- recipe scvi
Single-cell Variational Inference
- Homepage:
- Documentation:
- License:
MIT / MIT License
- Recipe:
Single-cell Variational Inference
- package 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:
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
myenvnamebeing 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>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/scvi/README.html)
