recipe gcen

GCEN: an easy-to-use toolkit for Gene Co-Expression Network analysis and lncRNAs annotation

Homepage:

https://www.biochen.org/gcen

License:

GPL v3

Recipe:

/gcen/meta.yaml

Links:

biotools: gcen

GCEN is a command-line toolkit that allows biologists to easily build gene co-expression network and predict gene function, especially in RNA-Seq research or lncRNAs annotation. GCEN is primarily designed to be used in lncRNAs annotation, but is not limited to those scenarios. It is an efficient and easy-to-use solution that will allow everyone to perform gene co-expression network analysis without sophisticated programming skills. The recommended pipeline consists of four parts: data pretreatment, network construction, module identification, and function annotation. A README file and sample data are included in the software package. Because of its modular design, the GCEN can be easily integrated into another pipeline. Also, the multithreaded implementation of GCEN makes it fast and efficient for RNA-Seq data.

package gcen

(downloads) docker_gcen

versions:
0.6.3-2,  0.6.3-1,  0.6.3-0,  0.6.2-1,  0.6.2-0,  0.6.1-0,  0.6.0-0,  0.5.2-0,  0.5.1-1, 

0.6.3-2,  0.6.3-1,  0.6.3-0,  0.6.2-1,  0.6.2-0,  0.6.1-0,  0.6.0-0,  0.5.2-0,  0.5.1-1,  0.5.1-0

depends libgcc-ng:

>=12

depends libstdcxx-ng:

>=12

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 gcen

and update with::

   mamba update gcen

To create a new environment, run:

mamba create --name myenvname gcen

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/gcen:<tag>

(see `gcen/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/gcen/README.html)