Rendering Backends

pyoncoplot has two rendering backends:

Plotly for interactive output.
Matplotlib for deterministic static output.

Plotly

Use Plotly when you want hover labels, interactive inspection, and HTML export.

result = oncoplot(
    mutations,
    gene_col="gene",
    sample_col="sample",
    mutation_type_col="mutation_type",
    tooltip_col="tooltip",
    backend="plotly",
)

result.save("oncoplot.html")

Plotly output supports copy_on_click:

Value	Copied value
`"sample"`	clicked sample identifier
`"gene"`	clicked gene identifier
`"tooltip"`	clicked tooltip text
`"mutation_type"`	clicked mutation type
`"nothing"`	disables clipboard behavior

Clipboard behavior is inserted into exported HTML via navigator.clipboard.writeText.

Matplotlib

Use Matplotlib when you need PNG, SVG, PDF, deterministic gallery images, or static figures for manuscripts.

result = oncoplot(
    mutations,
    gene_col="gene",
    sample_col="sample",
    mutation_type_col="mutation_type",
    backend="matplotlib",
)

result.save("oncoplot.svg")

Matplotlib currently has the richest static layout support for:

stacked TMB bars.
right-side gene bars with percentage labels.
numeric metadata bars.
separate metadata legends.
compact tile borders and row separators.

Choosing A Backend

Need	Recommended backend
exploratory browser plot	Plotly
hover and click-to-copy	Plotly
standalone HTML	Plotly
PNG/SVG/PDF figure	Matplotlib
deterministic gallery recreation	Matplotlib
manuscript-style static output	Matplotlib

Backend Support Matrix

Feature	Plotly	Matplotlib
mutation grid	interactive markers with hover and linked selection	static tile grid
TMB totals	bar trace; log and scientific tick formatting supported	bar axis; log labels and scientific tick formatting supported
TMB subtype legends	`TMB: <subtype>` entries when custom stacked TMB is rendered	separate `TMB Type` legend when custom stacked TMB is rendered
metadata display	heatmap strip with prettified hover labels and shared interactive legend	heatmap or mini-bar strip with separate metadata legends
image export	HTML built in; image export needs the `export` extra	PNG, SVG, PDF, and other `savefig` formats
copy-on-click	supported in exported HTML	not applicable to static figures
static layout controls	useful font, legend, marker, and axis controls	richest support for tile dimensions, metadata bars, font faces, and separate legend layout

The interactive argument is a convenience alias:

oncoplot(..., interactive=True)   # backend="plotly"
oncoplot(..., interactive=False)  # backend="matplotlib"