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spatial-omics-analysis

ToolUniverse workflow — Spatial Omics Analysis

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---
name: tooluniverse-spatial-omics-analysis
description: Computational analysis framework for spatial multi-omics data integration. Given spatially variable genes (SVGs), spatial domain annotations, tissue type, and disease context from spatial transcriptomics/proteomics experiments (10x Visium, MERFISH, DBiTplus, SLIDE-seq, etc.), performs comprehensive biological interpretation including pathway enrichment, cell-cell interaction inference, druggable target identification, immune microenvironment characterization, and multi-modal integration. Produces a detailed markdown report with Spatial Omics Integration Score (0-100), domain-by-domain characterization, and validation recommendations. Uses 70+ ToolUniverse tools across 9 analysis phases. Use when users ask about spatial transcriptomics analysis, spatial omics interpretation, tissue heterogeneity, spatial gene expression patterns, tumor microenvironment mapping, tissue zonation, or cell-cell communication from spatial data.
---

# Spatial Multi-Omics Analysis Pipeline

Comprehensive biological interpretation of spatial omics data. Transforms spatially variable genes (SVGs), domain annotations, and tissue context into actionable biological insights covering pathway enrichment, cell-cell interactions, druggable targets, immune microenvironment, and multi-modal integration.

**KEY PRINCIPLES**:
1. **Report-first approach** - Create report file FIRST, then populate progressively
2. **Domain-by-domain analysis** - Characterize each spatial region independently before comparison
3. **Gene-list-centric** - Analyze user-provided SVGs and marker genes with ToolUniverse databases
4. **Biological interpretation** - Go beyond statistics to explain biological meaning of spatial patterns