Cargando…

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

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 descri...

Descripción completa

Detalles Bibliográficos
Autores principales: Kang, Eun Yong, Park, Yurang, Li, Xiao, Segrè, Ayellet V., Han, Buhm, Eskin, Eleazar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4938634/
https://www.ncbi.nlm.nih.gov/pubmed/27194809
http://dx.doi.org/10.1534/g3.116.029439
Descripción
Sumario: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.