GPA

DOI: 10.18129/B9.bioc.GPA  

GPA (Genetic analysis incorporating Pleiotropy and Annotation)

Bioconductor version: Release (3.16)

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 "4.2") 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")

 

PDF R Script GPA
PDF   Reference Manual
Text   NEWS

Details

biocViews Classification, Clustering, DifferentialExpression, GeneExpression, Genetics, GenomeWideAssociation, MultipleComparison, Preprocessing, SNP, Software, StatisticalMethod
Version 1.10.0
In Bioconductor since BioC 3.11 (R-4.0) (3 years)
License GPL (>= 2)
Depends R (>= 4.0.0), methods, graphics, Rcpp
Imports parallel, ggplot2, ggrepel, plyr, vegan, DT, shiny, shinyBS, stats, utils, grDevices
LinkingTo Rcpp
Suggests gpaExample
SystemRequirements GNU make
Enhances
URL http://dongjunchung.github.io/GPA/
BugReports https://github.com/dongjunchung/GPA/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package GPA_1.10.0.tar.gz
Windows Binary GPA_1.10.0.zip
macOS Binary (x86_64) GPA_1.10.0.tgz
macOS Binary (arm64) GPA_1.10.0.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

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