## Abstract For a dense set of genetic markers such as single nucleotide polymorphisms (SNPs) on high linkage disequilibrium within a small candidate region, a haplotype‐based approach for testing association between a disease phenotype and the set of markers is attractive in reducing the data comp
Power estimation of multiple SNP association test of case-control study and application
✍ Scribed by Ke Hao; Xin Xu; Nan Laird; Xiaobin Wang; Xiping Xu
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 115 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
At the current stage, a large number of single nucleotide polymorphisms (SNPs) have been deployed in searching for genes underlying complex diseases. A powerful method is desirable for efficient analysis of SNP data. Recently, a novel method for multiple SNP association test using a combination of allelic association (AA) and Hardy‐Weinberg disequilibrium (HWD) has been proposed. However, the power of this test has not been systematically examined. In this study, we conducted a simulation study to further evaluate the statistical power of the new procedure, as well as of the influence of the HWD on its performance. The simulation examined the scenarios of multiple disease SNPs among a candidate pool, assuming different parameters including allele frequencies and risk ratios, dominant, additive, and recessive genetic models, and the existence of gene‐gene interactions and linkage disequilibrium (LD). We also evaluated the performance of this test in capturing real disease associated SNPs, when a significant global P value is detected. Our results suggest that this new procedure is more powerful than conventional single‐point analyses with correction of multiple testing. However, inclusion of HWD reduces the power under most circumstances. We applied the novel association test procedure to a case‐control study of preterm delivery (PTD), examining the effects of 96 candidate gene SNPs concurrently, and detected a global P value of 0.0250 by using Cochran‐Armitage χ^2^s as “starting” statistics in the procedure. In the following single point analysis, SNPs on IL1RN, IL1R2, ESR1, Factor 5, and OPRM1 genes were identified as possible risk factors in PTD. Genet Epidemiol 26:22–30, 2004. © 2003 Wiley‐Liss, Inc.
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