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

Genome Biol. 2018 Feb 6;19(1):15. doi: 10.1186/s13059-017-1382-0.


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 ( ). Along with SCANPY, we present ANNDATA, a generic class for handling annotated data matrices ( ).

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

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Expression Profiling / methods*
  • Gene Regulatory Networks
  • Single-Cell Analysis
  • Software*