recipe r-rubic

RUBIC detects recurrent copy number aberrations using copy number breaks, rather than recurrently amplified or deleted regions. This allows for a vastly simplified approach as recursive peak splitting procedures and repeated re-estimation of the background model are avoided. Furthermore, the false discovery rate is controlled on the level of called regions, rather than at the probe level.

Homepage:

http://ccb.nki.nl/software/

License:

Apache-2.0

Recipe:

/r-rubic/meta.yaml

package r-rubic

(downloads) docker_r-rubic

versions:
1.0.3-7,  1.0.3-6,  1.0.3-5,  1.0.3-4,  1.0.3-3,  1.0.3-2,  1.0.3-1,  1.0.3-0,  1.0.2-1, 

1.0.3-7,  1.0.3-6,  1.0.3-5,  1.0.3-4,  1.0.3-3,  1.0.3-2,  1.0.3-1,  1.0.3-0,  1.0.2-1,  1.0.2-0

depends r-base:

>=4.4,<4.5.0a0

depends r-data.table:

>1.9.6

depends r-digest:

depends r-ggplot2:

depends r-gtable:

depends r-pracma:

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 r-rubic

and update with::

   mamba update r-rubic

To create a new environment, run:

mamba create --name myenvname r-rubic

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-rubic:<tag>

(see `r-rubic/tags`_ for valid values for ``<tag>``)

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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