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scanpy-single-cell-analysis

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Streamlined Scanpy workflows for .h5ad data

Data & Analytics#quality control#single-cell#clustering#h5ad#scvi-tools#scanpy
AuthorKetomihine
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill provides a comprehensive, reproducible workflow for analyzing single-cell RNA-seq data stored in .h5ad format using Scanpy within a dedicated conda environment.

Core Features & Use Cases

  • Data loading and QC: Efficiently load .h5ad files, assess quality metrics, and filter cells based on gene counts and mitochondrial content.
  • Normalization, feature selection, and visualization: Normalize data, identify highly variable genes, and prepare data for downstream analyses, including UMAP visualization.
  • Clustering and integration: Construct neighborhood graphs, perform clustering, identify marker genes, and optionally integrate data across batches using scvi-tools for batch correction.

Quick Start

Activate the Scanpy conda environment and run a standard workflow to load an .h5ad file and begin analysis. For example:

  • conda activate scanpy
  • python -c "import scanpy as sc; adata = sc.read_h5ad('path/to/file.h5ad'); print(adata.shape)"

Dependency Matrix

Required Modules

None required

Components

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: scanpy-single-cell-analysis
Download link: https://github.com/Ketomihine/my_skills/archive/main.zip#scanpy-single-cell-analysis

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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