Genome biology · 2018
SCANPY: large-scale single-cell gene expression data analysis
Wolf FA, Angerer P, Theis FJ
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- Wolf FA — Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Munich, Neuherberg, Germany. alex.wolf@helmholtz-muenchen.de.
- Angerer P — Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Munich, Neuherberg, Germany.
- Theis FJ — Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Computational Biology, Munich, Neuherberg, Germany. fabian.theis@helmholtz-muenchen.de.
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SCANPY is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells ( https://github.com/theislab/Scanpy ). Along with SCANPY, we present ANNDATA, a generic class for handling annotated data matrices ( https://github.com/theislab/anndata ).
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