recipe bioconductor-proteomm

Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform

Homepage

https://bioconductor.org/packages/3.11/bioc/html/ProteoMM.html

License

MIT

Recipe

/bioconductor-proteomm/meta.yaml

ProteoMM is a statistical method to perform model-based peptide-level differential expression analysis of single or multiple datasets. For multiple datasets ProteoMM produces a single fold change and p-value for each protein across multiple datasets. ProteoMM provides functionality for normalization, missing value imputation and differential expression. Model-based peptide-level imputation and differential expression analysis component of package follows the analysis described in “A statistical framework for protein quantitation in bottom-up MS based proteomics" (Karpievitch et al. Bioinformatics 2009). EigenMS normalisation is implemented as described in "Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition." (Karpievitch et al. Bioinformatics 2009).

package bioconductor-proteomm

Versions

1.6.0-0,  1.4.0-0,  1.2.0-1,  1.0.0-0

Depends

• bioconductor-biomart >=2.44.0,<2.45.0

• r-base >=4.0,<4.1.0a0

• r-gdata

• r-ggplot2

• r-ggrepel

• r-gtools

• r-matrixstats

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-proteomm

and update with:

conda update bioconductor-proteomm

or use the docker container:

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

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

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-proteomm/README.html)