This tutorial is still under construction

Tutorial 4: Plotting

Generate publication-ready plots with scpviz. — generate abundance plots, PCA/UMAP, clustermaps, raincloud, volcano plots.

Most plotting functions accept a matplotlib.axes.Axes object as the first argument, allowing seamless integration into multi-panel figures.

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Abundance Plots

pdata.plot_abundance(
    namelist=["ACTB", "GAPDH"],
    classes="condition",
    order=["control", "treated"]
)

The plot_abundance() function automatically selects between barplots and violin plots (with inner points) depending on the number of samples per group.

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PCA and UMAP

pdata.plot_pca(classes="celltype")
pdata.plot_umap(classes="condition")

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Clustermap

pdata.plot_clustermap(namelist=["TP53", "VIM", "MAPT"], classes="condition")

🎨 Colors automatically follow sample classes, but you can customize palettes.