skills.rest
ya-way
ya-wayCOMMUNITY
Explore all skills by this author →
GitHub

bio-data-visualization-multipanel-figures

Assemble individual plots into publication-ready multi-panel figures with shared legends.

Updated Mar 30, 2026
Search Tags:#visualization#ggplot2#publication-figures#gridspec#multipanel#patchwork#cowplot
One-click install
npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-data-visualization-multipanel-figures
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-data-visualization-multipanel-figures
Source: https://github.com/ya-way/cytoclaw-skills/tree/main/workspace/skills/bio-data-visualization-multipanel-figures
Command: npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-data-visualization-multipanel-figures

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Combining multiple plots from R (patchwork/cowplot) or Python (GridSpec) into a single publication-ready figure can be tedious, requiring careful alignment, consistent styling, and unified legends. This Skill streamlines the process by providing guidance and patterns to assemble panels, label them clearly, and export high-quality figures ready for journals.

Core Features & Use Cases

  • Cross-language layout orchestration using patchwork, cowplot, and matplotlib GridSpec to assemble panels.
  • Support for common publication layouts (2x2 grids, spanning panels, insets) with shared legends and panel labels.
  • Export options for high-resolution figures (PDF/PNG) suitable for manuscript submission; include examples for typical biology workflows.

Quick Start

Tell your AI to assemble a 2x2 panel figure from four individual plots with a shared legend.

Frequently Asked Questions about bio-data-visualization-multipanel-figures

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

FAQPage Schema
How do I combine multiple plots into a single publication-ready figure?▼

You can combine individual plots into a publication-ready figure by aligning and assembling them into multi-panel layouts. This Skill provides patterns to orchestrate panel assembly, apply shared legends, and export high-resolution files for journal submission.

Can I use GridSpec with patchwork to create multi-panel layouts?▼

GridSpec and patchwork are both supported for creating multi-panel layouts, but they belong to different environments. GridSpec orchestrates Python matplotlib panels, while patchwork and cowplot handle R plot assembly.

What is the best way to add a shared legend to a multi-panel figure?▼

Adding a shared legend to a multi-panel figure involves extracting the legend from one plot and positioning it globally across the assembled grid. This Skill provides layout patterns to unify legends across panels in both R and Python workflows.

How do I export high-resolution multi-panel figures for journal submission?▼

Exporting high-resolution multi-panel figures requires configuring specific output settings for PDF or PNG formats. This Skill guides you through setting export dimensions and resolutions to meet journal submission standards.

Does this approach support complex publication layouts like spanning panels and insets?▼

Yes, the approach supports common publication layouts including 2x2 grids, spanning panels, and insets. You can assemble these complex structures while maintaining consistent styling and clear panel labels.

Why does aligning multiple plots into one figure require careful styling?▼

Aligning multiple plots requires careful styling because inconsistent axes, varying legends, and mismatched dimensions disrupt the visual flow. Assembling panels with unified legends and clear labels ensures a cohesive, publication-grade visual.

Related Skills

Explore More Data & Analytics Skills→
StarlitnightlyStarlitnightly
1.2k

data-viz-plots

Generate publication-quality plots with matplotlib and seaborn.

Community
Advanced
ovachieverovachiever
52

scientific-visualization

Generate publication-ready scientific figures with matplotlib, seaborn, and plotly.

Community
Advanced
AidenSbVevoAidenSbVevo
1

viz

Generate production-ready data visualizations using Python and R plotting libraries.

Community
Advanced
SunS1eep1ngSunS1eep1ng

nature-figure

Automate publication-quality scientific figure creation with Python or R.

Community
Advanced