Testing Rare-Variant Association without Calling Genotypes Allows for Systematic Differences in Sequencing between Cases and Controls
Testing Rare-Variant Association without Calling Genotypes Allows for Systematic Differences in Sequencing between Cases and Controls
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DOI：
10.1371/journal.pgen.1006040
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发表时间：
2016-05-01
期刊：
影响因子：
4.5
通讯作者：
Satten, Glen A.
中科院分区：
文献类型：
--
作者：
Hu, Yi-Juan;Liao, Peizhou;Satten, Glen A.
下一代DNA测序为发现与复杂疾病和特征相关的罕见遗传变异提供了前所未有的机会。然而，首先调用潜在基因型，然后将调用值作为已知值处理的常见做法容易产生假阳性结果，特别是当病例和对照之间的基因型错误系统不同时。每当在不同深度、不同平台或不同批次上对案例和控件进行排序时，都会发生这种情况。在这篇文章中，我们提供了一种基于可能性的方法来测试罕见的变异关联，该方法直接模拟测序读取，而不需要调用基因型。我们考虑（加权）负担检验统计量，这是（加权）分数统计量的总和，用于评估个体变异对感兴趣性状的影响。由于变异位点是未知的，我们开发了一个简单的，计算效率高的筛选算法来估计变异位点。因为我们的负担统计在筛选后可能没有平均零，我们开发了一种新的自举程序来评估负担统计的重要性。我们通过广泛的模拟研究证明，所提出的测试对于病例和对照之间的广泛差异测序质量是稳健的，并且当后者控制I型错误时，至少与标准基因型调用方法一样强大。对UK10K数据的一项应用揭示了与儿童期发病肥胖相关的BTBD18基因的新型罕见变异。相关软件是免费提供的。
Next-generation sequencing of DNA provides an unprecedented opportunity to discover rare genetic variants associated with complex diseases and traits. However, the common practice of first calling underlying genotypes and then treating the called values as known is prone to false positive findings, especially when genotyping errors are systematically different between cases and controls. This happens whenever cases and controls are sequenced at different depths, on different platforms, or in different batches. In this article, we provide a likelihood-based approach to testing rare variant associations that directly models sequencing reads without calling genotypes. We consider the (weighted) burden test statistic, which is the (weighted) sum of the score statistic for assessing effects of individual variants on the trait of interest. Because variant locations are unknown, we develop a simple, computationally efficient screening algorithm to estimate the loci that are variants. Because our burden statistic may not have mean zero after screening, we develop a novel bootstrap procedure for assessing the significance of the burden statistic. We demonstrate through extensive simulation studies that the proposed tests are robust to a wide range of differential sequencing qualities between cases and controls, and are at least as powerful as the standard genotype calling approach when the latter controls type I error. An application to the UK10K data reveals novel rare variants in gene BTBD18 associated with childhood onset obesity. The relevant software is freely available.