Detecting Interacting Genetic Loci with Effects on Quantitative Traits Where the Nature and Order of the Interaction Are Unknown

作者：Davies Joanna L^*; Hein Jotun; Holmes Chris C

来源：Genetic Epidemiology, 2010, 34(4): 299-308.

DOI：10.1002/gepi.20461

• Bayesian mixture model
• gene-gene interaction
• gene-environment interactions
• Laplace approximation

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.

• 出版日期2010-5