In this article, we propose a novel test via combining the maximum and minimum values among a large number of dependent Z‐scores for testing the hypothesis with sparse signals. The proposed test employs the information about different signs of maximum and minimum Z‐scores and thus power is gained. Its asymptotic null distribution is derived under the null hypothesis and some regular conditions. Extensive simulation studies are conducted to show the advantages of the proposed test by comparing with two existing ones. A real application to the lipids genome wide association study further shows its performances.

中文翻译：

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结合大量依赖Z评分中的最大值和最小值的新颖测试，并应用于基因组范围的关联研究

在本文中，我们提出了一种新颖的测试方法，该方法通过组合大量依赖Z评分中的最大值和最小值来测试具有稀疏信号的假设。建议的测试使用有关最大Z分数和最小Z分数的不同符号的信息，从而获得功率。它的渐近零分布是在零假设和一些常规条件下得出的。进行了广泛的仿真研究，通过与两个现有的比较来显示所提出的测试的优点。在脂质全基因组关联研究中的实际应用进一步证明了其性能。