recipe bioconductor-gwas.bayes

Bayesian analysis of Gaussian GWAS data






This package is built to perform GWAS analysis using Bayesian techniques. Currently, GWAS.BAYES has functionality for the implementation of BICOSS for Gaussian phenotypes (Williams, J., Ferreira, M. A., and Ji, T. (2022). BICOSS: Bayesian iterative conditional stochastic search for GWAS. BMC Bioinformatics 23, 475). The research related to this package was supported in part by National Science Foundation awards DMS 1853549, DMS 1853556, and DMS 2054173.

package bioconductor-gwas.bayes

(downloads) docker_bioconductor-gwas.bayes



depends bioconductor-limma:


depends r-base:


depends r-caret:


depends r-ga:


depends r-mass:


depends r-matrix:


depends r-memoise:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-gwas.bayes

and update with::

   mamba update bioconductor-gwas.bayes

To create a new environment, run:

mamba create --name myenvname bioconductor-gwas.bayes

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-gwas.bayes/tags`_ for valid values for ``<tag>``)

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