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Toward a Network-Based Approach to Modeling Epistatic Interactions in Genome-Wide Association Studies

机译:在全基因组关联研究中建立基于网络的上位性相互作用建模方法

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In genome-wide association studies, statistical procedures such as logistic regression or the Cochran-Armitage test for trend can be used for the analysis of genetic variants while taking the underlying genetic model into consideration. Should a researcher was to investigate the role played by the interaction between two or more of these genetic variants (epistasis), it would suffice to add an interaction term, which corresponds to their product, to a logistic regression model. However, we question whether such a model is able to capture the intricacy of the genetic architecture in complex traits. Therefore, this paper proposes a network-based model that allows graph theory to characterize both genetic variants and their interactions in a genome-wide context, including a simulation study that proves its applicability.
机译:在全基因组关联研究中,可以将诸如逻辑回归或趋势的Cochran-Armitage检验之类的统计程序用于分析遗传变异,同时考虑潜在的遗传模型。如果研究人员要研究两个或多个这些遗传变异(epistasis)之间的相互作用所起的作用,就可以在逻辑回归模型中添加一个与其产品相对应的相互作用项。但是,我们质疑这种模型是否能够捕捉复杂性状中遗传结构的复杂性。因此,本文提出了一个基于网络的模型,该模型允许图论在整个基因组范围内表征遗传变异及其相互作用,其中包括一项模拟研究,证明了其适用性。

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