recipe simba

SIMBA - SIngle-cell eMBedding Along with features

Homepage:

https://github.com/huidongchen/simba

License:

BSD / BSD-3

Recipe:

/simba/meta.yaml

package simba

(downloads) docker_simba

versions:

1.2-01.1-01.0-00.1-00.1a-0

depends adjusttext:

>=0.7.3

depends anndata:

>=0.7.4

depends kneed:

>=0.7

depends matplotlib-base:

>=3.3

depends numpy:

>=1.17.0

depends pandas:

>=1.0,!=1.1

depends pybedtools:

>=0.8.0

depends pytables:

depends python:

depends scikit-learn:

>=1.2

depends scikit-misc:

>=0.1.3

depends scipy:

>=1.4

depends seaborn:

>=0.11

depends simba_pbg:

>=1.2

depends umap-learn:

>=0.3.0

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 simba

and update with::

   mamba update simba

To create a new environment, run:

mamba create --name myenvname simba

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/simba:<tag>

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

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