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This is the development version of GPA; for the stable release version, see GPA.

GPA (Genetic analysis incorporating Pleiotropy and Annotation)

Bioconductor version: Development (3.20)

This package provides functions for fitting GPA, a statistical framework to prioritize GWAS results by integrating pleiotropy information and annotation data. In addition, it also includes ShinyGPA, an interactive visualization toolkit to investigate pleiotropic architecture.

Author: Dongjun Chung, Emma Kortemeier, Carter Allen

Maintainer: Dongjun Chung <dongjun.chung at>

Citation (from within R, enter citation("GPA")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

GPA PDF R Script
Reference Manual PDF


biocViews Classification, Clustering, DifferentialExpression, GeneExpression, Genetics, GenomeWideAssociation, MultipleComparison, Preprocessing, SNP, Software, StatisticalMethod
Version 1.17.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License GPL (>= 2)
Depends R (>= 4.0.0), methods, graphics, Rcpp
Imports parallel, ggplot2, ggrepel, plyr, vegan, DT, shiny, shinyBS, stats, utils, grDevices
System Requirements GNU make
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Suggests gpaExample
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Follow Installation instructions to use this package in your R session.

Source Package GPA_1.17.0.tar.gz
Windows Binary
macOS Binary (x86_64) GPA_1.17.0.tgz
macOS Binary (arm64) GPA_1.17.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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