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Showing content from https://www.bioconductor.org/packages/devel/bioc/html/../../bioc/html/GWAS.BAYES.html below:

Bioconductor - GWAS.BAYES (development version)

GWAS.BAYES

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

Bayesian analysis of Gaussian GWAS data

Bioconductor version: Development (3.22)

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] ORCID: 0000-0002-6425-1365 , Marco Ferreira [aut] ORCID: 0000-0002-4705-5661 , Tieming Ji [aut]

Maintainer: Jacob Williams <jwilliams at vt.edu>

Citation (from within R, enter citation("GWAS.BAYES")): Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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")
Details biocViews AssayDomain, Bayesian, GenomeWideAssociation, SNP, Software Version 1.19.0 In Bioconductor since BioC 3.12 (R-4.0) (4.5 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 Package Archives

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

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