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SP
spatial-transcriptomics-analysis
Maintainer FreedomIntelligence · Last updated April 1, 2026
This skill provides automated analysis capabilities for Spatial Transcriptomics data, specifically designed for 10x Visium and Xenium platforms. It enables the integration of histological data with gene expression profiles to uncover spatial organi.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/spatial-transcriptomics-analysis
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- Version: 1.0.0 Author: MD BABU MIA, PhD Date: February 2026.
- This skill provides automated analysis capabilities for Spatial Transcriptomics data, specifically designed for 10x Visium and Xenium platforms. It enables the integration of histological data with gene expression profiles to uncover spatial organization of cell types.
Source Doc
Excerpt From SKILL.md
Capabilities
- Data Loading: Supports Spaceranger output (h5, images).
- QC & Preprocessing: Spatial QC metrics, normalization.
- Spatial Variable Features: Identification of spatially variable genes (SVGs) using Moran's I and Geary's C.
- Deconvolution: Interface for cell type deconvolution (mapping scRNA-seq to spatial).
- Visualization: Interactive spatial plots overlaying gene expression on tissue images.
Usage
from Skills.Genomics.Spatial_Transcriptomics.spatial_analyzer import SpatialAnalyzer
## Initialize
sa = SpatialAnalyzer(data_path="./data/visium_sample1")
Use cases
- Use spatial-transcriptomics-analysis for single-cell or spatial omics analysis.
- Apply spatial-transcriptomics-analysis to clustering, integration, or trajectory workflows.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
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