recipe bioconductor-plgem

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

Homepage:

https://bioconductor.org/packages/3.16/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

Versions:

1.70.0-0,  1.66.0-0,  1.64.0-0,  1.62.0-1,  1.62.0-0,  1.60.0-0,  1.58.0-0,  1.56.0-1,  1.54.1-0, 

1.70.0-0,  1.66.0-0,  1.64.0-0,  1.62.0-1,  1.62.0-0,  1.60.0-0,  1.58.0-0,  1.56.0-1,  1.54.1-0,  1.54.0-0,  1.52.0-0,  1.50.0-0,  1.48.0-0

Depends:

• bioconductor-biobase >=2.58.0,<2.59.0

• r-base >=4.2,<4.3.0a0

• r-mass

Required By:

• bioconductor-inspect

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-plgem

and update with:

conda update bioconductor-plgem

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-plgem:<tag>

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

Download stats

Link to this page

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-plgem/README.html)