Scanpy – Single-Cell Analysis in Python#
Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. 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].
scanpy is part of the scverse project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse and want to support our mission, please consider making a donation to support our efforts.
Other resources
Follow changes in the release notes.
Find tools that harmonize well with anndata & Scanpy via the external API and the ecosystem page.
Check out our contributing guide for development practices.
Consider citing Genome Biology (2018) along with original references.
News#
Scanpy hits 100 contributors! 2022-03-31#
100 people have contributed to Scanpy’s source code!
Of course, contributions to the project are not limited to direct modification of the source code. Many others have improved the project by building on top of it, participating in development discussions, helping others with usage, or by showing off what it’s helped them accomplish.
Thanks to all our contributors for making this project possible!
New community channels 2022-03-31#
We’ve moved our forums and have a new publicly available chat!
Our discourse forum has migrated to a joint scverse forum (discourse.scverse.org).
Our private developer Slack has been replaced by a public Zulip chat (scverse.zulipchat.com).
Toolkit for spatial (squidpy) and multimodal (muon) published 2022-02-01#
Two large toolkits extending our ecosystem to new modalities have had their manuscripts published!
Muon, a framework for multimodal has been published in Genome Biology.
Squidpy a toolkit for working with spatial single cell data has been published in Nature Methods.