Journal article
A genetic association test through combining two independent tests
Genomics (San Diego, Calif.), Vol.111(5), pp.1152-1159
09/2019
DOI: 10.1016/j.ygeno.2018.07.010
PMID: 30009923
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.
Details
- Title: Subtitle
- A genetic association test through combining two independent tests
- Creators
- Zhongxue Chen - Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E. 7th street, Bloomington, IN 47405, USAQingzhong Liu - Department of Computer Science, Sam Houston State University, 1803 Avenue I, Huntsville, TX 77341, USAKai Wang - Department of Biostatistics, College of Public Health, University of Iowa, 145 N. Riverside Drive, Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- Genomics (San Diego, Calif.), Vol.111(5), pp.1152-1159
- DOI
- 10.1016/j.ygeno.2018.07.010
- PMID
- 30009923
- NLM abbreviation
- Genomics
- ISSN
- 0888-7543
- eISSN
- 1089-8646
- Publisher
- Elsevier Inc
- Language
- English
- Date published
- 09/2019
- Academic Unit
- Biostatistics
- Record Identifier
- 9984213371302771
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