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ShinyGPA: An interactive visualization toolkit for investigating pleiotropic architecture using GWAS datasets.
Emma Kortemeier1, Paula S Ramos1,2, Kelly J Hunt1
1Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425, United States of America.
Plos One
|January 9, 2018
Summary
ShinyGPA is a new toolkit that helps researchers investigate pleiotropic architecture, which is the genetic basis shared across complex traits. This tool simplifies the analysis of genome-wide association studies (GWAS) summary statistics for better understanding of genetic relationships.
Area of Science:
- Genetics and Bioinformatics
- Complex Trait Analysis
- Statistical Genomics
Background:
- Growing evidence indicates shared genetic risk factors (pleiotropy) underlie diverse complex traits.
- Investigating the pleiotropic architecture of complex traits remains a significant challenge in genetic research.
Purpose of the Study:
- To develop an interactive visualization toolkit, ShinyGPA, for exploring pleiotropic structures.
- To facilitate the investigation of genetic relationships among multiple phenotypes using summary statistics.
Main Methods:
- Developed ShinyGPA, a dynamic and interactive visualization toolkit.
- Utilized summary statistics from genome-wide association studies (GWAS) as input.
- Incorporated flexible low-dimensional visualization and joint association mapping functionalities.
Main Results:
- Analyzed GWAS summary statistics for 12 phenotypes using ShinyGPA.
- Generated visualization and joint association mapping results consistent with existing literature.
- Demonstrated ShinyGPA's utility in understanding pleiotropic architecture and generating novel hypotheses.
Conclusions:
- ShinyGPA effectively addresses the challenge of investigating pleiotropic architecture.
- The toolkit simplifies genetic relationship analysis and enhances biological understanding of complex traits.
- ShinyGPA serves as a valuable tool for hypothesis generation and future genetic study design.
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