bio-spatial-transcriptomics-spatial-communication
CommunityMap spatial signaling between cell types
System Documentation
What problem does it solve?
Spatial transcriptomics studies generate cell-type maps and spatial coordinates but inferring meaningful cell-cell signaling requires integrating ligand-receptor interactions with spatial proximity. This Skill provides end-to-end guidance to perform ligand-receptor analysis in spatial context using Squidpy, including graph construction, permutation-based testing, and visualization.
Core Features & Use Cases
- Spatially-aware ligand-receptor analysis using Squidpy and Scanpy on annotated spatial transcriptomics data.
- Build spatial neighbor graphs, run permutation-based LR testing, and filter significant interactions.
- Visualize results via heatmaps, network graphs, and spatial expression maps; compare conditions or datasets.
Quick Start
Provide your spatial transcriptomics dataset with cell-type annotations and run a ligand-receptor analysis to identify communicating cell types.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
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Please help me install this Skill: Name: bio-spatial-transcriptomics-spatial-communication Download link: https://github.com/ya-way/cytoclaw-skills/archive/main.zip#bio-spatial-transcriptomics-spatial-communication Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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