Package Recipe 'bioconductor-enrichviewnet'

recipe bioconductor-enrichviewnet

From functional enrichment results to biological networks

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/enrichViewNet.html
License:: Artistic-2.0
Recipe:: /bioconductor-enrichviewnet/meta.yaml

This package enables the visualization of functional enrichment results as network graphs. First the package enables the visualization of enrichment results, in a format corresponding to the one generated by gprofiler2, as a customizable Cytoscape network. In those networks, both gene datasets (GO terms/pathways/protein complexes) and genes associated to the datasets are represented as nodes. While the edges connect each gene to its dataset(s). The package also provides the option to create enrichment maps from functional enrichment results. Enrichment maps enable the visualization of enriched terms into a network with edges connecting overlapping genes.

package bioconductor-enrichviewnet¶

Versions:

1.8.1-0, 1.4.0-0, 1.0.0-0

Depends:

on bioconductor-enrichplot >=1.30.0,<1.31.0
on bioconductor-rcy3 >=2.30.0,<2.31.0
on r-base >=4.5,<4.6.0a0
on r-gprofiler2
on r-igraph
on r-jsonlite
on r-reshape2
on r-strex
on r-stringr

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-enrichviewnet

to add into an existing workspace instead, run:

pixi add bioconductor-enrichviewnet

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-enrichviewnet

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-enrichviewnet

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-enrichviewnet:<tag>

(see bioconductor-enrichviewnet/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an 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-enrichviewnet/README.html)