A Geometric Framework for Evaluating Rare Variant Tests of Association
A Geometric Framework for Evaluating Rare Variant Tests of Association
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DOI：
10.1002/gepi.21722
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发表时间：
2013-05-01
影响因子：
2.1
通讯作者：
Tintle, Nathan L.
中科院分区：
文献类型：
--
作者：
Liu, Keli;Fast, Shannon;Tintle, Nathan L.
下一代测序数据的浪潮已经到来。然而，关于如何最好地分析序列数据，特别是罕见遗传变异对人类疾病的贡献，仍然存在许多问题。已经提出了许多统计方法来聚合多个罕见变异位点之间的关联信号，以提高统计功效;然而，测试之间的精确关系往往没有得到很好的理解。我们提出了一个几何表示罕见的变异数据，其中罕见的等位基因计数的情况下，对照样本被视为向量在欧几里得空间。几何框架有利于严格分类现有的罕见变异测试分为两大类：测试的情况下，控制向量的长度的差异，以及联合测试的长度或角度的差异，这两个向量。我们证明了一个性状的遗传结构，包括风险等位基因的数量和频率，直接关系到长度和联合测试的行为。因此，几何框架允许预测哪些测试在不同的疾病模型下表现最好。此外，几何框架的结构立即表明了其他类别和类型的罕见变异测试。我们考虑两个一般类的测试，显示出鲁棒性的非因果和保护性的变种。几何框架介绍了一种新的和独特的方法来评估当前的罕见变异的方法，并提供了应用和理论研究人员的指导方针。
The wave of next-generation sequencing data has arrived. However, many questions still remain about how to best analyze sequence data, particularly the contribution of rare genetic variants to human disease. Numerous statistical methods have been proposed to aggregate association signals across multiple rare variant sites in an effort to increase statistical power; however, the precise relation between the tests is often not well understood. We present a geometric representation for rare variant data in which rare allele counts in case and control samples are treated as vectors in Euclidean space. The geometric framework facilitates a rigorous classification of existing rare variant tests into two broad categories: tests for a difference in the lengths of the case and control vectors, and joint tests for a difference in either the lengths or angles of the two vectors. We demonstrate that genetic architecture of a trait, including the number and frequency of risk alleles, directly relates to the behavior of the length and joint tests. Hence, the geometric framework allows prediction of which tests will perform best under different disease models. Furthermore, the structure of the geometric framework immediately suggests additional classes and types of rare variant tests. We consider two general classes of tests which show robustness to noncausal and protective variants. The geometric framework introduces a novel and unique method to assess current rare variant methodology and provides guidelines for both applied and theoretical researchers.