一种用于病例对照关联研究的基于MAF中性等位基因的强有力检验
A powerful MAF-neutral allele-based test for case-control association studies
摘要：
在旨在定位感兴趣疾病的常染色体疾病变体的病例对照研究中，通常通过比较病例和对照之间的标记次要等位基因频率（MAF）来测试标记与疾病状态之间的关联。对于大多数常见的基于等位基因的测试，统计功效高度依赖于这些MAF的实际值，其中与具有高MAF的相关标志物相比，具有低MAF的相关标志物具有更低的检测功效。因此，主要基于其p值选择用于后续研究的标记物的流行策略可能优先选择具有高MAF的标记物。我们提出了一种新的测试，它不支持标记物与高MAF，并提高了权力的标记物与低至中度的MAF，而不牺牲性能的标记物与高MAF，因此在这方面优于大多数现有的测试。从理论上推导出了该检验的渐近幂函数的显式公式，从而可以快速简便地计算相应的p值。在渐近和有限样本量的设置与现有的几个测试的性能进行了比较。
英文摘要：
In a case-control study aimed at locating autosomal disease variants for a disease of interest, association between markers and the disease status is often tested by comparing the marker minor allele frequencies (MAFs) between cases and controls. For most common allele-based tests the statistical power is highly dependent on the actual values of these MAFs, where associated markers with low MAFs have less power to be detected compared to associated markers with high MAFs. Therefore, the popular strategy of selecting markers for follow-up studies based primarily on their p-values is likely to preferentially select markers with high MAFs. We propose a new test which does not favor markers with high MAFs and improves the power for markers with low to moderate MAFs without sacrificing performance for markers with high MAFs and is therefore superior to most existing tests in this regard. An explicit formula for the asymptotic power function of the proposed test is derived theoretically, which allows for fast and easy computation of the corresponding p-values. The performance of the proposed test is compared with several existing tests both in the asymptotic and the finite sample size settings.
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