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alterlab-scientific-viz

Apply standardized styles and colorblind-safe palettes to scientific plots for journal publication.

58|9|Updated Mar 16, 2026
Search Tags:#data-visualization#publication-figures#multi-panel#journal-guidelines#colorblind-palettes#figure-export
One-click install
npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-scientific-viz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alterlab-scientific-viz
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/visualization/alterlab-scientific-viz
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-scientific-viz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, numpy, PyPDF2, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Part of the AlterLab Academic Skills suite helps researchers produce publication-ready figures that comply with journal guidelines, reducing manual formatting time and ensuring consistency across panels and styles.

Core Features & Use Cases

  • Multi-panel figure creation with consistent styling across all panels.
  • Colorblind-safe palettes, typography presets, and per-journal styling to meet Nature/Science/Cell guidelines.
  • Export-ready outputs in vector and high-resolution formats (PDF, EPS, SVG, TIFF) for manuscripts.
  • Use Case: Quickly assemble a 3- or 4-panel figure combining time-series, bar plots, and heatmaps with a unified visual language, then export to journal-ready dimensions.

Quick Start

Configure the publication style, build multi-panel visuals using the provided templates, and export in required formats with a single instruction.

Frequently Asked Questions about alterlab-scientific-viz

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

FAQPage Schema
How do I create publication-ready figures that meet Nature or Science journal guidelines?▼

Publication-ready figures meeting Nature or Science guidelines are created by applying standardized styles, colorblind-friendly palettes, typography presets, and journal-specific sizing to scientific plots using built-in style presets.

How do I build multi-panel layouts in matplotlib with consistent styling across all subplots?▼

Multi-panel layouts with consistent styling are built by applying unified visual language across panels, combining time-series, bar plots, and heatmaps, then exporting to journal-ready dimensions.

Can I export scientific plots to vector and high-resolution formats like PDF, EPS, SVG, and TIFF for manuscripts?▼

Scientific plots can be exported to vector and high-resolution formats including PDF, EPS, SVG, and TIFF for manuscripts using the provided export utilities.

Does this scientific visualization workflow support colorblind-safe palettes for multi-panel figures?▼

Colorblind-safe palettes are supported for multi-panel figures to ensure accessibility and compliance with publication standards across all panels.

What's the best way to assemble a 4-panel figure combining different plot types with a unified visual style?▼

Assembling a 4-panel figure with a unified visual style is done by using the provided templates to combine different plot types like time-series, bar plots, and heatmaps with consistent typography and palettes.

Do I need matplotlib and numpy to generate journal-specific scientific visuals?▼

Matplotlib and numpy are required dependencies to generate journal-specific scientific visuals, along with PyPDF2 for handling PDF outputs.

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