A genetic association test through combining two independent tests

Genomics
Zhongxue ChenKai Wang

Abstract

Gene- and pathway-based variant association tests are important tools in finding genetic variants that are associated with phenotypes of interest. Although some methods have been proposed in the literature, powerful and robust statistical tests are still desirable in this area. In this study, we propose a statistical test based on decomposing the genotype data into orthogonal parts from which powerful and robust independent p-value combination approaches can be utilized. Through a comprehensive simulation study, we compare the proposed test with some existing popular ones. Our simulation results show that the new test has great performance in terms of controlling type I error rate and statistical power. Real data applications are also conducted to illustrate the performance and usefulness of the proposed test.

References

Nov 16, 2007·Biostatistics·Gang Zheng, Hon Keung Tony Ng
Mar 17, 2011·PLoS Genetics·Benjamin M NealeMark J Daly
Jul 9, 2011·American Journal of Human Genetics·Michael C WuXihong Lin
Jan 4, 2012·Human Heredity·Zhongxue Chen, Hon Keung Tony Ng
Jun 16, 2012·Biostatistics·Seunggeun LeeXihong Lin
Feb 5, 2013·Statistical Methods in Medical Research·Zhongxue ChenHon Keung Tony Ng
Apr 22, 2014·American Journal of Human Genetics·Hugues AschardPeter Kraft
May 17, 2014·Genetics·Wei PanPeng Wei
Sep 26, 2014·Statistical Methods in Medical Research·Zhongxue ChenHanwen Huang
Sep 24, 2015·Biometrics·Zhongxue ChenPeihua Qiu
Jul 5, 2017·Statistical Applications in Genetics and Molecular Biology·Zhongxue ChenKai Wang
Nov 28, 2017·Genetic Epidemiology·Zhongxue ChenKai Wang

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Citations

Oct 26, 2021·Journal of Parkinson's Disease·Yuri L SoseroZiv Gan-Or

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