GWAS.BAYES
Bayesian analysis of Gaussian GWAS data
Bioconductor version: Release (3.20)
This package is built to perform GWAS analysis using Bayesian techniques. Currently, GWAS.BAYES has functionality for the implementation of BICOSS (Williams, J., Ferreira, M. A., and Ji, T. (2022). BICOSS: Bayesian iterative conditional stochastic search for GWAS. BMC Bioinformatics), BGWAS (Williams, J., Xu, S., Ferreira, M. A.. (2023) "BGWAS: Bayesian variable selection in linear mixed models with nonlocal priors for genome-wide association studies." BMC Bioinformatics), and GINA. All methods currently are for the analysis of Gaussian phenotypes The research related to this package was supported in part by National Science Foundation awards DMS 1853549, DMS 1853556, and DMS 2054173.
Author: Jacob Williams [aut, cre] 
, Marco Ferreira [aut] , Tieming Ji [aut]
Maintainer: Jacob Williams <jwilliams at vt.edu>
citation("GWAS.BAYES")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GWAS.BAYES")
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("GWAS.BAYES")| BICOSS | HTML | R Script |
| GINA | HTML | R Script |
| Reference Manual | ||
| LICENSE | Text |
Details
| biocViews | AssayDomain, Bayesian, GenomeWideAssociation, SNP, Software |
| Version | 1.16.0 |
| In Bioconductor since | BioC 3.12 (R-4.0) (4 years) |
| License | GPL-3 + file LICENSE |
| Depends | R (>= 4.3.0) |
| Imports | GA (>= 3.2), caret (>= 6.0-86), memoise (>= 1.1.0), Matrix (>= 1.2-18), limma(>= 3.54.0), stats (>= 4.2.2), MASS (>= 7.3-58.1) |
| System Requirements | |
| URL |
See More
| Suggests | BiocStyle, knitr, rmarkdown, formatR, rrBLUP |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | GWAS.BAYES_1.16.0.tar.gz |
| Windows Binary (x86_64) | GWAS.BAYES_1.16.0.zip |
| macOS Binary (x86_64) | GWAS.BAYES_1.16.0.tgz |
| macOS Binary (arm64) | GWAS.BAYES_1.15.1.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/GWAS.BAYES |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/GWAS.BAYES |
| Bioc Package Browser | https://code.bioconductor.org/browse/GWAS.BAYES/ |
| Package Short Url | https://bioconductor.org/packages/GWAS.BAYES/ |
| Package Downloads Report | Download Stats |