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Robust genetic interaction analysis

机译:强大的遗传互动分析

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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.
机译:对于对许多复杂疾病的治疗的风险,进展和反应,越来越认识到遗传相互作用(包括基因 - 基因和基因 - 环境相互作用)在主要遗传和环境影响之外起重要作用。 在实际的遗传相互作用分析中,响应变量和协变量中的模型MIM规范和异常值/污染不常见,并且需求鲁棒分析方法。 与其非侦察对应物相比,强大的遗传相互作用分析方法显着不那么流行,但正在快速受到关注。 在本文中,我们对边缘和联合分析的方法和应用程序提供了对强大的遗传交互分析方法的全面审查,以及用于解决模型错误规范以及响应变量和协变量中的异常值/污染物。

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