DRCTdb: disease-related cell type analysis to decode cell type effect and underlying regulatory mechanisms
Understanding the molecular mechanisms underlying genetic diseases is challenging due to environmental and genetic factors. Genome-wide association studies (GWAS) have identified numerous genetic loci, but their functional implications are largely unknown. Single-cell multiomics sequencing has emerged as a powerful tool to study disease-specific cell types and their relationship with genetic variants. However, comprehensive databases for exploring these mechanisms across different tissues are lacking. We present the Disease-Related Cell Type database (DRCTdb), integrating GWAS and single-cell multiomics data to identify disease-related cell types and elucidate their regulatory mechanisms. DRCTdb contains well-processed data from 16 studies, covering 4 million cells within 28 tissues. Users can browse relationships and regulatory mechanisms between SNPs of 42 genetic diseases and cell types based on GWAS and single-cell data. DRCTdb also offers data downloads and is available at https://singlecellatlas.top/DRCTDB .
Authors
- Sheng Qin (ORCID: https://orcid.org/0000-0003-2916-1871)
- Yunhui Kong (ORCID: https://orcid.org/0000-0003-3004-7574)
- Junyao Jiang (ORCID: https://orcid.org/0009-0006-8639-059X)
- Weikang Kong
Institutions
- Suzhou University of Science and Technology (CN)
- Westlake University (CN)
- Jiangsu University of Science and Technology (CN)
- Ministry of Agriculture (CA)
- Sericultural Research Institute (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Communications Biology
- Published
- 2024-09-28
- DOI
- https://doi.org/10.1038/s42003-024-06833-y
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- National Natural Science Foundation of China
- Government of Jiangsu Province