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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 contribution 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.
If you use scanpy
in your work, please cite the scanpy
publication as follows:
SCANPY: large-scale single-cell gene expression data analysis
F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
Genome Biology 2018 Feb 06. doi: 10.1186/s13059-017-1382-0.
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
Nat Biotechnol. 2023 Apr 10. doi: 10.1038/s41587-023-01733-8.
FAQs
Single-Cell Analysis in Python.
We found that scanpy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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