ForestPMPlot: A Flexible Tool for Visualizing Heterogeneity Between Studies in Meta-analysis

被引：26

作者：

Kang, Eun Yong ^{[1
]}

Park, Yurang ^{[3
]}

Li, Xiao ^{[6
]}

Segre, Ayellet V. ^{[6
]}

Han, Buhm ^{[4
,5
]}

Eskin, Eleazar ^{[1
,2
]}

机构：

[1] Univ Calif Los Angeles, Dept Comp Sci, Los Angeles, CA 90095 USA

[2] Univ Calif Los Angeles, Dept Human Genet, 3532-J Boelter Hall, Los Angeles, CA 90095 USA

[3] Univ Ulsan, Coll Med, Dept Biomed Informat, Seoul 05505, South Korea

[4] Univ Ulsan, Coll Med, Dept Convergence Med, Seoul 05505, South Korea

[5] Asan Med Ctr, Asan Inst Life Sci, 88 Olymp Ro 43 Gil, Seoul 05505, South Korea

[6] Broad Inst Massachusetts Inst Technol & Harvard U, Cambridge, MA 02142 USA

来源：

G3-GENES GENOMES GENETICS | 2016年 / 6卷 / 07期

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

GWAS; genetic association studies; heterogeneity; meta-analysis; TRANSGENIC MICE; LOCI; SUSCEPTIBILITY; INSULIN; TRAITS; GENE;

D O I：

10.1534/g3.116.029439

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

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.

引用

页码：1793 / 1798

页数：6

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