DOI resolved by resea

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

Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, different…

F. Alexander Wolf, Philipp Angerer, Fabian J. Theis
https://resea.org/10.1186/s13059-017-1382-0

Abstract

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 ).