recipe multixrank

MultiXrank - heterogeneous MULTIlayer eXploration by RANdom walK with restart. MultiXrank is a Python package for the exploration of heterogeneous multilayer networks, with random walk with restart method. It permits prioritization of nodes between full heterogeneous networks, whatever their complexities.

Homepage:

https://multixrank.readthedocs.io

License:

MIT

Recipe:

/multixrank/meta.yaml

package multixrank

versions:

0.3-0,  0.1-1

depends networkx:

2.5

depends numpy:

<2

depends pandas:

depends psutil:

depends python:

depends pyyaml:

depends scipy:

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 multixrank

and update with::

   mamba update multixrank

To create a new environment, run:

mamba create --name myenvname multixrank

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/multixrank:<tag>

(see `multixrank/tags`_ for valid values for ``<tag>``)

Download stats

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/multixrank/README.html)