[![Stars](https://img.shields.io/github/stars/scverse/scanpy?logo=GitHub&color=yellow)](https://github.com/scverse/scanpy/stargazers) [![PyPI](https://img.shields.io/pypi/v/scanpy?logo=PyPI)](https://pypi.org/project/scanpy) [![PyPIDownloads](https://pepy.tech/badge/scanpy)](https://pepy.tech/project/scanpy) [![Conda](https://img.shields.io/conda/dn/conda-forge/scanpy?logo=Anaconda)](https://anaconda.org/conda-forge/scanpy) [![Docs](https://readthedocs.com/projects/icb-scanpy/badge/?version=latest)](https://scanpy.readthedocs.io) [![Build Status](https://dev.azure.com/scverse/scanpy/_apis/build/status/theislab.scanpy?branchName=master)](https://dev.azure.com/scverse/scanpy/_build) [![Discourse topics](https://img.shields.io/discourse/posts?color=yellow&logo=discourse&server=https%3A%2F%2Fdiscourse.scverse.org)](https://discourse.scverse.org/) [![Chat](https://img.shields.io/badge/zulip-join_chat-%2367b08f.svg)](https://scverse.zulipchat.com) # Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with [anndata](https://anndata.readthedocs.io). It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells. Discuss usage on the scverse [Discourse]. Read the [documentation]. If you'd like to contribute by opening an issue or creating a pull request, please take a look at our [contributing guide]. If Scanpy is useful for your research, consider citing [Genome Biology (2018)]. [contributing guide]: CONTRIBUTING.md [discourse]: https://discourse.scverse.org/ [documentation]: https://scanpy.readthedocs.io [genome biology (2018)]: https://doi.org/10.1186/s13059-017-1382-0