Evaluation of pooled association tests for rare variant identification.
Evaluation of pooled association tests for rare variant identification.
复制标题
DOI：
10.1186/1753-6561-5-s9-s118
复制
发表时间：
2011-11-29
期刊：
影响因子：
--
通讯作者：
Liu N
中科院分区：
文献类型：
--
作者：
Lin WY;Zhang B;Yi N;Gao G;Liu N
全基因组关联研究已经成功地确定了许多与复杂人类疾病相关的常见变异。然而，大部分剩余的遗传力不能用这些常见的变异来解释。探索与疾病相关的罕见变异现在引起了更多的关注。最近已经提出了几种方法来鉴定罕见的变异。其中，固定阈值、加权和可变阈值方法有效地将多个变体的信息组合到一个功能单元中;这些方法是常用的。我们评估这三种方法的性能。基于我们对遗传分析研讨会17数据的分析，我们发现没有一种方法普遍优于其他方法。此外，调整潜在协变量不仅可以增加真阳性比例，还可以减少假阳性比例。我们的研究得出结论，在我们比较的三种方法（固定阈值，加权和和可变阈值方法）中没有统一的最强大的测试，它们的性能取决于疾病的潜在遗传结构。
Genome-wide association studies have successfully identified many common variants associated with complex human diseases. However, a large portion of the remaining heritability cannot be explained by these common variants. Exploring rare variants associated with diseases is now catching more attention. Several methods have been recently proposed for identification of rare variants. Among them, the fixed-threshold, weighted-sum, and variable-threshold methods are effective in combining the information of multiple variants into a functional unit; these approaches are commonly used. We evaluate the performance of these three methods. Based on our analyses of the Genetic Analysis Workshop 17 data, we find that no method is universally better than the others. Furthermore, adjusting for potential covariates can not only increase the true-positive proportions but also reduce the false-positive proportions. Our study concludes that there is no uniformly most powerful test among the three methods we compared (the fixed-threshold, weighted-sum, and variable-threshold methods), and their performances depend on the underlying genetic architecture of a disease.