recipe bioconductor-bloodgen3module

This R package for performing module repertoire analyses and generating fingerprint representations

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/BloodGen3Module.html

License:

GPL-2

Recipe:

/bioconductor-bloodgen3module/meta.yaml

The BloodGen3Module package provides functions for R user performing module repertoire analyses and generating fingerprint representations. Functions can perform group comparison or individual sample analysis and visualization by fingerprint grid plot or fingerprint heatmap. Module repertoire analyses typically involve determining the percentage of the constitutive genes for each module that are significantly increased or decreased. As we describe in details;https://www.biorxiv.org/content/10.1101/525709v2 and https://pubmed.ncbi.nlm.nih.gov/33624743/, the results of module repertoire analyses can be represented in a fingerprint format, where red and blue spots indicate increases or decreases in module activity. These spots are subsequently represented either on a grid, with each position being assigned to a given module, or in a heatmap where the samples are arranged in columns and the modules in rows.

package bioconductor-bloodgen3module

(downloads) docker_bioconductor-bloodgen3module

versions:

1.10.0-01.8.0-01.6.0-01.2.0-01.0.0-0

depends bioconductor-complexheatmap:

>=2.18.0,<2.19.0

depends bioconductor-experimenthub:

>=2.10.0,<2.11.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-preprocesscore:

>=1.64.0,<1.65.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-circlize:

depends r-ggplot2:

depends r-gtools:

depends r-matrixstats:

depends r-randomcolor:

depends r-reshape2:

depends r-testthat:

depends r-v8:

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-bloodgen3module

and update with::

   mamba update bioconductor-bloodgen3module

To create a new environment, run:

mamba create --name myenvname bioconductor-bloodgen3module

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-bloodgen3module:<tag>

(see `bioconductor-bloodgen3module/tags`_ for valid values for ``<tag>``)

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