recipe bioconductor-coregnet

CoRegNet : reconstruction and integrated analysis of co-regulatory networks

Homepage:

https://bioconductor.org/packages/3.17/bioc/html/CoRegNet.html

License:

GPL-3

Recipe:

/bioconductor-coregnet/meta.yaml

This package provides methods to identify active transcriptional programs. Methods and classes are provided to import or infer large scale co-regulatory network from transcriptomic data. The specificity of the encoded networks is to model Transcription Factor cooperation. External regulation evidences (TFBS, ChIP,…) can be integrated to assess the inferred network and refine it if necessary. Transcriptional activity of the regulators in the network can be estimated using an measure of their influence in a given sample. Finally, an interactive UI can be used to navigate through the network of cooperative regulators and to visualize their activity in a specific sample or subgroup sample. The proposed visualization tool can be used to integrate gene expression, transcriptional activity, copy number status, sample classification and a transcriptional network including co-regulation information.

package bioconductor-coregnet

(downloads) docker_bioconductor-coregnet

versions:
1.38.0-0,  1.36.0-2,  1.36.0-1,  1.36.0-0,  1.32.0-2,  1.32.0-1,  1.32.0-0,  1.30.0-0,  1.28.0-1, 

1.38.0-0,  1.36.0-2,  1.36.0-1,  1.36.0-0,  1.32.0-2,  1.32.0-1,  1.32.0-0,  1.30.0-0,  1.28.0-1,  1.28.0-0,  1.26.0-0,  1.24.0-0,  1.22.0-1,  1.22.0-0,  1.20.0-0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends r-arules:

depends r-base:

>=4.3,<4.4.0a0

depends r-igraph:

depends r-shiny:

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 bioconductor-coregnet

and update with::

   mamba update bioconductor-coregnet

To create a new environment, run:

mamba create --name myenvname bioconductor-coregnet

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/bioconductor-coregnet:<tag>

(see `bioconductor-coregnet/tags`_ for valid values for ``<tag>``)

Download stats

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/bioconductor-coregnet/README.html)