scTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies

Single-cell transcriptome-wide association studies (scTWAS) is a new method for conducting TWAS analysis at the cellular level to identify gene-trait associations with higher precision. This approach helps overcome the challenge of interpreting cell-type heterogeneity in traditional TWAS results. As the field of scTWAS rapidly advances, there is a growing need for additional database platforms to integrate this wealth of data and knowledge effectively. To address this gap, we present scTWAS Atlas (https://ngdc.cncb.ac.cn/sctwas/), a comprehensive database of scTWAS information integrating literature curation and data analysis. The current version of scTWAS Atlas amasses 2,765,211 associations encompassing 34 traits, 30 cell types, 9 cell conditions and 16,470 genes. The database features visualization tools, including an interactive knowledge graph that integrates single-cell expression quantitative trait loci (sc-eQTL) and scTWAS associations to build a multi-omics level regulatory network at the cellular level. Additionally, scTWAS Atlas facilitates cross-cell-type analysis, highlighting cell-type-specific and shared TWAS genes. The database is designed with user-friendly interfaces and allows for easy browsing, searching, and downloading of relevant information. Overall, scTWAS Atlas is instrumental in exploring the genetic regulatory mechanisms at the cellular level and shedding light on the role of various cell types in biological processes, offering novel insights for human health research.

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Publication Details

Journal
Nucleic Acids Research
Published
2024-10-18
DOI
https://doi.org/10.1093/nar/gkae931
Citations
5
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
1.17

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article

scTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies

Zhuojing Fan, Jingfa Xiao, Jingyao Zeng, Qiheng Qian et al.
5 citations
Nucleic Acids Research
Single-cell and spatial transcriptomics
1.17
article

scTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies

Zhuojing Fan, Jingfa Xiao, Jingyao Zeng, Qiheng Qian, Jialin Mai, Hao Gao
article en
5 citations

Abstract

Single-cell transcriptome-wide association studies (scTWAS) is a new method for conducting TWAS analysis at the cellular level to identify gene-trait associations with higher precision. This approach helps overcome the challenge of interpreting cell-type heterogeneity in traditional TWAS results. As the field of scTWAS rapidly advances, there is a growing need for additional database platforms to integrate this wealth of data and knowledge effectively. To address this gap, we present scTWAS Atlas (https://ngdc.cncb.ac.cn/sctwas/), a comprehensive database of scTWAS information integrating literature curation and data analysis. The current version of scTWAS Atlas amasses 2,765,211 associations encompassing 34 traits, 30 cell types, 9 cell conditions and 16,470 genes. The database features visualization tools, including an interactive knowledge graph that integrates single-cell expression quantitative trait loci (sc-eQTL) and scTWAS associations to build a multi-omics level regulatory network at the cellular level. Additionally, scTWAS Atlas facilitates cross-cell-type analysis, highlighting cell-type-specific and shared TWAS genes. The database is designed with user-friendly interfaces and allows for easy browsing, searching, and downloading of relevant information. Overall, scTWAS Atlas is instrumental in exploring the genetic regulatory mechanisms at the cellular level and shedding light on the role of various cell types in biological processes, offering novel insights for human health research.

Nucleic Acids ResearchVol. 53(D1)
Chinese Academy of Sciences (CN), Beijing Institute of Genomics (CN), Shanghai Center For Bioinformation Technology (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, Youth Innovation Promotion Association of the Chinese Academy of Sciences, Youth Innovation Promotion Association
Openalex Percentile: Top 21%
Single-cell and spatial transcriptomics
1.17
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