Tooluniverse Spatial Transcriptomics

The tooluniverse-spatial-transcriptomics skill enables AI agents to analyze spatial transcriptomics datasets, mapping gene expression patterns directly onto tissue coordinates. It processes complex biological data to reveal how cellular interactions vary across specific anatomical regions within a sample.

When to use it

• Investigating tumor microenvironments to identify distinct cell populations based on their physical location.
• Analyzing brain tissue sections to correlate gene activity with specific neural structures.
• Studying developmental biology by tracking how gene expression shifts across growing tissues.
• Validating single-cell RNA sequencing results by adding spatial context to cellular data.

Key capabilities

• Ingests and processes raw spatial transcriptomics data files.
• Maps gene expression levels onto 2D or 3D tissue coordinates.
• Identifies spatially variable genes within defined regions of interest.
• Visualizes cellular neighborhoods and interaction patterns.

Example prompts

• "Analyze this breast cancer tissue sample to identify clusters of immune cells surrounding tumor regions."
• "Map the expression of neurodevelopmental markers across different layers of the cerebral cortex."
• "Detect spatially variable genes in this liver section that correlate with fibrosis zones."

Tips & gotchas

Ensure your input data includes accurate coordinate metadata, as the tool relies on precise spatial alignment to generate meaningful maps. While effective for pattern recognition, interpret results alongside traditional histology to confirm biological context.