spatial-condition
OfficialCompare experimental conditions in spatial data.
Data & Analytics#DESeq2#spatial transcriptomics#differential expression#pseudobulk#condition comparison#multi-sample statistics
AuthorTianGzlab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the challenge of comparing experimental conditions in spatial transcriptomics data, preventing common pitfalls like pseudoreplication and ensuring robust statistical analysis.
Core Features & Use Cases
- Pseudobulk Differential Expression: Performs proper multi-sample pseudobulk differential expression analysis.
- Statistical Rigor: Utilizes DESeq2-style statistics or Wilcoxon rank-sum tests on pseudobulk values for accurate results.
- Use Case: Analyze spatial transcriptomics data from healthy and diseased tissue samples to identify genes that are differentially expressed between the two conditions, specifically within different annotated regions of the tissue.
Quick Start
Compare the 'treatment' and 'control' conditions in your spatial data using the 'sample_id' column for sample identification.
Dependency Matrix
Required Modules
scanpyscipypydeseq2
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-condition Download link: https://github.com/TianGzlab/OmicsClaw/archive/main.zip#spatial-condition Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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