Original Research ARTICLE
Detecting weak signals by combining small P-values in genetic association studies
- 1University of Kentucky, United States
- 2National Institute of Environmental Health Sciences (NIEHS), United States
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 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, 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 mu-opioid receptor variants with sensitivity to pain.
Keywords: combining evidence, RTP, adaptive RTP, Art, adaptive ART
Received: 01 Jul 2019;
Accepted: 30 Sep 2019.
Copyright: © 2019 Vsevolozhskaya, Hu and Zaykin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Dmitri V. Zaykin, National Institute of Environmental Health Sciences (NIEHS), Durham, 27709, North Carolina, United States, firstname.lastname@example.org