Gene-based Higher Criticism methods for large-scale exonic single-nucleotide polymorphism data.
Gene-based Higher Criticism methods for large-scale exonic single-nucleotide polymorphism data.
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DOI：
10.1186/1753-6561-5-s9-s65
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发表时间：
2011-11-29
期刊：
影响因子：
--
通讯作者：
Wu, Zheyang
中科院分区：
文献类型：
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作者：
He, Shiquan;Wu, Zheyang
在全基因组关联研究中，基于基因的方法测量基因内位点的潜在联合遗传效应，并有望检测致病性遗传变异。根据最近的统计多假设检验的理论研究，我们建议适应更高的批评程序开发新的基于基因的方法，使用连锁不平衡的信息来检测弱和稀疏的遗传信号。与大规模的外显子单核苷酸多态性数据从遗传分析研讨会17，我们表明，新的更高的批评型基因为基础的方法有更高的统计功率检测致病基因比最小P值的方法，岭回归，和原型的更高的批评。
In genome-wide association studies, gene-based methods measure potential joint genetic effects of loci within genes and are promising for detecting causative genetic variations. Following recent theoretical research in statistical multiple-hypothesis testing, we propose to adapt the Higher Criticism procedures to develop novel gene-based methods that use the information of linkage disequilibrium for detecting weak and sparse genetic signals. With the large-scale exonic single-nucleotide polymorphism data from Genetic Analysis Workshop 17, we show that the new Higher-Criticism-type gene-based methods have higher statistical power to detect causative genes than the minimal P-value method, ridge regression, and the prototypes of Higher Criticism do.