Comparing the power of family-based association tests for sequence data with applications in the GAW18 simulated data

BMC Proceedings

Proceedings

Iuliana Ionita-Laza¹  Jing Huang²  Yong Chen²  Michael D Swartz² 

[1] Department of Biostatistics, Columbia University, Mailman School of Public Health, 10032, New York City, NY, USA;Division of Biostatistics, University of Texas School of Public Health, 77030, Houston, TX, USA;

关键词: Rare Variant;    Causal Variant;    Genetic Analysis Workshop;    Causal SNPs;    Generalize Linear Mixed Effect Model;   

DOI  :  10.1186/1753-6561-8-S1-S27

来源: Springer

【 摘 要 】

We apply a family-based extension of the sequence kernel association test (SKAT) to 93 trios extracted from the 20 pedigrees in the Genetic Analysis Workshop 18 simulated data. Each extracted trio includes a unique set of parents to ensure conditionally independent trios are sampled. We compare the empirical type I error and power between the family-based SKAT and the burden test under varying percentages of causal single-nucleotide polymorphisms included in the analysis. Our investigation using simulated data suggests that, under the setting used for Genetic Analysis Workshop 18 data, both the family-based SKAT and the burden test have limited power, and that there is no substantial impact of percentage of signal on the power of either test. The low power is partially a result of the small sample size. However, we find that both the family-based SKAT and the burden test are more powerful when we use only rare variants, rather than common variants, to test the association.

【 授权许可】

Unknown   
© Huang et al.; licensee BioMed Central Ltd. 2014. 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.