bio-data-visualization-circos-plots

Name: bio-data-visualization-circos-plots
Availability: InStock
Author: stellaromics

Generate circular genome visualizations with Circos and pyCircos multi-track plots.

Updated Aug 27, 2026

Search Tags:#genomics #circos #cnv #pycircos #genome-visualization #data-tracks #gene-fusions

Ready to run

npx skills add https://github.com/stellaromics/fast-bioinfo --skill bio-data-visualization-circos-plots

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: bio-data-visualization-circos-plots
Source: https://github.com/stellaromics/fast-bioinfo/tree/main/.claude/agents/spatial-analysis/skills/bio-data-visualization-circos-plots
Command: npx skills add https://github.com/stellaromics/fast-bioinfo --skill bio-data-visualization-circos-plots

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Circos and pyCircos enable researchers to create circular genome visualizations that display multiple data tracks around chromosome ideograms, consolidating complex genomic data into a single, interpretable figure.

Core Features & Use Cases

Circos and pyCircos support multi-track circular genome plots with ideograms, genes, variants, CNVs, and interaction arcs.
Data tracks include scatter, heatmap, links, and density representations, with examples for CNV visualization, gene fusions, Hi-C contacts, and multi-omics summaries.
Provides installation tips, language support (Python, R, Perl), and ready-to-run templates to generate publication-ready figures that can be exported as SVG or PNG.

Quick Start

Create a multi-track circos plot for CNV, fusion, and Hi-C data using Circos or pyCircos and export the figure.

Frequently Asked Questions about bio-data-visualization-circos-plots

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I create multi-track circos plots for CNV and gene fusion data?▼

Create multi-track circos plots by using Circos or pyCircos to arrange scatter, heatmap, link, and density tracks around chromosome ideograms. This consolidates CNV, gene fusion, and Hi-C contact data into a single publication-ready figure exportable as SVG or PNG.

What is the best way to visualize Hi-C contacts and multi-omics summaries together?▼

Visualizing Hi-C contacts and multi-omics summaries together is best done with circular genome plots. Circos and pyCircos map these complex datasets onto parallel tracks around chromosome ideograms, producing an interpretable, publication-ready visualization from a single figure.

Does pyCircos support exporting publication-ready SVG or PNG figures?▼

Yes, pyCircos supports exporting publication-ready figures as SVG or PNG files. The tool provides ready-to-run templates and configuration guidelines to help you generate high-quality circular genome visualizations suitable for academic publishing.

Can I use Circos with Python, R, and Perl for genomic data visualization?▼

Circos can be used with Python, R, and Perl for genomic data visualization. The framework provides language support and installation tips across these environments, allowing you to generate circular plots using your preferred scripting language.

How do I add scatter, heatmap, and density tracks to a circular genome visualization?▼

Add scatter, heatmap, and density tracks to a circular genome visualization by configuring data track layers within Circos or pyCircos. These tracks display variations, CNVs, and density metrics around chromosome ideograms to highlight distinct genomic features simultaneously.

When should I not use circular genome plots for my genomic data?▼

You should avoid circular genome plots when your analysis requires linear coordinate precision or when visualizing small, isolated genomic regions rather than whole-genome overviews. Circos plots are designed for consolidating complex, multi-track genomic relationships into a single circular summary.