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Stratify or adjust? Dealing with multiple populations when evaluating rare variants

机译:分层还是调整?评估稀有变体时处理多个种群

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The unrelated individuals sample from Genetic Analysis Workshop 17 consists of a small number of subjects from eight population samples and genetic data composed mostly of rare variants. We compare two simple approaches to collapsing rare variants within genes for their utility in identifying genes that affect phenotype. We also compare results from stratified analyses to those from a pooled analysis that uses ethnicity as a covariate. We found that the two collapsing approaches were similarly effective in identifying genes that contain causative variants in these data. However, including population as a covariate was not an effective substitute for analyzing the subpopulations separately when only one subpopulation contained a rare variant linked to the phenotype.
机译:遗传分析研讨会17的无关个体样本由来自八个种群样本的少数受试者组成,遗传数据主要由稀有变异组成。我们比较了两种简单的方法来折叠基因中的稀有变体,以鉴定其影响表型的基因。我们还比较了分层分析的结果和使用种族作为协变量的合并分析的结果。我们发现,两种折叠方法在识别这些数据中包含致病性变异的基因方面同样有效。但是,当只有一个亚群包含与表型相关的罕见变体时,将种群作为协变量包括在内并不是单独分析亚群的有效替代方法。

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