recipe medusa-data-fusion

Medusa is an approach to detect size-k modules of objects that, taken together, appear most significant to another set of objects. It builds on collective matrix factorization to derive different semantics, and it formulates the growing of the modules as a submodular optimization program.

Homepage:

https://github.com/marinkaz/medusa

License:

GPLv3

Recipe:

/medusa-data-fusion/meta.yaml

package medusa-data-fusion

(downloads) docker_medusa-data-fusion

versions:

0.1-3,  0.1-2,  0.1-0

depends numpy:

depends python:

<3

depends scipy:

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 medusa-data-fusion

and update with::

   mamba update medusa-data-fusion

To create a new environment, run:

mamba create --name myenvname medusa-data-fusion

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/medusa-data-fusion:<tag>

(see `medusa-data-fusion/tags`_ for valid values for ``<tag>``)

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Link to this page

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