Gene-based Higher Criticism methods for large-scale exonic single-nucleotide polymorphism data

摘要

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.