Robust Tests for Single-marker Analysis in Case-Control Genetic Association Studies

摘要

Choosing an appropriate single-marker association test is critical to the success of case-control genetic association studies. An ideal single-marker analysis should have robust performance across a wide range of potential disease risk models. MAX was designed specifically to achieve such robustness. In this work, we derived the power calculation formula for MAX and conducted a comprehensive power comparison between MAX and two other commonly used single-marker tests, the one-degree-of-freedom (1-df) Cochran-Armitage trend test and the 2-df Pearson Chi-squared test. We used a single-marker disease risk model and a two-marker haplotype risk model to explore the performances of the above three tests. We found that each test has its own “sweet” spots. Among the three tests considered, MAX appears to have the most robust performance.