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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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A Gene-Based Approach for Testing Gene × Gene and Gene × Environment Interactions

A Gene-Based Approach for Testing Gene × Gene and Gene × Environment Interactions

Chapter:
(p.71) 5 A Gene-Based Approach for Testing Gene × Gene and Gene × Environment Interactions
Source:
Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes
Author(s):

Tao Wang

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262034685.003.0005

The importance of the gene × gene (G × G) and gene × environment (G × E) interaction has been widely recognized. It is statistically challenging to account for interactions in the analysis of genome-wide association data. In this chapter, we introduce a gene-based method for modeling G × G and G × E interactions under the regression framework. We evaluate the type 1 error rate and power of this new method by simulations. We apply this method to the endometrial cancer case-control dataset.

Keywords:   Genome-wide association study, gene × gene and gene × environment interaction, regression model, partial least square

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