Evaluation of association tests for rare variants using simulated data sets in the Genetic Analysis Workshop 17 data

BMC Proceedings

Proceedings

Degui Zhi¹  Nianjun Liu¹  Wenan Chen²  Jiexun Wang²  Wen Wan²  Chuanyu Sun²  Guimin Gao²  Xi Gao³  Xiangning Chen⁴ 

[1] Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, 1665 University Boulevard, 35294, Birmingham, AL, USA;Department of Biostatistics, Virginia Commonwealth University School of Medicine, 830 East Main Street, One Capitol Square, 7th Floor, 23298-0032, Richmond, VA, USA;Department of Computer Science, Virginia Commonwealth University, PO Box 843019, 401 West Main Street, Room E4225, 23284-3019, Richmond, VA, USA;Departments of Psychiatry, Virginia Commonwealth University School of Medicine, 23298-0003, Richmond, VA, USA;

关键词: Rare Variant;    Permutation Procedure;    Genetic Analysis Workshop;    Nonsynonymous SNPs;    Genetic Score;   

DOI  :  10.1186/1753-6561-5-S9-S86

来源: Springer

【 摘 要 】

We evaluate four association tests for rare variants—the combined multivariate and collapsing (CMC) method, two weighted-sum methods, and a variable threshold method—by applying them to the simulated data sets of unrelated individuals in the Genetic Analysis Workshop 17 (GAW17) data. The family-wise error rate (FWER) and average power are used as criteria for evaluation. Our results show that when all nonsynonymous SNPs (rare variants and common variants) in a gene are jointly analyzed, the CMC method fails to control the FWER; when only rare variants (single-nucleotide polymorphisms with minor allele frequency less than 0.05) are analyzed, all four methods can control FWER well. All four methods have comparable power, which is low for the analysis of the GAW17 data sets. Three of the methods (not including the CMC method) involve estimation of p-values using permutation procedures that either can be computationally intensive or generate inflated FWERs. We adapt a fast permutation procedure into these three methods. The results show that using the fast permutation procedure can produce FWERs and average powers close to the values obtained from the standard permutation procedure on the GAW17 data sets. The standard permutation procedure is computationally intensive.

【 授权许可】

Unknown   
© Chen et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.