“SCANPY: large-scale single-cell gene expression data analysis” (2018), by F. Alexander Wolf et al. Genetics and Biochemistry research paper. Original abstract below, unchanged. A free PDF is available.

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

F. Alexander Wolf, Philipp Angerer, Fabian Joachim Theis · February 6, 2018 · Genetics and Biochemistry

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 ).

Free PDF DOI: 10.1186/s13059-017-1382-0