Package Recipe 'bioconductor-netsam'

recipe bioconductor-netsam

Network Seriation And Modularization

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/NetSAM.html
License:: LGPL
Recipe:: /bioconductor-netsam/meta.yaml

The NetSAM (Network Seriation and Modularization) package takes an edge-list representation of a weighted or unweighted network as an input, performs network seriation and modularization analysis, and generates as files that can be used as an input for the one-dimensional network visualization tool NetGestalt (http://www.netgestalt.org) or other network analysis. The NetSAM package can also generate correlation network (e.g. co-expression network) based on the input matrix data, perform seriation and modularization analysis for the correlation network and calculate the associations between the sample features and modules or identify the associated GO terms for the modules.

package bioconductor-netsam¶

Versions:

1.50.0-0, 1.46.0-0, 1.42.0-0, 1.40.0-0, 1.38.0-0, 1.34.0-0, 1.32.0-0, 1.30.0-1, 1.30.0-0,

1.50.0-0, 1.46.0-0, 1.42.0-0, 1.40.0-0, 1.38.0-0, 1.34.0-0, 1.32.0-0, 1.30.0-1, 1.30.0-0, 1.28.0-0, 1.26.0-0, 1.24.0-1, 1.22.0-0

Depends:

on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-go.db >=3.22.0,<3.23.0
on r-base >=4.5,<4.6.0a0
on r-dbi >=0.5-1
on r-doparallel >=1.0.10
on r-foreach >=1.4.0
on r-igraph >=2.0.0
on r-r2html >=2.2.0
on r-seriation >=1.0-6
on r-survival >=2.37-7
on r-wgcna >=1.34.0

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-netsam

to add into an existing workspace instead, run:

pixi add bioconductor-netsam

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-netsam

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-netsam

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-netsam:<tag>

(see bioconductor-netsam/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-netsam/README.html)