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GPA

GPA (Genetic analysis incorporating Pleiotropy and Annotation)


Bioconductor version: Release (3.18)

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 gmail.com>

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

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GPA")

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

Documentation

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

browseVignettes("GPA")
GPA PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, Clustering, DifferentialExpression, GeneExpression, Genetics, GenomeWideAssociation, MultipleComparison, Preprocessing, SNP, Software, StatisticalMethod
Version 1.14.0
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
URL http://dongjunchung.github.io/GPA/
Bug Reports https://github.com/dongjunchung/GPA/issues
See More
Suggests gpaExample
Linking To Rcpp
Enhances
Depends On Me
Imports Me
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Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package GPA_1.14.0.tar.gz
Windows Binary GPA_1.14.0.zip
macOS Binary (x86_64) GPA_1.14.0.tgz
macOS Binary (arm64) GPA_1.14.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/GPA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/GPA
Bioc Package Browser https://code.bioconductor.org/browse/GPA/
Package Short Url https://bioconductor.org/packages/GPA/
Package Downloads Report Download Stats