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Review
. 2019 Mar 25;20(2):624-637.
doi: 10.1093/bib/bby033.

Robust genetic interaction analysis

Mengyun Wu  1 , Shuangge Ma  1
Affiliations
Review

Robust genetic interaction analysis

Mengyun Wu et al. Brief Bioinform. .

Abstract

For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that genetic interactions (including gene-gene and gene-environment interactions) play important roles beyond the main genetic and environmental effects. In practical genetic interaction analyses, model mis-specification and outliers/contaminations in response variables and covariates are not uncommon, and demand robust analysis methods. Compared with their nonrobust counterparts, robust genetic interaction analysis methods are significantly less popular but are gaining attention fast. In this article, we provide a comprehensive review of robust genetic interaction analysis methods, on their methodologies and applications, for both marginal and joint analysis, and for addressing model mis-specification as well as outliers/contaminations in response variables and covariates.

Keywords: genetic interaction; model mis-specification; outlier/contamination; robustness.

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