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Single-cell analysis in Python. Scales to >100M cells.
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scverse/scanpy
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Scanpy is a scalable toolkit for analyzing single-cell gene expression databuilt jointly withanndata. It includespreprocessing, visualization, clustering, trajectory inference and differentialexpression testing. The Python-based implementation efficiently deals withdatasets of more than one million cells.
Discuss usage on the scverseDiscourse. Read thedocumentation.If you'd like to contribute by opening an issue or creating a pull request, please take a look at ourcontribution guide.
scanpy is part of the scverse® project (website,governance) and is fiscally sponsored byNumFOCUS.If you like scverse® and want to support our mission, please consider making a tax-deductibledonation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
If you usescanpy
in your work, please cite thescanpy
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.
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Single-cell analysis in Python. Scales to >100M cells.