Ballouz, Sara and Liu, Jason Y and Oti, Martin and Gaeta, Bruno and Fatkin, Diane and Bahlo, Melanie and Wouters, Merridee A (2014) Candidate disease gene prediction using Gentrepid: application to a genome-wide association study on coronary artery disease. Molecular genetics & Genomic Medicine, 2 (1). pp.44-57. ISSN 2324-9269 (OA)
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Abstract
Current single-locus-based analyses and candidate disease gene prediction methodologies used in genome-wide association studies (GWAS) do not capitalize on the wealth of the underlying genetic data, nor functional data available from molecular biology. Here, we analyzed GWAS data from the Wellcome Trust Case Control Consortium (WTCCC) on coronary artery disease (CAD). Gentrepid uses a multiple-locus-based approach, drawing on protein pathway- or domain-based data to make predictions. Known disease genes may be used as additional information (seeded method) or predictions can be based entirely on GWAS single nucleotide polymorphisms (SNPs) (ab initio method). We looked in detail at specific predictions made by Gentrepid for CAD and compared these with known genetic data and the scientific literature. Gentrepid was able to extract known disease genes from the candidate search space and predict plausible novel disease genes from both known and novel WTCCC-implicated loci. The disease gene candidates are consistent with known biological information. The results demonstrate that this computational approach is feasible and a valuable discovery tool for geneticists.(NHMRC grant 635512)
| Item Type: | Article |
|---|---|
| Additional Information: | This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Subjects: | R Medicine > R Medicine (General) |
| Depositing User: | Repository Administrator |
| Date Deposited: | 10 Dec 2015 23:50 |
| Last Modified: | 18 May 2016 07:13 |
| URI: | https://eprints.victorchang.edu.au/id/eprint/4 |
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