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

Tao Feng; Robert C Elston; Xiaofeng Zhu

doi:10.1186/1753-6561-5-S9-S80

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

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

Authors

Tao Feng¹, Robert C Elston, Xiaofeng Zhu

Affiliation

¹ Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH 44106, USA. xzhu1@darwin.EPBI.cwru.edu.

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.