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

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

F Alexander Wolf  1 , Philipp Angerer  2 , Fabian J Theis  3   4
Affiliations

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

F Alexander Wolf et al. Genome Biol. .

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 ).

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

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Conflict of interest statement

Ethics approval and consent to participate

Ethics approval was not applicable for this study.

Competing interests

None of the authors declare competing interests.

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Figures

Fig. 1
Fig. 1
aSCANPY’s analysis features. We use the example of 68,579 peripheral blood mononuclear cells of [6]. We regress out confounding variables, normalize, and identify highly variable genes. TSNE and graph-drawing (Fruchterman–Reingold) visualizations show cell-type annotations obtained by comparisons with bulk expression. Cells are clustered using the Louvain algorithm. Ranking differentially expressed genes in clusters identifies the MS4A1 marker gene for B cells in cluster 7, which agrees with the bulk labels. We use pseudotemporal ordering from a root cell in the CD34+ cluster and detect a branching trajectory, visualized with TSNE and diffusion maps. b Speedup over CELL RANGER R kit. We consider representative steps of the analysis [6]. c Visualizing and clustering 1.3 million cells. The data, brain cells from E18 mice, are publicly available from 10x Genomics. PCA = principal component analysis, DC = diffusion component
See this image and copyright information in PMC

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