011 ,
Abstract
Genome-wide association studies (GWAS) identify loci associated with human diseases and disease-related traits, but the regulators and cellular contexts linked to these signals remain difficult to resolve. We present scTraitReg, a database of trait-relevant transcription factor (TF) eRegulons—TFs with their target genes and linked cis-regulatory regions—at single-cell resolution. scTraitReg integrates 655 sets of curated GWAS summary statistics covering 122 Medical Subject Headings (MeSH) disease terms with 111 human single-cell multi-omic datasets profiling RNA and chromatin accessibility in the same cells. The resource spans 34 tissues, 252 cell types, 2 081 538 cells, and 2208 curated GWAS—single-cell analysis pairs. Across these analyses, it contains 2 840 939 TF–cell-type records for 886 regulators; 67 666 records met all three criteria—cell-type specificity, genetic relevance, and the trait-associated regulon score—and were included as candidate trait-relevant eRegulon records. Each record links to the TF—target regulatory network with its cis-regulatory regions, cell-type-resolved evidence, per-cell regulon module scores, and target-gene enrichment, all available as downloadable tables. Users can search by disease, tissue, cell type, or regulator and examine these associations through interactive visualizations. scTraitReg thus provides a searchable and reusable resource linking genetic associations to cell-type-specific regulatory programs, and is freely available at https://www.sctraitreg.bio/.
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BibTeX
@article{chen2026sctraitreg,
title = {{scTraitReg: a single-cell multi-omic database of trait-relevant transcription factor eRegulons}},
author = {Haoran Chen and Yin Liu and Xue Rui and Shengxian Li and Lingna Sun and Guoli Xiao and Haozhe Tang and Yanqun Sun and Xiang Guan and Chen Cao},
journal = {Nucleic Acids Research},
year = {2026},
month = oct,
doi = {10.1093/nar/gkag1017},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1017/8971830},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - scTraitReg: a single-cell multi-omic database of trait-relevant transcription factor eRegulons
AU - Haoran Chen
AU - Yin Liu
AU - Xue Rui
AU - Shengxian Li
AU - Lingna Sun
AU - Guoli Xiao
AU - Haozhe Tang
AU - Yanqun Sun
AU - Xiang Guan
AU - Chen Cao
PY - 2026
DA - 2026/10/22
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1017
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1017/8971830
AB - Genome-wide association studies (GWAS) identify loci associated with human diseases and disease-related traits, but the regulators and cellular contexts linked to these signals remain difficult to resolve. We present scTraitReg, a database of trait-relevant transcription factor (TF) eRegulons—TFs with their target genes and linked cis-regulatory regions—at single-cell resolution. scTraitReg integrates 655 sets of curated GWAS summary statistics covering 122 Medical Subject Headings (MeSH) disease terms with 111 human single-cell multi-omic datasets profiling RNA and chromatin accessibility in the same cells. The resource spans 34 tissues, 252 cell types, 2 081 538 cells, and 2208 curated GWAS—single-cell analysis pairs. Across these analyses, it contains 2 840 939 TF–cell-type records for 886 regulators; 67 666 records met all three criteria—cell-type specificity, genetic relevance, and the trait-associated regulon score—and were included as candidate trait-relevant eRegulon records. Each record links to the TF—target regulatory network with its cis-regulatory regions, cell-type-resolved evidence, per-cell regulon module scores, and target-gene enrichment, all available as downloadable tables. Users can search by disease, tissue, cell type, or regulator and examine these associations through interactive visualizations. scTraitReg thus provides a searchable and reusable resource linking genetic associations to cell-type-specific regulatory programs, and is freely available at https://www.sctraitreg.bio/.
SN - 0305-1048
SN - 1362-4962
ER -