title: ForestPMPlot: A Flexible Tool for Visualizing Heterogeneity Between Studies in Meta-analysis.
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.
authors.affiliation: Department of Computer Science, University of California, Los Angeles, California 90095.
authors.forename: Eun Yong
authors.initials: EY
authors.lastname: Kang
authors.affiliation: Department of Biomedical Informatics and.
authors.forename: Yurang
authors.initials: Y
authors.lastname: Park
authors.affiliation: Department of Convergence Medicine, University of Ulsan College of Medicine & Asan Institute for Life Sciences, Asan Medical Center, Seoul, 05505 Republic of Korea, 05.
authors.forename: Xiao
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Convergence Medicine, University of Ulsan College of Medicine & Asan Institute for Life Sciences, Asan Medical Center, Seoul, 05505 Republic of Korea, 05.
authors.forename: Ayellet V
authors.initials: AV
authors.lastname: Segrè
authors.affiliation: Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea buhm.han@amc.seoul.kr eeskin@cs.ucla.edu.
authors.forename: Buhm
authors.initials: B
authors.lastname: Han
authors.affiliation: Department of Computer Science, University of California, Los Angeles, California 90095 Department of Human Genetics, University of California, Los Angeles, California 90095 buhm.han@amc.seoul.kr eeskin@cs.ucla.edu.
authors.forename: Eleazar
authors.initials: E
authors.lastname: Eskin
mesh_terms: D000818:Animals; D003196:Computer Graphics; D018740:Genetic Heterogeneity; D006801:Humans; D015201:Meta-Analysis as Topic; D051379:Mice; D015233:Models, Statistical; D010641:Phenotype; D040641:Quantitative Trait Loci; D018401:Sample Size; D015983:Selection Bias; D012984:Software
keywords: GWAS; genetic association studies; heterogeneity; meta-analysis