recipe bioconductor-moma

Multi Omic Master Regulator Analysis

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-moma/meta.yaml

This package implements the inference of candidate master regulator proteins from multi-omics' data (MOMA) algorithm, as well as ancillary analysis and visualization functions.

package bioconductor-moma

versions:

1.18.0-0,  1.14.0-0,  1.12.0-0,  1.10.0-0,  1.6.0-0,  1.4.0-0,  1.2.0-1,  1.2.0-0,  1.0.1-0

depends bioconductor-complexheatmap:

>=2.22.0,<2.23.0

depends bioconductor-multiassayexperiment:

>=1.32.0,<1.33.0

depends bioconductor-qvalue:

>=2.38.0,<2.39.0

depends r-base:

>=4.4,<4.5.0a0

depends r-circlize:

depends r-cluster:

depends r-dplyr:

depends r-ggplot2:

depends r-magrittr:

depends r-mkmisc:

depends r-rcolorbrewer:

depends r-readr:

depends r-reshape2:

depends r-rlang:

depends r-stringr:

depends r-tibble:

depends r-tidyr:

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-moma

and update with::

   mamba update bioconductor-moma

To create a new environment, run:

mamba create --name myenvname bioconductor-moma

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-moma:<tag>

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

Download stats

Link to this page

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