Skip to main content
Fig. 1 | Genome Biology

Fig. 1

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

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

Back to article page