API Reference¶
Use this section when you need API-level details beyond the task-oriented guides.
- Generated module/class reference: Reference Summary
- Auto-generated options reference for every track: Aesthetics Reference
Discover options at runtime¶
from plotnado import GenomicFigure, BigWigTrack, list_options
GenomicFigure.available_track_aliases()
GenomicFigure.track_options("bigwig")
GenomicFigure.track_options_markdown("bigwig")
BigWigTrack.options()
BigWigTrack.options_markdown()
list_options(BigWigTrack)
For overlay-specific discovery, ask for the overlay track directly:
GenomicFigure.track_options("overlay")
GenomicFigure.track_options_markdown("overlay")
Each option payload is split into:
track: top-level constructor fields.aesthetics: style model fields (aesthetics={...}or shorthand kwargs).label: label controls (label={...}or shorthand kwargs).
If you want a browsable summary rather than runtime output, start with Aesthetics Reference.
GenomicFigure helper methods: automatic kwargs¶
For helper methods like gf.bigwig(...), kwargs can be provided in shorthand form and PlotNado routes them automatically:
- Track fields: passed directly.
- Aesthetics fields: routed into
aesthetics. - Label fields: routed into
label.
from plotnado import GenomicFigure
gf = GenomicFigure()
gf.bigwig(
"signal.bw",
title="Sample A", # label
title_color="black", # label
style="std", # aesthetics
color="#1f77b4", # aesthetics
alpha=0.8, # aesthetics
)
color_group is a track-level kwarg and works well with gf.autocolor() for consistent sample coloring:
gf = GenomicFigure(theme="publication")
gf.autocolor()
gf.bed("sampleA.bigBed", title="A peaks", color_group="sampleA")
gf.bigwig("sampleA.bw", title="A signal", color_group="sampleA")
Common entry points¶
plotnado.GenomicFigure: high-level composition (add_track,plot,plot_regions,plot_gene,from_template,from_igv_session,to_toml,from_toml).plotnado.Template: YAML model used by the CLI andGenomicFigure.from_template().plotnado.TemplateCompiler: converts aTemplateinto a reusable render plan.plotnado.Theme: built-in or custom visual defaults.plotnado.tracks.*: concrete track classes when you want explicit model construction.plotnado.parse_igv_session: parse an IGV session XML into anIgvSession(.template,.locus,.genome).
Track editing¶
After a figure is built, tracks can be edited in-place.
| Method | Description |
|---|---|
fig["title"] / fig[i] |
Access a track by title (case-insensitive) or index |
fig.update_track(key, **kw) |
Update fields on one track |
fig.update_track(**kw) |
Update all tracks (no key) |
fig.update_track(track_type=…, **kw) |
Bulk update filtered by type |
fig.update_track(group=…, **kw) |
Bulk update filtered by autoscale group |
fig.update_track(where=fn, **kw) |
Bulk update with a predicate |
fig.remove_track(key) |
Remove a track by title or index |
fig.add_track(…, position="top") |
Prepend instead of append |
All editing methods return self for chaining.
For practical usage, prefer Quick Start, Track Catalog, and Recipes.