recipe bioconductor-multirnaflow

An R package for analysing RNA-seq raw counts with several biological conditions and different time points

Homepage:

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

License:

GPL-3 | file LICENSE

Recipe:

/bioconductor-multirnaflow/meta.yaml

Our R package MultiRNAflow provides an easy to use unified framework allowing to automatically make both unsupervised and supervised (DE) analysis for datasets with an arbitrary number of biological conditions and time points. In particular, our code makes a deep downstream analysis of DE information, e.g. identifying temporal patterns across biological conditions and DE genes which are specific to a biological condition for each time.

package bioconductor-multirnaflow

(downloads) docker_bioconductor-multirnaflow

versions:

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-multirnaflow

and update with::

   mamba update bioconductor-multirnaflow

To create a new environment, run:

mamba create --name myenvname bioconductor-multirnaflow

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-multirnaflow:<tag>

(see `bioconductor-multirnaflow/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-multirnaflow/README.html)