基因组学中的家族错误率是否受到基于有效独立测试数量的方法的控制？
Is the familywise error rate in genomics controlled by methods based on the effective number of independent tests?
摘要：
在全基因组关联（GWA）研究中，目标是检测一个或多个遗传标记与给定表型之间的关联。在GWA研究中遗传标记的数量可以是数十万的量级，因此需要多重检验方法。本文介绍了一套流行的方法，用于纠正多重检验在GWA研究。所有这些都是基于估计独立测试的有效数量的概念。我们比较这些方法使用模拟数据和TOP研究的数据，并表明，独立测试的有效数量是不加性的独立遗传标记的块，除非我们假设一个共同的本地显着性水平的值。我们还表明，审查的方法的基础上估计的有效数量的独立测试一般不控制familywise错误率。
英文摘要：
In genome-wide association (GWA) studies the goal is to detect association between one or more genetic markers and a given phenotype. The number of genetic markers in a GWA study can be in the order hundreds of thousands and therefore multiple testing methods are needed. This paper presents a set of popular methods to be used to correct for multiple testing in GWA studies. All are based on the concept of estimating an effective number of independent tests. We compare these methods using simulated data and data from the TOP study, and show that the effective number of independent tests is not additive over blocks of independent genetic markers unless we assume a common value for the local significance level. We also show that the reviewed methods based on estimating the effective number of independent tests in general do not control the familywise error rate.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
