bio-spatial-transcriptomics-spatial-deconvolution
CommunitySpatial cell-type deconvolution from scRNA-seq references
Data & Analytics#spatial-transcriptomics#scrna-seq#tangram#spatial-deconvolution#cell-type-proportions#cell2location#rctd
Authorya-way
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Estimate cell-type proportions in spatial transcriptomics spots by leveraging reference scRNA-seq data with methods like cell2location, RCTD, SPOTlight, or Tangram.
Core Features & Use Cases
- Reference-based deconvolution: infer per-spot cell-type proportions using established methods (cell2location, RCTD, SPOTlight, Tangram).
- Versatile applicability: supports Visium-like datasets across tissues, enabling integrated multi-method workflows and cross-method comparisons.
- Example Use Case: map tumor microenvironment composition in spatial tissue sections to identify dominant cell-type neighborhoods.
Quick Start
Load your spatial data and scRNA-seq reference, then run a chosen deconvolution method to obtain per-spot cell-type proportions.
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-deconvolution Download link: https://github.com/ya-way/cytoclaw-skills/archive/main.zip#bio-spatial-transcriptomics-spatial-deconvolution Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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