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DOI: 10.1186/s13059-017-1382-0
¤ OpenAccess: Gold
This work has “Gold” OA status. This means it is published in an Open Access journal that is indexed by the DOAJ.

SCANPY: large-scale single-cell gene expression data analysis

F. Alexander Wolf,Philipp Angerer,Fabian J. Theis

Python (programming language)
Preprocessor
Inference
2018
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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    SCANPY: large-scale single-cell gene expression data analysis” is a paper by F. Alexander Wolf Philipp Angerer Fabian J. Theis published in 2018. It has an Open Access status of “gold”. You can read and download a PDF Full Text of this paper here.