A simple and accurate method to determine genomewide significance for association tests in sequencing studies
A simple and accurate method to determine genomewide significance for association tests in sequencing studies
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DOI：
10.1002/gepi.22183
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发表时间：
2019-06-01
影响因子：
2.1
通讯作者：
Lin, Dan-Yu
中科院分区：
文献类型：
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作者：
Lin, Dan-Yu
全外显子组测序（WES）和全基因组测序（WGS）研究正在进行中，以研究遗传变异对复杂疾病和性状的影响。通常对常见变异进行单变异关联检验，对罕见变异进行基于区域的关联检验。后者可以靶向具有相似或相反效应的变体，询问具有不同频率或不同功能注释的变体，并检查各种区域。执行的大量测试需要针对多个测试进行调整。传统的Bonferroni校正过于保守，因为检验统计量是相关的。为了应对这一挑战，我们提出了一种简单而准确的方法，基于参数引导来评估全基因组的意义。我们表明，检验统计量的相关性主要由基因型决定，因此可以在共享共同测序平台的不同研究中使用相同的显著性阈值。我们证明了所提出的方法与WES数据从国家心脏，肺，血液研究所外显子组测序项目和WGS数据从1000个基因组计划的有用性。我们建议将5x 10 -9的p值作为检测人类基因组中所有常见和低频变异（MAF>= 0.1%）的全基因组显著性阈值。
Whole-exome sequencing (WES) and whole-genome sequencing (WGS) studies are underway to investigate the impact of genetic variants on complex diseases and traits. It is customary to perform single-variant association tests for common variants and region-based association tests for rare variants. The latter may target variants with similar or opposite effects, interrogate variants with different frequencies or different functional annotations, and examine a variety of regions. The large number of tests that are performed necessitates adjustment for multiple testing. The conventional Bonferroni correction is overly conservative as the test statistics are correlated. To address this challenge, we propose a simple and accurate method based on parametric bootstrap to assess genomewide significance. We show that the correlations of the test statistics are determined primarily by the genotypes, such that the same significance threshold can be used in different studies that share a common sequencing platform. We demonstrate the usefulness of the proposed method with WES data from the National Heart, Lung, and Blood Institute Exome Sequencing Project and WGS data from the 1000 Genomes Project. We recommend the p value of 5x10-9 as the genomewide significance threshold for testing all common and low-frequency variants (MAFs >= 0.1%) in the human genome.