ForestPMPlot: A Flexible Tool for Visualizing Heterogeneity Between Studies in Meta-analysis
Eun Yong Kang, Yurang Park, Xiao Li and 3 more
G3: Genes, Genomes, Genetics · 2016
doi:10.1534/g3.116.029439 (opens in a new tab)
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Abstract
Meta-analysis has become a popular tool for genetic association studies to combine different genetic studies. A key challenge in meta-analysis is heterogeneity, or the differences in effect sizes between studies. Heterogeneity complicates the interpretation of meta-analyses. In this paper, we describe ForestPMPlot, a flexible visualization tool for analyzing studies included in a meta-analysis. The main feature of the tool is visualizing the differences in the effect sizes of the studies to understand why the studies exhibit heterogeneity for a particular phenotype and locus pair under different conditions. We show the application of this tool to interpret a meta-analysis of 17 mouse studies, and to interpret a multi-tissue eQTL study.
Abstract licence: CC BY
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