spatial-deconv
OfficialUncover cell types in spatial data.
Data & Analytics#data analysis#bioinformatics#cell type#deconvolution#spatial transcriptomics#spatial biology
AuthorTianGzlab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the complex process of identifying and quantifying different cell types within spatial transcriptomics data, providing crucial insights into tissue architecture and cellular interactions.
Core Features & Use Cases
- Multi-Method Support: Integrates 8 leading deconvolution algorithms (FlashDeconv, Cell2Location, RCTD, DestVI, Stereoscope, Tangram, SPOTlight, CARD).
- Unified Interface: Provides a consistent command-line interface for all methods, simplifying workflow integration.
- Use Case: Analyze a spatial transcriptomics dataset to determine the proportion of immune cells, stromal cells, and tumor cells in each spatial spot, enabling a deeper understanding of the tumor microenvironment.
Quick Start
Run cell type deconvolution on your spatial data using the default FlashDeconv method.
Dependency Matrix
Required Modules
flashdeconvscanpyanndatanumpypandasscipymatplotlibrpy2scvitorchtangramcell2location
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-deconv Download link: https://github.com/TianGzlab/OmicsClaw/archive/main.zip#spatial-deconv Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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