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Update on the State of the Science for Analytical Methods for Gene-Environment Interactions

Abstract : The analysis of gene-environment interaction (G×E) may hold the key for further understanding the etiology of many complex traits. The current availability of high-volume genetic data, the wide range in types of environmental data that can be measured, and the formation of consortiums of multiple studies provide new opportunities to identify G×E but also new analytical challenges. In this article, we summarize several statistical approaches that can be used to test for G×E in a genome-wide association study. These include traditional models of G×E in a case-control or quantitative trait study as well as alternative approaches that can provide substantially greater power. The latest methods for analyzing G×E with gene sets and with data in a consortium setting are summarized, as are issues that arise due to the complexity of environmental data. We provide some speculation on why detecting G×E in a genome-wide association study has thus far been difficult. We conclude with a description of software programs that can be used to implement most of the methods described in the paper.
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Submitted on : Monday, July 5, 2021 - 8:00:39 PM
Last modification on : Tuesday, November 29, 2022 - 12:02:10 PM

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W James Gauderman, Bhramar Mukherjee, Hugues Aschard, Li Hsu, Juan Pablo Lewinger, et al.. Update on the State of the Science for Analytical Methods for Gene-Environment Interactions. American Journal of Epidemiology, 2017, 186 (7), pp.762-770. ⟨10.1093/aje/kwx228⟩. ⟨pasteur-03278715⟩



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