recipe scprep

Tools for loading and preprocessing biological matrices in Python.

Homepage:

https://github.com/KrishnaswamyLab/scprep

License:

GPL2 / GNU General Public Version 2

Recipe:

/scprep/meta.yaml

package scprep

versions:

1.2.3-0,  1.2.2-0,  1.2.1-0,  1.2.0-0,  1.1.0-0,  1.0.13-0,  1.0.12-0,  1.0.11-0,  1.0.10-0, 

1.2.3-0,  1.2.2-0,  1.2.1-0,  1.2.0-0,  1.1.0-0,  1.0.13-0,  1.0.12-0,  1.0.11-0,  1.0.10-0,  1.0.9-0,  1.0.8-0,  1.0.7-0,  1.0.6-0,  1.0.5.post2-0,  1.0.4-0,  1.0.3-0,  1.0.2-0,  1.0.1-0,  1.0.0-0,  0.12.2-0,  0.12.1-0,  0.12.0-0,  0.8.1-0,  0.7.1-0

depends decorator:

>=4.3.0

depends numpy:

>=1.12.0

depends packaging:

depends pandas:

>=0.25

depends python:

>=3.5

depends scikit-learn:

>=0.19.1

depends scipy:

>=0.18.1

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 scprep

and update with::

   mamba update scprep

To create a new environment, run:

mamba create --name myenvname scprep

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/scprep:<tag>

(see `scprep/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/scprep/README.html)