bio-data-visualization-circos-plots
Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.
npx skills add BioTender-max/awesome-bio-agent-skills --skill circos-plots --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: circlize 0.4.16+ (R), pyCirclize 1.4+ (Python), Circos 0.69-9 (Perl CLI), ComplexHeatmap 2.18+ (uses circlize for color mapping). Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` - Python: `pip show <package>` then `help(module.function)` If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Circular Genome Plots (Circos) **"Make a circos plot"** -> Render genome chromosomes around a circle with stacked tracks (histogram, scatter, heatmap) and arcs/chords showing interactions. Krzywinski 2009 *Genome Res* 19:1639 introduced the genre for genome-scale comparative views. The single decision that matters: **does the circular layout convey meaning that Cartesian cannot?** - R: `circlize::circos.initializeWithIdeogram` + `circos.genomicTrack*` (Gu 2014) - Python: `pyCirclize.Gcircle` - CLI: Circos (Perl); config-driven; most flexible but steepest learning ## The Single Most Important Modern Insight -- Circular Plots Often Hide What Cartesian
- Version Compatibility
- circlize (R) — Modern Default
- The circos.clear() Trap
- pyCirclize (Python)
- Circos CLI (Perl) — Most Powerful, Steepest Curve
- Decision Tree by Use Case
- Ideogram + Karyogram Without Circos
- Per-Method Failure Modes
- circos.clear() forgotten in a loop
- Using circular when Cartesian would be better
- Too many links produce a black blob
- Sector ordering arbitrary
- Wrong species ideogram
- Ideogram covers data track
circos -conf circos.conf -outputfile output.png
What does the bio-data-visualization-circos-plots skill do?
Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill circos-plots --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.