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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 tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
Citation
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
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