recipe r-isva

Independent Surrogate Variable Analysis is an algorithm for feature selection in the presence of potential confounding factors (see Teschendorff AE et al 2011, <doi: 10.1093/bioinformatics/btr171>).

Homepage:

https://CRAN.R-project.org/package=isva

License:

GPL2 / GPL-2

Recipe:

/r-isva/meta.yaml

package r-isva

(downloads) docker_r-isva

versions:

1.9-6,  1.9-5,  1.9-4,  1.9-3,  1.9-2,  1.9-1,  1.9-0

depends bioconductor-qvalue:

depends r-base:

>=4.3,<4.4.0a0

depends r-fastica:

depends r-jade:

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 r-isva

and update with::

   mamba update r-isva

To create a new environment, run:

mamba create --name myenvname r-isva

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/r-isva:<tag>

(see `r-isva/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/r-isva/README.html)