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 .

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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

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article

DRCTdb: disease-related cell type analysis to decode cell type effect and underlying regulatory mechanisms

Sheng Qin, Yunhui Kong, Junyao Jiang, Weikang Kong
1 citations
Communications Biology
Single-cell and spatial transcriptomics
0.23
article

DRCTdb: disease-related cell type analysis to decode cell type effect and underlying regulatory mechanisms

Sheng Qin, Yunhui Kong, Junyao Jiang, Weikang Kong
article en
1 citations

Abstract

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 .

Communications BiologyVol. 7(1)
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)
National Natural Science Foundation of China, Government of Jiangsu Province
Openalex Percentile: Top 42%
Single-cell and spatial transcriptomics
0.23
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DRCTdb: disease-related cell type analysis to decode cell type effect and underlying regulatory mechanisms — Sheng Qin, Yunhui Kong, et al. · Communications Biology (2024) | TGRS Research Map | TGRS