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.
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
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. 2022 Apr 10. doi: 10.1038/s41587-023-01733-8.