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A Rare Variant Association Test Based on Combinations of Single-Variant Tests

机译:基于单变量检验组合的稀有变异关联检验

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摘要

Next generation sequencing technologies make directly testing rare variant associations possible. However, the development of powerful statistical methods for rare variant association studies is still underway. Most of existing methods are burden and quadratic tests. Recent studies show that the performance of each of burden and quadratic tests depends strongly upon the underlying assumption and no test demonstrates consistently acceptable power. Thus, combined tests by combining information from the burden and quadratic tests have been proposed recently. However, results from recent studies (including this study) show that there exist tests that can outperform both burden and quadratic tests. In this article, we propose three classes of tests that include tests outperforming both burden and quadratic tests. Then, we propose the optimal combination of single-variant tests (OCST) by combining information from tests of the three classes. We use extensive simulation studies to compare the performance of OCST with that of burden, quadratic and optimal single-variant tests. Our results show that OCST either is the most powerful test or has similar power with the most powerful test. We also compare the performance of OCST with that of the two existing combined tests. Our results show that OCST has better power than the two combined tests.
机译:下一代测序技术使直接测试稀有变异关联成为可能。但是,针对稀有变异关联研究的有效统计方法的开发仍在进行中。现有的大多数方法是负担和二次检验。最近的研究表明,负担测试和二次测试的性能在很大程度上取决于基本假设,没有一项测试能够证明其始终具有可接受的功效。因此,最近提出了通过组合来自负担的信息和二次检验的组合检验。但是,最近的研究(包括本研究)的结果表明,存在的测试可以胜过负担测试和二次测试。在本文中,我们提出了三类测试,其中包括胜过负担测试和二次测试的测试。然后,我们通过结合来自三类测试的信息,提出了单变量测试(OCST)的最佳组合。我们使用大量的模拟研究来比较OCST的性能与负担,二次方和最优单变量测试的性能。我们的结果表明,OCST是功能最强大的测试,或者具有与功能最强大的测试相似的功能。我们还将OCST的性能与两个现有组合测试的性能进行了比较。我们的结果表明,OCST具有比两个组合测试更好的功能。

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