recipe rgccacmd

Multiblock data analysis concerns the analysis of several sets of variables (blocks) observed on the same group of individuals. The main aims of the RGCCA package are (i) to study the relationships between blocks and (ii) to identify subsets of variables of each block which are active in their relationships with the other blocks.

Homepage:

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

Documentation:

https://github.com/BrainAndSpineInstitute/rgcca_ui#readme

License:

GPL3 / GPL-2.0-or-later

Recipe:

/rgccacmd/meta.yaml

package rgccacmd

(downloads) docker_rgccacmd

versions:

3.0.3-03.0.2-03.0.1-03.0.0-23.0.0-13.0.0-0

depends r-base:

>=4.2,<4.3.0a0

depends r-deriv:

depends r-ggplot2:

depends r-ggrepel:

depends r-gridextra:

depends r-igraph:

depends r-mass:

depends r-openxlsx:

depends r-optparse:

depends r-pbapply:

depends r-plotly:

depends r-rlang:

depends r-scales:

depends r-vegan:

depends wget:

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 rgccacmd

and update with::

   mamba update rgccacmd

To create a new environment, run:

mamba create --name myenvname rgccacmd

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/rgccacmd:<tag>

(see `rgccacmd/tags`_ for valid values for ``<tag>``)

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