recipe bioconductor-plgem

Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM)

Homepage:

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

License:

GPL-2

Recipe:

/bioconductor-plgem/meta.yaml

Links:

biotools: plgem

The Power Law Global Error Model (PLGEM) has been shown to faithfully model the variance-versus-mean dependence that exists in a variety of genome-wide datasets, including microarray and proteomics data. The use of PLGEM has been shown to improve the detection of differentially expressed genes or proteins in these datasets.

package bioconductor-plgem

(downloads) docker_bioconductor-plgem

versions:
1.74.0-01.72.0-01.70.0-01.66.0-01.64.0-01.62.0-11.62.0-01.60.0-01.58.0-0

1.74.0-01.72.0-01.70.0-01.66.0-01.64.0-01.62.0-11.62.0-01.60.0-01.58.0-01.56.0-11.54.1-01.54.0-01.52.0-01.50.0-01.48.0-0

depends bioconductor-biobase:

>=2.62.0,<2.63.0

depends r-base:

>=4.3,<4.4.0a0

depends r-mass:

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 bioconductor-plgem

and update with::

   mamba update bioconductor-plgem

To create a new environment, run:

mamba create --name myenvname bioconductor-plgem

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-plgem:<tag>

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

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