bio-spatial-transcriptomics-spatial-statistics
CommunityUncover spatial patterns in tissue transcriptomics.
Authorya-way
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Researchers need to quantify and interpret spatial patterns in spatial transcriptomics data to identify spatially variable genes and interactions.
Core Features & Use Cases
- Compute Moran's I and Geary's C to identify spatial autocorrelation across genes or features.
- Co-occurrence and neighborhood enrichment analyses to understand how cell types or clusters co-localize in tissue space.
- Scalability and workflow notes: easy integration with AnnData; subset to HVGs for speed.
Quick Start
Tell me how to run spatial statistics on my spatial transcriptomics data using Squidpy.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: bio-spatial-transcriptomics-spatial-statistics Download link: https://github.com/ya-way/cytoclaw-skills/archive/main.zip#bio-spatial-transcriptomics-spatial-statistics Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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