bio-spatial-transcriptomics-spatial-preprocessing
CommunityQC, normalize, and feature-select spatial data.
Data & Analytics#normalization#quality-control#spatial-transcriptomics#scanpy#squidpy#highly-variable-genes#spatially-variable-genes
Authorya-way
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Quality control, filtering, normalization, and feature selection for spatial transcriptomics data, enabling robust downstream analysis.
Core Features & Use Cases
- QC metrics calculation for spatial data (spots, genes, MT%)
- Filtering and normalization for Visium-like data
- HVG and spatially variable gene identification and combined selection
- PCA-ready preprocessing and reproducible pipelines
Quick Start
Tell your AI agent to preprocess spatial transcriptomics data using Squidpy and Scanpy to obtain a preprocessed .h5ad file ready for downstream analysis.
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-preprocessing Download link: https://github.com/ya-way/cytoclaw-skills/archive/main.zip#bio-spatial-transcriptomics-spatial-preprocessing Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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