bio-data-visualization-genome-tracks
OfficialVisualize multi-track genomic data across tools.
Education & Research#bioinformatics#genomics#data-visualization#pygenometracks#genome-tracks#gviz#igv.js
Authorstellaromics
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Visual scientists often need to compare multiple genomic data layers (coverage, peaks, genes) across several visualization platforms in a single, coherent view. This skill provides a unified approach to generating genome track plots using pyGenomeTracks (Python), Gviz (R), and IGV.js (web), enabling reproducible visuals across analyses.
Core Features & Use Cases
- Multi-tool genome track visualizations using pyGenomeTracks, Gviz, and IGV.js for cross-platform compatibility.
- Flexible data inputs supporting BigWig, BED, and GTF/GFF formats for integrated views of coverage, peaks, and gene models.
- Use Case: produce publication-ready plots for locus-centric studies or comparative genomics across samples.
Quick Start
Configure a genome track plot for your region and generate figures using pyGenomeTracks, Gviz, or IGV.js.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: bio-data-visualization-genome-tracks Download link: https://github.com/stellaromics/fast-bioinfo/archive/main.zip#bio-data-visualization-genome-tracks Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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