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tooluniverse-spatial-transcriptomics

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Analyze spatial transcriptomics data to map gene expression in tissue architecture. Supports 10x Visium, MERFISH, seqFISH, Slide-seq, and imaging-based platforms. Performs spatial clustering, domain identification, cell-cell proximity analysis, spatial gene expression patterns, tissue architecture mapping, and integration with single-cell data. Use when analyzing spatial transcriptomics datasets, studying tissue organization, identifying spatial expression patterns, mapping cell-cell interactions in tissue context, characterizing tumor microenvironment spatial structure, or integrating spatial and single-cell RNA-seq data for comprehensive tissue analysis.

When to use

• User has spatial transcriptomics data (Visium, MERFISH, seqFISH, etc.)
• Questions about tissue architecture or spatial organization
• Spatial gene expression pattern analysis
• Cell-cell proximity or neighborhood analysis requests
• Tumor microenvironment spatial structure questions
• Integration of spatial with single-cell data
• Spatial domain identification
• Tissue morphology correlation with expression

When not to use

• **Resolution**: Visium spots contain multiple cells (not single-cell)
• **Gene coverage**: Imaging methods have limited gene panels
• **3D structure**: Most platforms are 2D sections
• **Tissue quality**: Requires well-preserved tissue for imaging
• **Computational**: Large datasets require significant memory
• **Reference dependency**: Deconvolution quality depends on scRNA-seq reference

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