Plotting: pl

The plotting module scanpy.pl largely parallels the tl.* and a few of the pp.* functions. For most tools and for some preprocessing functions, you’ll find a plotting function with the same name.

See Core plotting functions for an overview of how to use these functions.

Note

See the Settings section for all important plotting configurations.

Generic

pl.scatter	Scatter plot along observations or variables axes.
pl.heatmap	Heatmap of the expression values of genes.
pl.dotplot	Makes a dot plot of the expression values of var_names.
pl.tracksplot	In this type of plot each var_name is plotted as a filled line plot where the y values correspond to the var_name values and x is each of the cells.
pl.violin	Violin plot.
pl.stacked_violin	Stacked violin plots.
pl.matrixplot	Creates a heatmap of the mean expression values per group of each var_names.
pl.clustermap	Hierarchically-clustered heatmap.
pl.ranking	Plot rankings.
pl.dendrogram	Plots a dendrogram of the categories defined in groupby.

Classes

These classes allow fine tuning of visual parameters.

pl.DotPlot	Allows the visualization of two values that are encoded as dot size and color.
pl.MatrixPlot	Allows the visualization of values using a color map.
pl.StackedViolin	Stacked violin plots.

Preprocessing

Methods for visualizing quality control and results of preprocessing functions.

pl.highest_expr_genes	Fraction of counts assigned to each gene over all cells.
pl.filter_genes_dispersion	Plot dispersions versus means for genes.
pl.highly_variable_genes	Plot dispersions or normalized variance versus means for genes.
pl.scrublet_score_distribution	Plot histogram of doublet scores for observed transcriptomes and simulated doublets.

Tools

Methods that extract and visualize tool-specific annotation in an AnnData object. For any method in module tl, there is a method with the same name in pl.

PCA

pl.pca	Scatter plot in PCA coordinates.
pl.pca_loadings	Rank genes according to contributions to PCs.
pl.pca_variance_ratio	Plot the variance ratio.
pl.pca_overview	Plot PCA results.

Embeddings

pl.tsne	Scatter plot in tSNE basis.
pl.umap	Scatter plot in UMAP basis.
pl.diffmap	Scatter plot in Diffusion Map basis.
pl.draw_graph	Scatter plot in graph-drawing basis.
pl.spatial	Scatter plot in spatial coordinates.
pl.embedding	Scatter plot for user specified embedding basis (e.g. umap, pca, etc).

Compute densities on embeddings.

pl.embedding_density

Plot the density of cells in an embedding (per condition).

Branching trajectories and pseudotime, clustering

Visualize clusters using one of the embedding methods passing color='louvain'.

pl.dpt_groups_pseudotime	Plot groups and pseudotime.
pl.dpt_timeseries	Heatmap of pseudotime series.
pl.paga	Plot the PAGA graph through thresholding low-connectivity edges.
pl.paga_path	Gene expression and annotation changes along paths in the abstracted graph.
pl.paga_compare	Scatter and PAGA graph side-by-side.

Marker genes

pl.rank_genes_groups	Plot ranking of genes.
pl.rank_genes_groups_violin	Plot ranking of genes for all tested comparisons.
pl.rank_genes_groups_stacked_violin	Plot ranking of genes using stacked_violin plot (see stacked_violin())
pl.rank_genes_groups_heatmap	Plot ranking of genes using heatmap plot (see heatmap())
pl.rank_genes_groups_dotplot	Plot ranking of genes using dotplot plot (see dotplot())
pl.rank_genes_groups_matrixplot	Plot ranking of genes using matrixplot plot (see matrixplot())
pl.rank_genes_groups_tracksplot	Plot ranking of genes using heatmap plot (see heatmap())

Simulations

pl.sim

Plot results of simulation.