WebTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study. Issue Volume 50:Issue D1(2022) (20th October 2021)
- Record Type:
- Journal Article
- Title:
- WebTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study. Issue Volume 50:Issue D1(2022) (20th October 2021)
- Main Title:
- WebTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study
- Authors:
- Cao, Chen
Wang, Jianhua
Kwok, Devin
Cui, Feifei
Zhang, Zilong
Zhao, Da
Li, Mulin Jun
Zou, Quan - Abstract:
- Abstract: The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases. However, there are currently no resources providing a comprehensive listing of gene-disease associations discovered by TWAS from published GWAS summary statistics. TWAS analyses are also difficult to conduct due to the complexity of TWAS software pipelines. To address these issues, we introduce a new resource called webTWAS, which integrates a database of the most comprehensive disease GWAS datasets currently available with credible sets of potential causal genes identified by multiple TWAS software packages. Specifically, a total of 235 064 gene-diseases associations for a wide range of human diseases are prioritized from 1298 high-quality downloadable European GWAS summary statistics. Associations are calculated with seven different statistical models based on three popular and representative TWAS software packages. Users can explore associations at the gene or disease level, and easily search for related studies or diseases using the MeSH disease tree. Since the effects of diseases are highly tissue-specific, webTWAS applies tissue-specific enrichment analysis to identify significant tissues. A user-friendly web server is also available to run custom TWAS analyses on user-provided GWAS summary statistics data. webTWAS is freely available at http://www.webtwas.net .
- Is Part Of:
- Nucleic acids research. Volume 50:Issue D1(2022)
- Journal:
- Nucleic acids research
- Issue:
- Volume 50:Issue D1(2022)
- Issue Display:
- Volume 50, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 50
- Issue:
- 1
- Issue Sort Value:
- 2022-0050-0001-0000
- Page Start:
- D1123
- Page End:
- D1130
- Publication Date:
- 2021-10-20
- Subjects:
- Nucleic acids -- Periodicals
Molecular biology -- Periodicals
572.805 - Journal URLs:
- http://nar.oxfordjournals.org/ ↗
http://www.ncbi.nlm.nih.gov/pmc/journals/4 ↗
http://ukcatalogue.oup.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1093/nar/gkab957 ↗
- Languages:
- English
- ISSNs:
- 0305-1048
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6183.850000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21045.xml