webTWAS 2.0: update platform for identifying complex disease susceptibility genes through transcriptome-wide
Chen Cao1, Mengting Shao1, Jianhua Wang2
1Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University,101 Longmian Ave, Nanjing, Jiangsu 211166, China.
Nucleic Acids Research
|November 11, 2024
Summary
webTWAS 2.0 enhances gene discovery for complex diseases using transcriptome-wide association studies (TWAS). This updated platform simplifies TWAS analysis and integrates extensive genetic data for researchers.
Area of Science:
- Genetics
- Bioinformatics
- Computational Biology
Background:
- Transcriptome-wide association study (TWAS) has become a powerful tool for identifying complex disease susceptibility genes.
- Recent advancements focus on understanding how single nucleotide polymorphisms (SNPs) regulate gene expression, incorporating fine-mapping techniques.
- The exponential growth of genome-wide association study (GWAS) summary statistics necessitates updated resources.
Purpose of the Study:
- To introduce webTWAS 2.0, an enhanced platform for identifying human complex disease susceptibility genes using TWAS.
- To provide an integrated online TWAS analysis tool for researchers.
- To update the webTWAS resource with expanded GWAS summary statistics and multiple TWAS methods.
Main Methods:
- Integration of 7247 GWAS summary statistics from 192 publications, covering 1588 complex diseases.
- Implementation of multiple TWAS algorithms including sTF-TWAS, 3'aTWAS, and GIFT.
- Development of an interactive visualization tool and a personalized online analysis tool for user-submitted GWAS data.
Main Results:
- webTWAS 2.0 incorporates a significantly larger dataset of GWAS summary statistics and diverse TWAS methodologies.
- The platform offers an updated interactive visualization tool for exploring significant genetic associations.
- A refined search function and personalized analysis tool enhance user efficiency and data exploration.
Conclusions:
- webTWAS 2.0 provides a comprehensive and user-friendly platform for TWAS, facilitating the identification of complex disease genes.
- The updated resource and analysis tools support researchers in leveraging large-scale genetic data for gene discovery.
- The platform's accessibility and enhanced features aim to meet the evolving needs of the research community.
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