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Pathway-based approach using hierarchical components of collapsed rare variants

机译:基于路径的方法,使用折叠的稀有变体的分层组件

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Motivation: To address 'missing heritability' issue, many statistical methods for pathway-based analyses using rare variants have been proposed to analyze pathways individually. However, neglecting correlations between multiple pathways can result in misleading solutions, and pathway-based analyses of large-scale genetic datasets require massive computational burden. We propose a Pathway-based approach using HierArchical components of collapsed RAre variants Of High-throughput sequencing data (PHARAOH) for the analysis of rare variants by constructing a single hierarchical model that consists of collapsed gene-level summaries and pathways and analyzes entire pathways simultaneously by imposing ridge-type penalties on both gene and pathway coefficient estimates; hence our method considers the correlation of pathways without constraint by a multiple testing problem.
机译:动机:为了解决“遗传力缺失”的问题,已提出了许多使用稀有变异体进行基于路径的分析的统计方法,以分别分析路径。但是,忽略多个路径之间的相关性可能导致产生误导性的解决方案,并且基于路径的大规模遗传数据集分析需要大量的计算负担。我们提出了一种基于途径的方法,该方法使用高通量测序数据的折叠RAre变体的分层层次成分(PHARAOH)来分析稀有变体,方法是构建一个由折叠的基因水平摘要和途径组成的单一层次模型,并同时分析整个途径通过对基因和途径系数估计值施加岭型惩罚;因此我们的方法考虑了路径的相关性而不受多重测试问题的约束。

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