scanpy
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.
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---
name: scanpy
description: "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."
license: SD-3-Clause license
metadata:
skill-author: K-Dense Inc.
risk: unknown
source: community
---
# Scanpy: Single-Cell Analysis
## Overview
Scanpy is a scalable PHow to Use
Recommended: Install to project (local)
mkdir -p .claude/skills
curl -o .claude/skills/scanpy.md \
https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/scanpy/SKILL.mdSkill is scoped to this project only. Add .claude/skills/ to your .gitignoreif you don't want to commit it.
Alternative: Clone full repo
git clone https://github.com/sickn33/antigravity-awesome-skillsThen reference at skills/scanpy/SKILL.md
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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.
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Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
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Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.
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