recipe bioconductor-rforproteomics

Companion package to the 'Using R and Bioconductor for proteomics data analysis' publication

Homepage:

https://bioconductor.org/packages/3.18/data/experiment/html/RforProteomics.html

License:

Artistic-2.0

Recipe:

/bioconductor-rforproteomics/meta.yaml

This package contains code to illustrate the 'Using R and Bioconductor for proteomics data analysis' and 'Visualisation of proteomics data using R and Bioconductor' manuscripts. The vignettes describe the code and data needed to reproduce the examples and figures described in the paper and functionality for proteomics visualisation. It also contain various function to discover R software for mass spectrometry and proteomics.

package bioconductor-rforproteomics

(downloads) docker_bioconductor-rforproteomics

versions:
1.40.0-0,  1.38.1-0,  1.35.1-0,  1.32.0-1,  1.31.1-0,  1.30.0-0,  1.28.1-0,  1.27.1-0,  1.26.0-0, 

1.40.0-0,  1.38.1-0,  1.35.1-0,  1.32.0-1,  1.31.1-0,  1.30.0-0,  1.28.1-0,  1.27.1-0,  1.26.0-0,  1.23.1-0,  1.22.0-1,  1.20.0-0

depends bioconductor-biocviews:

>=1.70.0,<1.71.0

depends bioconductor-data-packages:

>=20231203

depends bioconductor-msnbase:

>=2.28.0,<2.29.0

depends curl:

depends r-base:

>=4.3,<4.4.0a0

depends r-biocmanager:

depends r-r.utils:

requirements:

additional platforms:

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-rforproteomics

and update with::

   mamba update bioconductor-rforproteomics

To create a new environment, run:

mamba create --name myenvname bioconductor-rforproteomics

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-rforproteomics:<tag>

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

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Link to this page

Render an install-with-bioconda 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-rforproteomics/README.html)