Genomics Inform.  2016 Dec;14(4):173-180. 10.5808/GI.2016.14.4.173.

Comparison of Two Meta-Analysis Methods: Inverse-Variance-Weighted Average and Weighted Sum of Z-Scores

Affiliations
  • 1Asan Institute for Life Sciences, Asan Medical Center, Seoul 05505, Korea. buhm.han@amc.seoul.kr
  • 2Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul 05505, Korea.
  • 3School of Systems Biomedical Science, Soongsil University, Seoul 06978, Korea.
  • 4Department of Medicine, University of Ulsan College of Medicine, Seoul 05505, Korea.

Abstract

The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.

Keyword

fixed effects model; genome-wide association study; inverse variance-weighted average; meta-analysis; optimality; weighted sum of z-scores
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