Statistics and Its Interface

Volume 17 (2024)

Number 1

Special issue in honor of Professor Lincheng Zhao

Robust and powerful gene-environment interaction tests using rare genetic variants in case-control studies

Pages: 51 – 62

DOI: https://dx.doi.org/10.4310/23-SII800

Authors

Yanan Zhao (Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China)

Hong Zhang (Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, China)

Abstract

Many association analysis methods have been developed to detect disease related rare genetic variants or gene-environment interactions. Most of them are based on prospectively likelihood, so they are robust but might not be powerful enough. On the other hand, retrospective likelihood based methods assuming gene-environment independence can effectively improve the association test power, but they suffer from type‑I error rate inflation if the independence assumption is violated. The aim of this paper is to develop novel test methods to balance power and robustness by appropriately weighting the above retrospective likelihood based tests and the existing prospective likelihood based tests. The desired finite sample performances of the proposed methods are demonstrated through simulation studies and the application to a real dataset.

Keywords

rare variant, retrospective likelihood, gene-environment interaction, case-control studies

2010 Mathematics Subject Classification

62F03, 62P10

Received 27 December 2022

Accepted 19 May 2023

Published 27 November 2023