recipe scvi

Single-cell Variational Inference

Homepage:

https://github.com/YosefLab/scVI

Documentation:

https://scvi.readthedocs.io

License:

MIT / MIT License

Recipe:

/scvi/meta.yaml

Single-cell Variational Inference

package scvi

(downloads) docker_scvi

versions:
0.6.8-0,  0.6.7-0,  0.6.5-0,  0.6.4-0,  0.6.3-1,  0.6.3-0,  0.6.1-0,  0.6.0-0,  0.5.0-0, 

0.6.8-0,  0.6.7-0,  0.6.5-0,  0.6.4-0,  0.6.3-1,  0.6.3-0,  0.6.1-0,  0.6.0-0,  0.5.0-0,  0.4.1-1,  0.4.1-0,  0.3.0-1,  0.3.0-0,  0.2.4-0,  0.2.3-0,  0.2.2-0,  0.2.1-0,  0.2.0-0,  0.1.6-0,  0.1.5-0,  0.1.4-0,  0.1.3-0,  0.1.2-0

depends anndata:

>=0.7

depends h5py:

>=2.9.0

depends hyperopt:

0.1.2

depends matplotlib-base:

>=3.0.3

depends numpy:

>=1.16.2

depends pandas:

>=0.25

depends python:

>=3.6

depends pytorch:

>=1.1

depends scanpy:

>=1.4.6

depends scikit-learn:

>=0.20.3

depends tqdm:

>=4.31.1

depends xlrd:

>=1.2.0

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 scvi

and update with::

   mamba update scvi

To create a new environment, run:

mamba create --name myenvname scvi

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/scvi:<tag>

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

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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