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Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes$
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Michael Windle

Print publication date: 2016

Print ISBN-13: 9780262034685

Published to MIT Press Scholarship Online: May 2017

DOI: 10.7551/mitpress/9780262034685.001.0001

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Marker-Set Approaches for Assessing Gene × Environment Interactions at Gene Level

Marker-Set Approaches for Assessing Gene × Environment Interactions at Gene Level

Chapter:
(p.35) 3 Marker-Set Approaches for Assessing Gene × Environment Interactions at Gene Level
Source:
Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes
Author(s):

Jung-Ying Tzeng

Arnab Maity

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262034685.003.0003

This chapter reviews the statistical methods for studying GxE effect at gene-level. Depending on how the main and interaction effects are modelled, we generally classify the current methods into either fixed or random effects approaches. The fixed effects approaches model the main and interaction effects parametrically. They are easy to interpret and computationally efficient, but are sensitive to model misspecification of the multi-variant genetic and environment effects. In contrast, the random-effects approaches model the main and interaction effects in a semi-parametric fashion, and the effects are quantified using variance components. These models are more robust to model misspecification compared to fixed effects models, though with a price of increasing computational burden caused by the use of variance components to capture the effects.

Keywords:   Set-based GxE test, gene-based GxE test, kernel machine GxE test, similarity GxE test

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