recipe bioconductor-gsar

Gene Set Analysis in R

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/GSAR.html

License:

GPL (>=2)

Recipe:

/bioconductor-gsar/meta.yaml

Gene set analysis using specific alternative hypotheses. Tests for differential expression, scale and net correlation structure.

package bioconductor-gsar

(downloads) docker_bioconductor-gsar

versions:
1.36.0-0,  1.34.0-0,  1.32.0-0,  1.28.0-0,  1.26.0-0,  1.24.0-1,  1.24.0-0,  1.22.0-0,  1.20.0-0, 

1.36.0-0,  1.34.0-0,  1.32.0-0,  1.28.0-0,  1.26.0-0,  1.24.0-1,  1.24.0-0,  1.22.0-0,  1.20.0-0,  1.18.0-1,  1.18.0-0,  1.16.0-0

depends r-base:

>=4.3,<4.4.0a0

depends r-igraph:

>=0.7.1

requirements:

Installation

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-gsar

and update with::

   mamba update bioconductor-gsar

To create a new environment, run:

mamba create --name myenvname bioconductor-gsar

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 quay.io/biocontainers/bioconductor-gsar:<tag>

(see `bioconductor-gsar/tags`_ for valid values for ``<tag>``)

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-gsar/README.html)