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Author:
The scvi-tools development team
License:
BSD 3-Clause License
Copyright (c) 2026, Yosef Lab, Weizmann Institute of Science
All rights reserved.
Redistribution and use in source and binary fo...
Summary:
Deep probabilistic analysis of single-cell omics data.
Latest version:
1.5.1
Required dependencies:
anndata
|
docrep
|
joblib
|
lightning
|
ml-collections
|
mudata
|
numba
|
numpy
|
pandas
|
pyro-ppl
|
rich
|
scanpy
|
scikit-learn
|
scipy
|
sparse
|
tensorboard
|
torch
|
torchmetrics
|
tqdm
|
xarray
Optional dependencies:
annbatch
|
biomart
|
biopython
|
boto3
|
captum
|
cell2location
|
cellxgene-census
|
cugraph-cu12
|
cugraph-cu13
|
cuml-cu12
|
cuml-cu13
|
cupy
|
cupy-cuda12x
|
cupy-cuda13x
|
dask
|
decoupler
|
dvc
|
fastcluster
|
fcswrite
|
gdown
|
genomepy
|
geomloss
|
gputil
|
huggingface-hub
|
hyperopt
|
igraph
|
jupyter
|
lamindb
|
leidenalg
|
matplotlib
|
mlflow
|
mlx
|
mlx-metal
|
muon
|
nvidia-ml-py
|
nvidia-nccl-cu12
|
nvidia-nccl-cu13
|
plotnine
|
pooch
|
psutil
|
pynndescent
|
rapids-singlecell
|
rapids-singlecell-cu12
|
rapids-singlecell-cu13
|
ray
|
readfcs
|
requests
|
scib-metrics
|
scrublet
|
seaborn
|
setuptools
|
shap
|
squidpy
|
tiledbsoma
|
tiledbsoma-ml
|
torch-geometric
|
torch-xla
|
torchaudio
|
torchdata
|
torchvision
|
umap-learn
|
zarr
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