recipe bioconductor-gwena

Pipeline for augmented co-expression analysis






The development of high-throughput sequencing led to increased use of co-expression analysis to go beyong single feature (i.e. gene) focus. We propose GWENA (Gene Whole co-Expression Network Analysis) , a tool designed to perform gene co-expression network analysis and explore the results in a single pipeline. It includes functional enrichment of modules of co-expressed genes, phenotypcal association, topological analysis and comparison of networks configuration between conditions.

package bioconductor-gwena

(downloads) docker_bioconductor-gwena



depends bioconductor-summarizedexperiment:


depends r-base:


depends r-cluster:


depends r-dplyr:


depends r-dynamictreecut:


depends r-ggplot2:


depends r-gprofiler2:


depends r-igraph:


depends r-magrittr:


depends r-matrixstats:


depends r-netrep:


depends r-purrr:


depends r-rcolorbrewer:


depends r-rlist:


depends r-stringr:


depends r-tibble:


depends r-tidyr:


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-gwena

and update with::

   mamba update bioconductor-gwena

To create a new environment, run:

mamba create --name myenvname bioconductor-gwena

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

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