Despite the extensive discovery of trait- and disease-associated common variants, much of the genetic contribution to complex traits remains unexplained. Rare variants can explain additional disease risk or trait variability. An increasing number of studies are underway to identify trait- and disease-associated rare variants. In this review, we provide an overview of statistical issues in rare-variant association studies with a focus on study designs and statistical tests. We present the design and analysis pipeline of rare-variant studies and review cost-effective sequencing designs and genotyping platforms. We compare various gene- or region-based association tests, including burden tests, variance-component tests, and combined omnibus tests, in terms of their assumptions and performance. Also discussed are the related topics of meta-analysis, population-stratification adjustment, genotype imputation, follow-up studies, and heritability due to rare variants. We provide guidelines for analysis and discuss some of the challenges inherent in these studies and future research directions.

中文翻译：

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稀有变异关联分析：研究设计和统计检验。

尽管广泛发现了性状和疾病相关的常见变异，但对复杂性状的大部分遗传贡献仍然无法解释。罕见的变异可以解释额外的疾病风险或性状变异。越来越多的研究正在进行中，以确定与性状和疾病相关的罕见变异。在这篇综述中，我们概述了罕见变异关联研究中的统计问题，重点是研究设计和统计检验。我们介绍了稀有变异研究的设计和分析流程，并审查了具有成本效益的测序设计和基因分型平台。我们在假设和性能方面比较了各种基于基因或区域的关联测试，包括负担测试、方差分量测试和组合综合测试。还讨论了荟萃分析的相关主题，人口分层调整、基因型插补、后续研究和由于罕见变异引起的遗传力。我们提供分析指南并讨论这些研究和未来研究方向中固有的一些挑战。