recipe scib

Evaluating single-cell data integration methods

Homepage:

https://github.com/theislab/scib

Documentation:

https://scib.readthedocs.io/en/latest/

License:

MIT / MIT

Recipe:

/scib/meta.yaml

Links:

doi: 10.1038/s41592-021-01336-8

package scib

versions:

1.1.5-1,  1.1.5-0,  1.1.4-1,  1.1.4-0

depends anndata:

>=0.7.2

depends deprecated:

depends h5py:

depends igraph:

>=0.10

depends leidenalg:

depends libgcc-ng:

>=12

depends libstdcxx-ng:

>=12

depends llvmlite:

depends matplotlib-base:

depends numpy:

depends pandas:

<2

depends pydot:

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

depends scanpy:

>=1.5,<1.10

depends scikit-learn:

depends scikit-misc:

depends scipy:

depends seaborn:

depends umap-learn:

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 scib

and update with::

   mamba update scib

To create a new environment, run:

mamba create --name myenvname scib

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/scib:<tag>

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

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