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ProxECAT: Proxy External Controls Association Test. A new case-control gene region association test using allele frequencies from public controls

机译:ProxECAT:代理外部控件关联测试。一种新的病例对照基因区域关联测试使用来自公共对照的等位基因频率

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摘要

A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis.
机译:最近对测序的投资的主要目标是检测健康和疾病中的新型遗传关联,从而改善治疗方法的发展并在精密医学中发挥关键作用。尽管这项投资已导致数量巨大的测序基因组总数,但对复杂性状和疾病的单独研究通常规模较小,并且不足以检测稀有变异基因关联。现有的遗传资源,例如外显子组聚集协会(> 60,000个外显子组)和基因组聚集数据库(〜140,000个测序样品),有可能在这些研究中用作对照。充分利用这些和其他现有测序资源可能会增加功能,并且在对其他样本进行测序的资源有限的研究中可能特别有用。但是,迄今为止,这些巨大的,可公开获得的遗传资源仍未得到充分利用,甚至被滥用,这在很大程度上是由于缺乏可适当使用此汇总级别数据的统计方法。在这里,我们提出了一种在案例控制分析中纳入外部控制的新方法,称为ProxECAT(代理外部控制关联测试)。 ProxECAT使用内部测序的病例和外部对照来估计基因区域内稀有变异的富集。我们使用低深度覆盖(7x)全基因组测序对照和ExAC作为对照,在肥胖病例的模拟和实证分析中评估了ProxECAT。我们发现,随着外部控件数量的增加,ProxECAT可以保持预期的I型错误率,并具有更高的功耗。借助随附的R包,ProxECAT可以在病例对照分析中使用公共等位基因频率作为外部对照。

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