spatial-statistics
OfficialAnalyze spatial patterns in omics data.
Data & Analytics#spatial statistics#spatial autocorrelation#neighborhood enrichment#moran's i#ripley's k#omics analysis#squidpy
AuthorTianGzlab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates complex spatial statistics analysis, moving beyond manual command execution to provide structured insights into spatial patterns within omics data.
Core Features & Use Cases
- Neighborhood Enrichment: Quantify how often cell types co-localize in spatial proximity.
- Spatial Autocorrelation: Measure global and local patterns for genes (Moran's I, Getis-Ord Gi*).
- Point Pattern Analysis: Analyze cluster distribution using Ripley's L function.
- Use Case: Identify if immune cells are clustered around tumor cells in a spatial transcriptomics dataset, or if specific gene expressions form hot or cold spots within a tissue.
Quick Start
Calculate neighborhood enrichment for the annotated clusters in the provided AnnData file.
Dependency Matrix
Required Modules
squidpyscanpyanndatamatplotlibnumpypandasesdalibpysal
Components
scriptsreferences
💻 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: spatial-statistics Download link: https://github.com/TianGzlab/OmicsClaw/archive/main.zip#spatial-statistics Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 223,000+ vetted skills library on demand.