ShinyGPA: An interactive visualization toolkit for investigating pleiotropic architecture using GWAS datasets.

Emma  Kortemeier; Paula S.  Ramos; Kelly J.  Hunt; Hang J.  Kim; Gary Hardiman; Dongjun  Chung

doi:10.1371/journal.pone.0190949

ShinyGPA: An interactive visualization toolkit for investigating pleiotropic architecture using GWAS datasets.

Emma Kortemeier, Paula S. Ramos, Kelly J. Hunt, Hang J. Kim, Gary Hardiman, Dongjun Chung

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Abstract

In spite of accumulating evidence suggesting that different complex traits share a common risk basis, namely pleiotropy, effective investigation of pleiotropic architecture still remains challenging. In order to address this challenge, we developed ShinyGPA, an interactive and dynamic visualization toolkit to investigate pleiotropic structure. ShinyGPA requires only the summary statistics from genome-wide association studies (GWAS), which reduces the burden on researchers using this tool. ShinyGPA allows users to effectively investigate genetic relationships among phenotypes using a flexible low-dimensional visualization and an intuitive user interface. In addition, ShinyGPA provides joint association mapping functionality that can facilitate biological understanding of the pleiotropic architecture. We analyzed GWAS summary statistics for 12 phenotypes using ShinyGPA and obtained visualization results and joint association mapping results that are well supported by the literature. The visualization produced by ShinyGPA can also be used as a hypothesis generating tool for relationships between phenotypes, which might also be used to improve the design of future genetic studies. ShinyGPA is currently available at https://dongjunchung.github.io/GPA/

Original language	English
Pages (from-to)	1-17
Journal	PLoS ONE
Volume	13
Issue number	1
DOIs	https://doi.org/10.1371/journal.pone.0190949
Publication status	Published - 08 Jan 2018

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10.1371/journal.pone.0190949Licence: CC BY

ShinyGPA: An interactive visualization toolkit for investigating pleiotropic architecture using GWAS datasets
Copyright 2018 the authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
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Cite this

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abstract = "In spite of accumulating evidence suggesting that different complex traits share a common risk basis, namely pleiotropy, effective investigation of pleiotropic architecture still remains challenging. In order to address this challenge, we developed ShinyGPA, an interactive and dynamic visualization toolkit to investigate pleiotropic structure. ShinyGPA requires only the summary statistics from genome-wide association studies (GWAS), which reduces the burden on researchers using this tool. ShinyGPA allows users to effectively investigate genetic relationships among phenotypes using a flexible low-dimensional visualization and an intuitive user interface. In addition, ShinyGPA provides joint association mapping functionality that can facilitate biological understanding of the pleiotropic architecture. We analyzed GWAS summary statistics for 12 phenotypes using ShinyGPA and obtained visualization results and joint association mapping results that are well supported by the literature. The visualization produced by ShinyGPA can also be used as a hypothesis generating tool for relationships between phenotypes, which might also be used to improve the design of future genetic studies. ShinyGPA is currently available at https://dongjunchung.github.io/GPA/",

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ShinyGPA: An interactive visualization toolkit for investigating pleiotropic architecture using GWAS datasets.

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