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 truncation (ART) method that retains main characteristics of the RTP but is substantially simpler to implement. ART leads to an efficient form of the adaptive algorithm, an approach where the number of top ranking SNPs is varied to optimize power. We illustrate our methods by strengthening previously reported associations of μ-opioid receptor variants with sensitivity to pain.
|Journal||Frontiers in Genetics|
|State||Published - Nov 20 2019|
Bibliographical noteFunding Information:
This research was supported in part by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences.
© Copyright © 2019 Vsevolozhskaya, Hu and Zaykin.
- a rank truncated product RTP
- adaptive augmented rank truncation
- augmented rank truncation
- combining evidence
- rank truncated product
ASJC Scopus subject areas
- Molecular Medicine