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 ).
Keywords: Bioinformatics; Clustering; Differential expression testing; Graph analysis; Machine learning; Pseudotemporal ordering; Scalability; Single-cell transcriptomics; Trajectory inference; Visualization.