recipe bioconductor-gmicr

Combines WGCNA and xCell readouts with bayesian network learrning to generate a Gene-Module Immune-Cell network (GMIC)



GPL-2 + file LICENSE



This package uses bayesian network learning to detect relationships between Gene Modules detected by WGCNA and immune cell signatures defined by xCell. It is a hypothesis generating tool.

package bioconductor-gmicr

(downloads) docker_bioconductor-gmicr



depends bioconductor-annotationdbi:


depends bioconductor-category:


depends bioconductor-gostats:


depends bioconductor-gseabase:






depends r-ape:

depends r-base:


depends r-bnlearn:

depends r-data.table:

depends r-doparallel:

depends r-dt:

depends r-foreach:

depends r-grain:

depends r-grbase:

depends r-reshape2:

depends r-shiny:

depends r-wgcna:



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-gmicr

and update with::

   mamba update bioconductor-gmicr

To create a new environment, run:

mamba create --name myenvname bioconductor-gmicr

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

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