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GPA (Genetic analysis incorporating Pleiotropy and Annotation) is a tool for the prioritization of genome-wide association studies (GWAS) results using pleiotropy information and annotation data. The GPA algorithm has functions for fitting models and hypothesis testing the associated SNPs.


Genomics; Genetics; GWAS study


  • Operation: Statistical calculation; Visualisation
  • Software interface: Library
  • Language: R;C++
  • Operating system: Linux; Mac OS X; Microsoft Windows
  • License: GNU General Public License v>=2
  • Cost: Free
  • Version name: 1.1-0
  • Maturity: Stable
  • Credit: The National Institutes of Health (NIH), the VA Cooperative Studies Program of the Department of Veterans Affairs, Office of Research and Development.
  • Contact: Dongjun Chung chungd _at_
  • Collection: -


Chung D, Yang C, Li C, Gelernter J, Zhao H "GPA: a statistical approach to prioritizing GWAS results by integrating pleiotropy and annotation." PLoS Genet. 2014; 10(11):e1004787
PMID: 25393678
PMCID: PMC4230845

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