Detecting Weak Signals by Combining Small P-Values in Genetic Association Studies.

ABSTRACT: We approach the problem of combining top-ranking association statistics or P-values from a new perspective which leads to a remarkably simple and powerful method. Statistical methods, such as the rank truncated product (RTP), have been developed for combining top-ranking associations, and this general strategy proved to be useful in applications for detecting combined effects of multiple disease components. To increase power, these methods aggregate signals across top ranking single nucleotide polymorphisms (SNPs), while adjusting for their total number assessed in a study. Analytic expressions for combined top statistics or P-values tend to be unwieldy, which complicates interpretation and practical implementation and hinders further developments. Here, we propose the augmented rank trunc

SUBMITTER: Vsevolozhskaya OA 

PROVIDER: S-EPMC6879667 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature