recipe bioconductor-moda

MODA: MOdule Differential Analysis for weighted gene co-expression network



GPL (>= 2)



MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes.

package bioconductor-moda

(downloads) docker_bioconductor-moda



depends bioconductor-amountain:


depends r-base:


depends r-cluster:

depends r-dynamictreecut:

depends r-igraph:

depends r-rcolorbrewer:

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-moda

and update with::

   mamba update bioconductor-moda

To create a new environment, run:

mamba create --name myenvname bioconductor-moda

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

Download stats