recipe bioconductor-ruvnormalize

RUV for normalization of expression array data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/RUVnormalize.html

License:

GPL-3

Recipe:

/bioconductor-ruvnormalize/meta.yaml

Links:

biotools: ruvnormalize

RUVnormalize is meant to remove unwanted variation from gene expression data when the factor of interest is not defined, e.g., to clean up a dataset for general use or to do any kind of unsupervised analysis.

package bioconductor-ruvnormalize

(downloads) docker_bioconductor-ruvnormalize

versions:
1.40.0-01.36.0-01.34.0-01.32.0-01.28.0-01.26.0-01.24.0-21.24.0-01.22.0-0

1.40.0-01.36.0-01.34.0-01.32.0-01.28.0-01.26.0-01.24.0-21.24.0-01.22.0-01.20.0-11.18.0-11.16.0-01.14.0-01.12.0-0

depends bioconductor-biobase:

>=2.66.0,<2.67.0

depends bioconductor-ruvnormalizedata:

>=1.26.0,<1.27.0

depends r-base:

>=4.4,<4.5.0a0

requirements:

additional platforms:

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 bioconductor-ruvnormalize

and update with::

   mamba update bioconductor-ruvnormalize

To create a new environment, run:

mamba create --name myenvname bioconductor-ruvnormalize

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/bioconductor-ruvnormalize:<tag>

(see `bioconductor-ruvnormalize/tags`_ for valid values for ``<tag>``)

Download stats