Candidate disease gene prediction using Gentrepid: application to a genome-wide association study on coronary artery disease.
- Author(s)
- Ballouz, S; Liu, JY; Oti, M; Gaeta, B; Fatkin, D; Bahlo, M; Wouters, MA;
- Details
- Publication Year 2014-01,Volume 2,Issue #1,Page 44-57
- Journal Title
- Molecular genetics & genomic medicine
- Publication Type
- Journal Article
- 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.
- Publisher
- WILEY
- Keywords
- Candidate gene prediction, WTCCC, cis-ruption, complex diseases, coronary artery disease, genome-wide association study, miRNA, Wellcome Trust Case Control Consortium
- Research Division(s)
- Bioinformatics
- Link To PubMed Central Version
- http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907915/
- Publisher's Version
- https://doi.org/10.1002/mgg3.40
- Open Access at Publisher's Site
http://onlinelibrary.wiley.com/doi/10.1002/mgg3.40/full- Terms of Use/Rights Notice
- Copyright © 2013 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc. 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.
Creation Date: 2014-02-21 08:58:53