recipe bioconductor-gsean

Gene Set Enrichment Analysis with Networks






Biological molecules in a living organism seldom work individually. They usually interact each other in a cooperative way. Biological process is too complicated to understand without considering such interactions. Thus, network-based procedures can be seen as powerful methods for studying complex process. However, many methods are devised for analyzing individual genes. It is said that techniques based on biological networks such as gene co-expression are more precise ways to represent information than those using lists of genes only. This package is aimed to integrate the gene expression and biological network. A biological network is constructed from gene expression data and it is used for Gene Set Enrichment Analysis.

package bioconductor-gsean

(downloads) docker_bioconductor-gsean



depends bioconductor-fgsea:


depends bioconductor-fgsea:


depends bioconductor-ppinfer:


depends bioconductor-ppinfer:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends r-base:




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-gsean

and update with::

   mamba update bioconductor-gsean

To create a new environment, run:

mamba create --name myenvname bioconductor-gsean

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

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