giottosuite-local

Orchestrate spatial transcriptomics analysis with Giotto Suite workflows.

1|Updated Dec 3, 2025
One-click install
npx skills add https://github.com/Ketomihine/my_skills --skill giottosuite-local
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: giottosuite-local
Source: https://github.com/Ketomihine/my_skills/tree/main/giottosuite-local
Command: npx skills add https://github.com/Ketomihine/my_skills --skill giottosuite-local

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill unifies the process of analyzing spatial transcriptomics data by providing a turnkey Giotto Suite workflow for data import, processing, and visualization.

Core Features & Use Cases

  • Data import and object creation: load data from Visium, Xenium, or CosMx and build Giotto objects ready for analysis.
  • Spatial analytics pipeline: QC, normalization, dimensionality reduction (PCA/UMAP), clustering, spatial networks, and domain detection.
  • 3D & cross-section workflows: dimensionality reductions, cross-sections, subcellular analyses, and multi-omics integration.
  • Visualization & reporting: generate publication-ready plots and export results with tutorials and references.

Quick Start

Use GiottoSuite to load a Visium dataset, create a Giotto object, run normalization, PCA, clustering, and visualize results.

Frequently Asked Questions about giottosuite-local

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

FAQPage Schema
How do I analyze spatial transcriptomics data from Visium and Xenium platforms?

Spatial transcriptomics analysis of Visium and Xenium data requires loading raw files, creating Giotto objects, and running QC, normalization, and dimensionality reduction. This skill orchestrates that entire pipeline, supporting data import, clustering, and spatial domain detection.

What is the best way to run spatial domain detection using HMRF in R?

Spatial domain detection using HMRF in R involves creating spatial networks and identifying distinct tissue regions. This skill provides a turnkey Giotto Suite workflow to construct spatial networks and execute HMRF for robust spatial domain identification.

Can I perform subcellular spatial analysis and multi-omics integration with Giotto?

Subcellular spatial analysis and multi-omics integration are supported within the Giotto ecosystem. This skill enables researchers to execute 3D workflows, cross-section analyses, subcellular processing, and multi-omics integration directly through Giotto APIs.

How do I generate publication-ready plots for spatial transcriptomics results in R?

Publication-ready plots for spatial transcriptomics results are generated after running dimensionality reduction and clustering. This skill facilitates visualization and reporting by producing high-quality plots and exporting analysis results aligned with Giotto tutorials.

Does this spatial transcriptomics workflow support CosMx data alongside Visium and Xenium?

CosMx data is fully supported alongside Visium and Xenium platforms for spatial transcriptomics analysis. This skill allows researchers to load CosMx datasets, create Giotto objects, and proceed through the standard spatial analytics pipeline.

Why use Giotto Suite for spatial transcriptomics instead of other R workflows?

Giotto Suite unifies spatial transcriptomics analysis by providing a single framework for data import, processing, and visualization. This skill leverages Giotto to orchestrate end-to-end pipelines, ensuring consistent workflows from QC to publication-ready reporting.