data-viz-plots

Create publication-quality matplotlib and seaborn plots from AnnData and pandas inputs.

32|5|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/omicverse/omicclaw --skill data-viz-plots-omicverse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-viz-plots
Source: https://github.com/omicverse/omicclaw/tree/main/src/omicverse_skills/skills/data-viz-plots
Command: npx skills add https://github.com/omicverse/omicclaw --skill data-viz-plots-omicverse

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researchers and analysts often need publication-ready visualizations but face fragmented examples, inconsistent styling, and cloud-dependent tools that limit reproducibility; this Skill provides deterministic, locally executed plotting recipes to generate consistent, high-quality figures for analysis and publication.

Core Features & Use Cases

  • Scatter, density, and UMAP/tSNE projections for cluster visualization and exploratory analysis.
  • Heatmaps, violin/box plots, dot plots, bar charts with error bars, and volcano plots for gene expression and differential analysis.
  • Multi-panel figure assembly, custom color palettes, high-resolution export (PNG/SVG/PDF), and basic defensive checks for input validity.
  • Use cases include QC metric visualization, marker gene dotplots, publication figures combining embeddings and expression matrices, and quick EDA plots for notebooks.

Quick Start

Generate a publication-quality UMAP scatter and gene expression heatmap from my AnnData or pandas DataFrame, label clusters, and save high-resolution PNG and SVG files.

Frequently Asked Questions about data-viz-plots

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

FAQPage Schema
How do I create publication-quality UMAP scatter plots from AnnData?▼

Generate publication-quality UMAP scatter plots from AnnData using locally executed matplotlib and seaborn recipes that label clusters and export high-resolution PNG, SVG, and PDF files for papers and presentations.

Can I visualize gene expression heatmaps and volcano plots for differential analysis?▼

Visualize gene expression heatmaps and volcano plots for differential analysis using seaborn recipes that produce consistent, high-quality figures locally from your pandas or AnnData inputs.

Does this plotting approach work with pandas DataFrames and AnnData inputs?▼

This plotting approach works with both pandas DataFrames and AnnData inputs, executing locally to generate exploratory data analysis plots and publication-ready figures without cloud dependencies.

What is the best way to assemble multi-panel figures for scientific publications?▼

Assemble multi-panel scientific publication figures using deterministic, locally executed plotting recipes that combine embeddings and expression matrices with custom color palettes and high-resolution export formats.

How do I export high-resolution SVG and PDF files for matplotlib visualizations?▼

Export high-resolution SVG, PNG, and PDF files for matplotlib visualizations by applying configurable layout options and color palettes to generate publication-ready outputs locally from your scientific data.