- recipe scvi-tools
Deep probabilistic analysis of single-cell omics data.
- Homepage:
- Documentation:
- Developer docs:
- License:
BSD / BSD-3-Clause
- Recipe:
- package scvi-tools¶
- versions:
0.14.5-1,0.14.5-0,0.14.4-0,0.14.3-0,0.14.2-0,0.13.0-0,0.12.2-0,0.11.0-0,0.10.1-0,0.14.5-1,0.14.5-0,0.14.4-0,0.14.3-0,0.14.2-0,0.13.0-0,0.12.2-0,0.11.0-0,0.10.1-0,0.10.0-0,0.9.1-0,0.9.0-0,0.8.1-0,0.8.0-0,0.7.1-0,0.7.0-0,0.7.0b0-0,0.7.0a6-0,0.7.0a5-0,0.7.0a4-1,0.7.0a4-0- depends anndata:
>=0.7.5- depends docrep:
>=0.3.2- depends h5py:
>=2.9.0- depends ipywidgets:
>=7.5.1- depends numba:
>=0.41.0- depends numpy:
>=1.17.0- depends openpyxl:
>=3.0- depends pandas:
>=1.0- depends pyro-ppl:
>=1.6.0- depends python:
>=3.7- depends pytorch:
>=1.8.0- depends pytorch-lightning:
>=1.3,<1.4- depends rich:
>=9.12.4- depends scikit-learn:
>=0.21.2- depends setuptools:
<59- depends tqdm:
>=4.56.0- 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-tools and update with:: mamba update scvi-tools
To create a new environment, run:
mamba create --name myenvname scvi-tools
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-tools:<tag> (see `scvi-tools/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-tools/README.html)
