recipe bioconductor-gpa

GPA (Genetic analysis incorporating Pleiotropy and Annotation)



GPL (>= 2)



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.

package bioconductor-gpa

(downloads) docker_bioconductor-gpa



depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-dt:

depends r-ggplot2:

depends r-ggrepel:

depends r-plyr:

depends r-rcpp:

depends r-shiny:

depends r-shinybs:

depends r-vegan:



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-gpa

and update with::

   mamba update bioconductor-gpa

To create a new environment, run:

mamba create --name myenvname bioconductor-gpa

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-gpa/tags`_ for valid values for ``<tag>``)

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