recipe bioconductor-gaga

GaGa hierarchical model for high-throughput data analysis

Homepage:

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

License:

GPL-3.0-or-later

Recipe:

/bioconductor-gaga/meta.yaml

Links:

biotools: gaga, doi: 10.1214/09-aoas244

Implements the GaGa model for high-throughput data analysis, including differential expression analysis, supervised gene clustering and classification. Additionally, it performs sequential sample size calculations using the GaGa and LNNGV models (the latter from EBarrays package).

package bioconductor-gaga

(downloads) docker_bioconductor-gaga

versions:
2.48.0-12.48.0-02.46.0-02.44.0-12.44.0-02.40.0-22.40.0-12.40.0-02.38.0-0

2.48.0-12.48.0-02.46.0-02.44.0-12.44.0-02.40.0-22.40.0-12.40.0-02.38.0-02.36.0-12.36.0-02.34.0-02.32.0-02.30.0-12.28.1-02.28.0-02.26.0-02.24.0-02.22.0-0

depends bioconductor-biobase:

>=2.62.0,<2.63.0

depends bioconductor-biobase:

>=2.62.0,<2.63.0a0

depends bioconductor-ebarrays:

>=2.66.0,<2.67.0

depends bioconductor-ebarrays:

>=2.66.0,<2.67.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends r-base:

>=4.3,<4.4.0a0

depends r-coda:

depends r-mgcv:

requirements:

additional platforms:
linux-aarch64

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-gaga

and update with::

   mamba update bioconductor-gaga

To create a new environment, run:

mamba create --name myenvname bioconductor-gaga

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-gaga:<tag>

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

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