Detecting interacting genetic loci with effects on quantitative traits where the nature and order of the interaction are unknown
✍ Scribed by Joanna L. Davies; Jotun Hein; Chris C. Holmes
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 284 KB
- Volume
- 34
- Category
- Article
- ISSN
- 0741-0395
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✦ Synopsis
Abstract
Standard techniques for single marker quantitative trait mapping perform poorly in detecting complex interacting genetic influences. When a genetic marker interacts with other genetic markers and/or environmental factors to influence a quantitative trait, a sample of individuals will show different effects according to their exposure to other interacting factors. This paper presents a Bayesian mixture model, which effectively models heterogeneous genetic effects apparent at a single marker. We compute approximate Bayes factors which provide an efficient strategy for screening genetic markers (genome‐wide) for evidence of a heterogeneous effect on a quantitative trait. We present a simulation study which demonstrates that the approximation is good and provide a real data example which identifies a population‐specific genetic effect on gene expression in the HapMap CEU and YRI populations. We advocate the use of the model as a strategy for identifying candidate interacting markers without any knowledge of the nature or order of the interaction. The source of heterogeneity can be modeled as an extension. Genet. Epidemiol. 34: 299–308, 2010. © 2009 Wiley‐Liss, Inc.