| name | nicheformer-spatial-agent |
| description | Foundation model-powered spatial transcriptomics analysis leveraging 53M+ spatially resolved cells for cellular architecture modeling and tissue niche discovery. |
Nicheformer Spatial Agent
The Nicheformer Spatial Agent leverages the Nicheformer foundation model, trained on over 53 million spatially resolved cells, to model cellular architecture and tissue microenvironments with unprecedented accuracy. It enables spatial context-aware cell type annotation, niche discovery, and tissue organization analysis.
When to Use This Skill
- When analyzing spatial transcriptomics requiring deep cellular context understanding.
- For identifying tissue niches and cellular neighborhoods.
- To predict cell-cell interactions based on spatial proximity.
- When transferring annotations from atlases to new spatial data.
- For studying tissue architecture and organization patterns.
Core Capabilities
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Spatial Context Embeddings: Generate embeddings that capture both gene expression and spatial context.
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Niche Discovery: Identify recurrent cellular neighborhoods across tissues.
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Zero-Shot Cell Type Annotation: Transfer cell type labels without retraining.
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Spatial Perturbation Prediction: Predict effects of removing cell types from niches.
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Cross-Tissue Transfer: Apply models trained on one tissue to another.
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Tissue Architecture Analysis: Quantify spatial organization patterns.
Model Architecture
| Component | Description | Parameters |
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