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visium

Analyze Visium spatial transcriptomics data with Scanpy, Squidpy, Giotto, or Seurat workflows.

Updated Apr 19, 2026
Search Tags:#spatial-transcriptomics#scanpy#giotto#seurat#spatial-analysis#visium#squidpy
One-click install
npx skills add https://github.com/CHENyiru3/AI-Skills-Collections --skill visium
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: visium
Source: https://github.com/CHENyiru3/AI-Skills-Collections/tree/main/skills-market/compbio/spatial-omics/platforms/visium
Command: npx skills add https://github.com/CHENyiru3/AI-Skills-Collections --skill visium

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visium spatial transcriptomics data require specialized workflows to integrate gene expression with tissue context across platforms. This skill provides a guided approach to processing Visium outputs and extracting meaningful spatial patterns.

Core Features & Use Cases

  • End-to-end Visium data processing from raw outputs to clustering and spatial visualization.
  • Python (Scanpy + Squidpy) workflow for preprocessing, dimensionality reduction, and spatial analysis.
  • R workflow using Giotto or Seurat for spatial mapping and visualization.
  • Use cases across tissue architecture discovery, spot-level clustering, and spatial gene expression patterning.

Quick Start

Load your Visium output into Scanpy with Squidpy and run the standard preprocessing and spatial clustering workflow.

Frequently Asked Questions about visium

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

FAQPage Schema
How do I analyze Visium spatial transcriptomics data to reveal tissue architecture?▼

To analyze Visium spatial transcriptomics data and reveal tissue architecture, apply Python (Scanpy + Squidpy) or R (Giotto or Seurat) workflows to preprocess, visualize, and interpret spatial patterns from raw outputs.

What is the best way to preprocess and cluster Visium spatial gene expression data?▼

The best way to preprocess and cluster Visium spatial gene expression data is using the Python Scanpy with Squidpy workflow, which handles dimensionality reduction, spot-level clustering, and spatial visualization.

Can I use Seurat or Giotto for spatial mapping of Visium outputs in R?▼

Yes, you can use Seurat or Giotto for spatial mapping of Visium outputs in R, as these workflows support spatial visualization and tissue architecture discovery directly from your data.

Do I need Scanpy and Squidpy installed to run spatial analysis on Visium data?▼

Yes, you need Scanpy and Squidpy installed to run the Python spatial analysis workflow on Visium data, or alternatively Giotto or Seurat installed if you prefer the R workflow environment.

Does the Visium spatial analysis workflow support spot-level clustering and spatial patterning?▼

Yes, the Visium spatial analysis workflow supports spot-level clustering and spatial gene expression patterning, enabling tissue architecture discovery through guided end-to-end processing of spatial transcriptomics outputs.

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