Work

An Efficient Bayesian Model Selection Approach for Interacting Quantitative Trait Loci Models With Many Effects

Year: 2007

Type: article

Abstract: We extend our Bayesian model selection framework for mapping epistatic QTL in experimental crosses to include environmental effects and gene-environment interactions. We propose a new, fast Markov chain Monte Carlo algorithm to explore the posterior distribution of unknowns. In addition, we take advantage of any prior knowledge about genetic architecture to increase posterior probability on more probable models. These enhancements have significant computational advantages in models with many effects. We illustrate the proposed method by detecting new epistatic and gene-sex interactions for obesity-related traits in two real data sets of mice. Our method has been implemented in the freely available package R/qtlbim (http://www.qtlbim.org) to facilitate the general usage of the Bayesian methodology for genomewide interacting QTL analysis.

Source: Genetics

DOI: 10.1534/genetics.107.071365

Authors: Nengjun Yi, Daniel Shriner, Samprit Banerjee, Tapan Mehta, Daniel Pomp, Brian S Yandell

Institutions: University of Alabama, University of Alabama at Birmingham, University of North Carolina at Chapel Hill, University of Wisconsin–Madison

Language: English

Topic: Genetic Mapping and Diversity in Plants and Animals

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: bronze