Package Recipe 'bioconductor-sgcp'

recipe bioconductor-sgcp

SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/SGCP.html
License:: GPL-3
Recipe:: /bioconductor-sgcp/meta.yaml

SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.

package bioconductor-sgcp¶

Versions:

1.6.0-0, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-annotate >=1.84.0,<1.85.0
on bioconductor-genefilter >=1.88.0,<1.89.0
on bioconductor-go.db >=3.20.0,<3.21.0
on bioconductor-gostats >=2.72.0,<2.73.0
on bioconductor-graph >=1.84.0,<1.85.0
on bioconductor-org.hs.eg.db >=3.20.0,<3.21.0
on bioconductor-rgraphviz >=2.50.0,<2.51.0
on bioconductor-summarizedexperiment >=1.36.0,<1.37.0
on r-base >=4.4,<4.5.0a0
on r-caret
on r-desctools
on r-dplyr
on r-expm
on r-ggplot2
on r-ggridges
on r-openxlsx
on r-plyr
on r-rcolorbrewer
on r-reshape2
on r-rspectra
on r-xtable

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-sgcp

to add into an existing workspace instead, run:

pixi add bioconductor-sgcp

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-sgcp

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-sgcp

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-sgcp:<tag>

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