Individual skill
scanpy
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.
backend/cli/skills/biology/scanpy/SKILL.md
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- Last checked
- Nov 2, 2026
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- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
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- single-cell Declared skill tag
- rna-seq Declared skill tag
- clustering Declared skill tag
- umap Declared skill tag
- bioinformatics Declared skill tag
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# Scanpy: Single-Cell Analysis
## Overview
Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.
## When to Use This Skill
This skill should be used when:
- Analyzing single-cell RNA-seq data (.h5ad, 10X, CSV formats)
- Performing quality control on scRNA-seq datasets
- Creating UMAP, t-SNE, or PCA visualizations
- Identifying cell clusters and finding marker genes
- Annotating cell types based on gene expression