GGPA
This is the development version of GGPA; for the stable release version, see GGPA.
graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture
Bioconductor version: Development (3.24)
Genome-wide association studies (GWAS) is a widely used tool for identification of genetic variants associated with phenotypes and diseases, though complex diseases featuring many genetic variants with small effects present difficulties for traditional these studies. By leveraging pleiotropy, the statistical power of a single GWAS can be increased. This package provides functions for fitting graph-GPA, a statistical framework to prioritize GWAS results by integrating pleiotropy. 'GGPA' package provides user-friendly interface to fit graph-GPA models, implement association mapping, and generate a phenotype graph.
Author: Dongjun Chung, Hang J. Kim, Carter Allen
Maintainer: Dongjun Chung <dongjun.chung at gmail.com>
citation("GGPA")):Dongjun Chung, Hang J. Kim, Carter Allen. GGPA: graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture. doi:10.18129/B9.bioc.GGPA, R package version 1.25.0, https://bioconductor.org/packages/GGPA.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
BiocManager::install("GGPA")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("GGPA")| GGPA | R Script | |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Classification, Clustering, DifferentialExpression, GeneExpression, Genetics, GenomeWideAssociation, MultipleComparison, Preprocessing, SNP, Software, StatisticalMethod |
| Version | 1.25.0 |
| In Bioconductor since | BioC 3.11 (R-4.0) (6.5 years) |
| License | GPL (>= 2) |
| Depends | R (>= 4.0.0), stats, methods, graphics, GGally, network, sna, scales, matrixStats |
| Imports | Rcpp (>= 0.11.3) |
| System Requirements | GNU make |
| URL | https://github.com/dongjunchung/GGPA/ |
See More
| Suggests | BiocStyle |
| Linking To | Rcpp, RcppArmadillo |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | GGPA_1.25.0.tar.gz |
| Windows Binary (x86_64) | GGPA_1.25.0.zip |
| macOS Binary (big-sur-x86_64) | GGPA_1.25.0.tgz |
| macOS Binary (sonoma-arm64) | GGPA_1.25.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/GGPA |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/GGPA |
| Package Short Url | https://bioconductor.org/packages/GGPA/ |
| Package Downloads Report | Download Stats |