title: A powerful and robust test in genetic association studies.
abstract: There are several well-known single SNP tests presented in the literature for detecting gene-disease association signals. Having in place an efficient and robust testing process across all genetic models would allow a more comprehensive approach to analysis. Although some studies have shown that it is possible to construct such a test when the variants are common and the genetic model satisfies certain conditions, the model conditions are too restrictive and in general difficult to verify. In this paper, we propose a powerful and robust test without assuming any model restrictions. Our test is based on the selected 2 × 2 tables derived from the usual 2 × 3 table. By signals from these tables, we show through simulations across a wide range of allele frequencies and genetic models that this approach may produce a test which is almost uniformly most powerful in the analysis of low- and high-frequency variants. Two cancer studies are used to demonstrate applications of the proposed test.
authors: Biostatistics Center and School of Public Health, Taipei Medical University, Taipei, Taiwan, ROC.
authors: Kuang-Fu
authors: KF
authors: Cheng
authors: Jen-Yu
authors: JY
authors: Lee
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005260:Female; D005787:Gene Frequency; D056726:Genetic Association Studies / Q000379:methods*; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D014644:Genetic Variation; D005838:Genotype; D006801:Humans; D008297:Male; D008957:Models, Genetic; D010051:Ovarian Neoplasms / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D011471:Prostatic Neoplasms / Q000235:genetics; D015203:Reproducibility of Results