Package Recipe 'bioconductor-gsgalgor'

recipe bioconductor-gsgalgor

An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/GSgalgoR.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-gsgalgor/meta.yaml

A multi-objective optimization algorithm for disease sub-type discovery based on a non-dominated sorting genetic algorithm. The 'Galgo' framework combines the advantages of clustering algorithms for grouping heterogeneous 'omics' data and the searching properties of genetic algorithms for feature selection. The algorithm search for the optimal number of clusters determination considering the features that maximize the survival difference between sub-types while keeping cluster consistency high.

package bioconductor-gsgalgor¶

Versions:

1.20.0-0, 1.16.0-0, 1.12.0-1, 1.12.0-0, 1.10.0-0, 1.8.0-0, 1.4.0-0, 1.2.1-0, 1.0.0-1,

1.20.0-0, 1.16.0-0, 1.12.0-1, 1.12.0-0, 1.10.0-0, 1.8.0-0, 1.4.0-0, 1.2.1-0, 1.0.0-1, 1.0.0-0

Depends:

on r-base >=4.5,<4.6.0a0
on r-cluster
on r-doparallel
on r-foreach
on r-matchingr
on r-nsga2r
on r-proxy
on r-survival

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-gsgalgor

to add into an existing workspace instead, run:

pixi add bioconductor-gsgalgor

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-gsgalgor

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-gsgalgor

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-gsgalgor:<tag>

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