recipe blksheep

A package for differential extreme values analysis

Homepage:

https://github.com/ruggleslab/blackSheep/

Documentation:

https://blacksheep.readthedocs.io/en/master/

Developer docs:

https://github.com/ruggleslab/blackSheep

License:

MIT / MIT

Recipe:

/blksheep/meta.yaml

package blksheep

versions:

0.0.7-0,  0.0.6-0,  0.0.5-0,  0.0.3-0,  0.0.2-0

depends matplotlib-base:

>=3.1.0

depends numpy:

>=1.16.4

depends pandas:

>=0.24.2

depends python:

depends scikit-learn:

>=0.21.2

depends scipy:

>=1.2.1

depends seaborn:

>=0.9.0

depends statsmodels:

>=0.10.0

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 blksheep

and update with::

   mamba update blksheep

To create a new environment, run:

mamba create --name myenvname blksheep

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/blksheep:<tag>

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

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