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一种利用家系数据和非亲缘病例对照数据检测罕见变异的新方法。

A novel method to detect rare variants using both family and unrelated case-control data.

作者信息

Feng Tao, Elston Robert C, Zhu Xiaofeng

机构信息

Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH 44106, USA.

出版信息

BMC Proc. 2011 Nov 29;5 Suppl 9(Suppl 9):S80. doi: 10.1186/1753-6561-5-S9-S80.

Abstract

To detect rare variants associated with a phenotype, we develop a novel statistical method that can use both family and unrelated case-control data. Unlike the currently existing methods, we first use family data to calculate weights to be given to rare variants, differentiating between concordantly affected and discordant sib pairs. These weights are then used in an association test applied to the unrelated case-control data. We applied the proposed method to the simulated sequencing data in Genetic Analysis Workshop 17 and identified two genes associated with the disease.

摘要

为了检测与一种表型相关的罕见变异,我们开发了一种新颖的统计方法,该方法可以同时使用家系数据和非亲缘病例对照数据。与现有方法不同的是,我们首先使用家系数据来计算赋予罕见变异的权重,区分一致患病和不一致的同胞对。然后将这些权重用于应用于非亲缘病例对照数据的关联测试中。我们将所提出的方法应用于遗传分析研讨会17的模拟测序数据,并鉴定出两个与该疾病相关的基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97cf/3287921/40ec17bf7236/1753-6561-5-S9-S80-1.jpg

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