A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
Joint Authors
Source
International Journal of Genomics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-31
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Biology
Abstract EN
A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease.
Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level.
The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information.
The entire model is fitted using Markov chain Monte Carlo methods.
Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects.
The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.
American Psychological Association (APA)
Duan, Lewei& Thomas, Duncan C.. 2013. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk. International Journal of Genomics،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-469559
Modern Language Association (MLA)
Duan, Lewei& Thomas, Duncan C.. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk. International Journal of Genomics No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-469559
American Medical Association (AMA)
Duan, Lewei& Thomas, Duncan C.. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk. International Journal of Genomics. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-469559
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-469559