Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/scverse/scvi-tools

Deep probabilistic analysis of single-cell and spatial omics data
https://github.com/scverse/scvi-tools

cite-seq deep-generative-model deep-learning human-cell-atlas scrna-seq scverse single-cell-genomics single-cell-rna-seq variational-autoencoder variational-bayes

Last synced: 24 days ago
JSON representation

Deep probabilistic analysis of single-cell and spatial omics data

Awesome Lists containing this project

README 

        


  scvi-tools




[![Stars][gh-stars-badge]][gh-stars-link]

[![PyPI][pypi-badge]][pypi-link]

[![PyPIDownloads][pepy-badge]][pepy-link]

[![CondaDownloads][conda-badge]][conda-link]

[![Docs][docs-badge]][docs-link]

[![Build][build-badge]][build-link]

[![Coverage][coverage-badge]][coverage-link]



[scvi-tools] (single-cell variational inference tools) is a package for probabilistic modeling and

analysis of single-cell omics data, built on top of [PyTorch] and [AnnData].



# Analysis of single-cell omics data



scvi-tools is composed of models that perform many analysis tasks across single-cell, multi, and

spatial omics data:



- Dimensionality reduction

- Data integration

- Automated annotation

- Factor analysis

- Doublet detection

- Spatial deconvolution

- and more!



In the [user guide], we provide an overview of each model. All model implementations have a

high-level API that interacts with [Scanpy] and includes standard save/load functions, GPU

acceleration, etc.



# Rapid development of novel probabilistic models



scvi-tools contains the building blocks to develop and deploy novel probablistic models. These

building blocks are powered by popular probabilistic and machine learning frameworks such as

[PyTorch Lightning] and [Pyro]. For an overview of how the scvi-tools package is structured, you

may refer to the [codebase overview] page.



We recommend checking out the [skeleton repository] as a starting point for developing and

deploying new models with scvi-tools.



# Basic installation



For conda,



```bash

conda install scvi-tools -c conda-forge

```



and for pip,



```bash

pip install scvi-tools

```



Please be sure to install a version of [PyTorch] that is compatible with your GPU (if applicable).



# Resources



- Tutorials, API reference, and installation guides are available in the [documentation].

- For discussion of usage, check out our [forum].

- Please use the [issues] to submit bug reports.

- If you'd like to contribute, check out our [contributing guide].

- If you find a model useful for your research, please consider citing the corresponding

    publication.



# Reference



If you use `scvi-tools` in your work, please cite



> **A Python library for probabilistic analysis of single-cell omics data**

>

> Adam Gayoso, Romain Lopez, Galen Xing, Pierre Boyeau, Valeh Valiollah Pour Amiri, Justin Hong,

> Katherine Wu, Michael Jayasuriya, Edouard Mehlman, Maxime Langevin, Yining Liu, Jules Samaran,

> Gabriel Misrachi, Achille Nazaret, Oscar Clivio, Chenling Xu, Tal Ashuach, Mariano Gabitto,

> Mohammad Lotfollahi, Valentine Svensson, Eduardo da Veiga Beltrame, Vitalii Kleshchevnikov,

> Carlos Talavera-López, Lior Pachter, Fabian J. Theis, Aaron Streets, Michael I. Jordan,

> Jeffrey Regier & Nir Yosef

>

> _Nature Biotechnology_ 2022 Feb 07. doi: [10.1038/s41587-021-01206-w](https://doi.org/10.1038/s41587-021-01206-w).



along with the publicaton describing the model used.



You can cite the scverse publication as follows:



> **The scverse project provides a computational ecosystem for single-cell omics data analysis**

>

> Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor Sturm, Adam Gayoso,

> Ilia Kats, Mikaela Koutrouli, Scverse Community, Bonnie Berger, Dana Pe’er, Aviv Regev,

> Sarah A. Teichmann, Francesca Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle &

> Fabian J. Theis

>

> _Nature Biotechnology_ 2023 Apr 10. doi: [10.1038/s41587-023-01733-8](https://doi.org/10.1038/s41587-023-01733-8).



scvi-tools is part of the scverse project ([website](https://scverse.org),

[governance](https://scverse.org/about/roles)) and is fiscally sponsored by [NumFOCUS]. Please

consider making a tax-deductible [donation] to help the project pay for developer time,

professional services, travel, workshops, and a variety of other needs.





  




[anndata]: https://anndata.readthedocs.io/en/latest/

[build-badge]: https://github.com/scverse/scvi-tools/actions/workflows/build.yml/badge.svg

[build-link]: https://github.com/scverse/scvi-tools/actions/workflows/build.yml/

[codebase overview]: https://docs.scvi-tools.org/en/stable/user_guide/background/codebase_overview.html

[conda-badge]: https://img.shields.io/conda/dn/conda-forge/scvi-tools?logo=Anaconda

[conda-link]: https://anaconda.org/conda-forge/scvi-tools

[contributing guide]: https://docs.scvi-tools.org/en/stable/contributing/index.html

[coverage-badge]: https://codecov.io/gh/scverse/scvi-tools/branch/main/graph/badge.svg

[coverage-link]: https://codecov.io/gh/scverse/scvi-tools

[docs-badge]: https://readthedocs.org/projects/scvi/badge/?version=latest

[docs-link]: https://scvi.readthedocs.io/en/stable/?badge=stable

[documentation]: https://docs.scvi-tools.org/

[donation]: https://numfocus.org/donate-to-scverse

[forum]: https://discourse.scvi-tools.org

[gh-stars-badge]: https://img.shields.io/github/stars/scverse/scvi-tools?style=flat&logo=GitHub&color=blue

[gh-stars-link]: https://github.com/scverse/scvi-tools/stargazers

[issues]: https://github.com/scverse/scvi-tools/issues

[numfocus]: https://numfocus.org/

[pepy-badge]: https://static.pepy.tech/badge/scvi-tools

[pepy-link]: https://pepy.tech/project/scvi-tools

[pypi-badge]: https://img.shields.io/pypi/v/scvi-tools.svg

[pypi-link]: https://pypi.org/project/scvi-tools

[pyro]: https://pyro.ai/

[pytorch]: https://pytorch.org

[pytorch lightning]: https://lightning.ai/docs/pytorch/stable/

[scanpy]: http://scanpy.readthedocs.io/

[scvi-tools]: https://scvi-tools.org/

[skeleton repository]: https://github.com/scverse/simple-scvi

[user guide]: https://docs.scvi-tools.org/en/stable/user_guide/index.html