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A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

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 i...

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Autores principales: Duan, Lewei, Thomas, Duncan C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3892936/
https://www.ncbi.nlm.nih.gov/pubmed/24490143
http://dx.doi.org/10.1155/2013/406217
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author Duan, Lewei
Thomas, Duncan C.
author_facet Duan, Lewei
Thomas, Duncan C.
author_sort Duan, Lewei
collection PubMed
description 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.
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spelling pubmed-38929362014-02-02 A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk Duan, Lewei Thomas, Duncan C. Int J Genomics Research Article 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. Hindawi Publishing Corporation 2013 2013-12-31 /pmc/articles/PMC3892936/ /pubmed/24490143 http://dx.doi.org/10.1155/2013/406217 Text en Copyright © 2013 L. Duan and D. C. Thomas. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Duan, Lewei
Thomas, Duncan C.
A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
title A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
title_full A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
title_fullStr A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
title_full_unstemmed A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
title_short A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk
title_sort bayesian hierarchical model for relating multiple snps within multiple genes to disease risk
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3892936/
https://www.ncbi.nlm.nih.gov/pubmed/24490143
http://dx.doi.org/10.1155/2013/406217
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