Gene-based genetic association test with adaptive optimal weights
Gene-based genetic association test with adaptive optimal weights
复制标题
具有自适应最佳权重的基于基因的遗传关联测试
DOI：
10.1002/gepi.22098
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发表时间：
2018-02-01
影响因子：
2.1
通讯作者：
Wang, Kai
中科院分区：
文献类型：
--
作者：
Chen, Zhongxue;Lu, Yan;Wang, Kai
众所周知，为遗传变异使用适当的权重对于增强基于基因或路径的关联测试的能力至关重要。为了提高功率，我们提出了一种通用的方法，自适应地选择一类权重家庭之间的权重，并将其应用到流行的排序核关联测试。通过全面的仿真研究，我们证明了所提出的方法可以大大提高功率在某些条件下。应用到真实的数据。该方法可以推广到目前所有基于集合的稀有变异关联测试，其性能依赖于变异的权重分配。
It is well known that using proper weights for genetic variants is crucial in enhancing the power of gene- or pathway-based association tests. To increase the power, we propose a general approach that adaptively selects weights among a class of weight families and apply it to the popular sequencing kernel association test. Through comprehensive simulation studies, we demonstrate that the proposed method can substantially increase power under some conditions. Applications to real data are also presented. This general approach can be extended to all current set-based rare variant association tests whose performances depend on variant's weight assignment.