webTWAS 2.0: update platform for identifying complex disease susceptibility genes through transcriptome-wide association study

Transcriptome-wide association study (TWAS) has successfully identified numerous complex disease susceptibility genes in the post-genome-wide association study (GWAS) era. Over the past 3 years, the focus of TWAS algorithms has shifted from merely identifying associations to understanding how single nucleotide polymorphisms (SNPs) regulate gene expression, with a growing emphasis on incorporating fine-mapping techniques. Additionally, the rapid increase in GWAS summary statistics, driven largely by the UK Biobank and other consortia, has made it essential to update our webTWAS resource. To address these challenges and meet the growing needs of researchers, we developed webTWAS 2.0, an updated platform for identifying susceptibility genes for human complex diseases using TWAS. Additionally, webTWAS 2.0 provides an online TWAS analysis tool that simplifies conducting TWAS analyses. The updated resource includes 7247 GWAS summary statistics covering 1588 complex human diseases from 192 publications. It also incorporates multiple TWAS methods, such as sTF-TWAS, 3'aTWAS and GIFT, along with an updated interactive visualization tool that allows users to easily explore significant associations across different methods. Other upgrades include a personalized online analysis tool for user-submitted GWAS data and a refined search function that makes it easier to identify relevant associations and meet diverse user needs more efficiently. webTWAS 2.0 is freely accessible at http://www.webtwas.net.

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Publication Details

Journal
Nucleic Acids Research
Published
2024-11-11
DOI
https://doi.org/10.1093/nar/gkae1022
Citations
7
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
3.85

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article

webTWAS 2.0: update platform for identifying complex disease susceptibility genes through transcriptome-wide association study

Quan Zou, Haoran Chen, Tianyi You, Jianhua Wang et al.
7 citations
Nucleic Acids Research
Genetic Associations and Epidemiology
3.85
article

webTWAS 2.0: update platform for identifying complex disease susceptibility genes through transcriptome-wide association study

Quan Zou, Haoran Chen, Tianyi You, Jianhua Wang, Chen Cao, Zhenghui Li, Mulin Jun Li, Yijie Ding, Mengting Shao
article en
7 citations

Abstract

Transcriptome-wide association study (TWAS) has successfully identified numerous complex disease susceptibility genes in the post-genome-wide association study (GWAS) era. Over the past 3 years, the focus of TWAS algorithms has shifted from merely identifying associations to understanding how single nucleotide polymorphisms (SNPs) regulate gene expression, with a growing emphasis on incorporating fine-mapping techniques. Additionally, the rapid increase in GWAS summary statistics, driven largely by the UK Biobank and other consortia, has made it essential to update our webTWAS resource. To address these challenges and meet the growing needs of researchers, we developed webTWAS 2.0, an updated platform for identifying susceptibility genes for human complex diseases using TWAS. Additionally, webTWAS 2.0 provides an online TWAS analysis tool that simplifies conducting TWAS analyses. The updated resource includes 7247 GWAS summary statistics covering 1588 complex human diseases from 192 publications. It also incorporates multiple TWAS methods, such as sTF-TWAS, 3'aTWAS and GIFT, along with an updated interactive visualization tool that allows users to easily explore significant associations across different methods. Other upgrades include a personalized online analysis tool for user-submitted GWAS data and a refined search function that makes it easier to identify relevant associations and meet diverse user needs more efficiently. webTWAS 2.0 is freely accessible at http://www.webtwas.net.

Nucleic Acids ResearchVol. 53(D1)
University of Electronic Science and Technology of China (CN), Theranostics (New Zealand) (NZ), Quzhou University (CN), Translational Therapeutics (United States) (US), Tianjin Medical University (CN), University of Pennsylvania (US), Nanjing Medical University (CN)
National Natural Science Foundation of China
Partnerships for the goals
Openalex Percentile: Top 6%
Genetic Associations and Epidemiology
3.85
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