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.
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---
name: scanpy
description: 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.
license: SD-3-Clause license
metadata:
skill-author: K-Dense Inc.
---
# Scanpy: Single-Cell Analysis
## Overview
Scanpy is a scalable Python How to Use
Recommended: Install to project (local)
mkdir -p .claude/skills
curl -o .claude/skills/scanpy.md \
https://raw.githubusercontent.com/K-Dense-AI/claude-scientific-skills/main/scientific-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/K-Dense-AI/claude-scientific-skillsThen reference at scientific-skills/scanpy/SKILL.md
Related Skills
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.
data-aiscanpy
by sickn33 (Antigravity) · antigravity-awesome-skills
anndata
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.
anndataanndata
by K-Dense-AI · claude-scientific-skills
cellxgene-census
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.
cellxgene-censuscellxgenecensus
by K-Dense-AI · claude-scientific-skills
scvelo
RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.
scveloscvelo
by K-Dense-AI · claude-scientific-skills