| Literature DB >> 33733358 |
Fei Zhou1, Jie Ren2, Xi Lu1, Shuangge Ma3, Cen Wu4.
Abstract
Gene-environment interactions have important implications for elucidating the genetic basis of complex diseases beyond the joint function of multiple genetic factors and their interactions (or epistasis). In the past, G × E interactions have been mainly conducted within the framework of genetic association studies. The high dimensionality of G × E interactions, due to the complicated form of environmental effects and the presence of a large number of genetic factors including gene expressions and SNPs, has motivated the recent development of penalized variable selection methods for dissecting G × E interactions, which has been ignored in the majority of published reviews on genetic interaction studies. In this article, we first survey existing studies on both gene-environment and gene-gene interactions. Then, after a brief introduction to the variable selection methods, we review penalization and relevant variable selection methods in marginal and joint paradigms, respectively, under a variety of conceptual models. Discussions on strengths and limitations, as well as computational aspects of the variable selection methods tailored for G × E studies, have also been provided.Keywords: Bayesian variable selection; Gene–environment interaction; Linear and nonlinear interaction; Marginal and joint analysis; Penalization
Mesh:
Year: 2021 PMID: 33733358 DOI: 10.1007/978-1-0716-0947-7_13
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745