recipe bioconductor-piuma

Phenotypes Identification Using Mapper from topological data Analysis

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/PIUMA.html

License:

GPL-3 + file LICENSE

Recipe:

/bioconductor-piuma/meta.yaml

The PIUMA package offers a tidy pipeline of Topological Data Analysis frameworks to identify and characterize communities in high and heterogeneous dimensional data.

package bioconductor-piuma

versions:

1.2.0-0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0

depends r-base:

>=4.4,<4.5.0a0

depends r-cluster:

depends r-dbscan:

depends r-ggplot2:

depends r-hmisc:

depends r-igraph:

depends r-kernlab:

depends r-patchwork:

depends r-scales:

depends r-tsne:

depends r-umap:

depends r-vegan:

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-piuma

and update with::

   mamba update bioconductor-piuma

To create a new environment, run:

mamba create --name myenvname bioconductor-piuma

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-piuma:<tag>

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

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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-piuma/README.html)