skills.rest
galeep
galeepCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

scanpy

Automates scRNA-seq analysis including QC, normalization, clustering, and visualization with AnnData and scanpy.

Updated May 17, 2026
Search Tags:#data analysis#single-cell RNA-seq#bioinformatics#anndata#scanpy
One-click install
npx skills add https://github.com/galeep/plugin-place --skill scanpy-galeep
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scanpy
Source: https://github.com/galeep/plugin-place/tree/main/plugins/sci-bioinformatics-genomics/skills/scanpy
Command: npx skills add https://github.com/galeep/plugin-place --skill scanpy-galeep

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scanpy, anndata, scvi-tools, dask, rapids-singlecell, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for analyzing single-cell RNA-seq data, including quality control, normalization, dimensionality reduction, clustering, and visualization.

Core Features & Use Cases

  • Quality Control: Perform various checks on your data to ensure its quality.
  • Normalization: Normalize your data to improve analysis results.
  • Dimensionality Reduction: Reduce the dimensionality of your data using PCA, UMAP, or t-SNE.
  • Clustering: Identify clusters of cells based on their features.
  • Visualization: Visualize your data in various ways, such as UMAP plots, t-SNE plots, and heatmaps.
  • Use Case: If you have single-cell RNA-seq data and want to perform quality control, identify clusters of cells, and visualize your data, this Skill can help you achieve those goals.

Quick Start

Load your single-cell RNA-seq data into the Scanpy Skill using the following command:

load your_data.h5ad

Frequently Asked Questions about scanpy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform quality control and clustering on single-cell RNA-seq data?▼

To analyze single-cell RNA-seq data, you can automate quality control, normalization, dimensionality reduction, clustering, and visualization using anndata structures and specialized bioinformatics libraries.

Can I visualize single-cell RNA-seq clustering results using UMAP or t-SNE plots?▼

Yes, visualizing single-cell RNA-seq data is supported through UMAP plots, t-SNE plots, and heatmaps. These visualizations help identify clusters of cells based on their features after dimensionality reduction.

Does single-cell RNA-seq analysis work with dask and rapids-singlecell for large datasets?▼

Single-cell RNA-seq analysis can leverage dask and rapids-singlecell dependencies. These libraries provide scalable processing for vast amounts of cellular data, essential for demanding biological research workflows.

Do I need anndata and scvi-tools to normalize single-cell RNA-seq data?▼

You need Python and anndata to load your_data.h5ad files for single-cell RNA-seq analysis. The scvi-tools library is also included as a dependency to support various normalization and analysis tasks.

What is the best way to load h5ad files for single-cell RNA-seq dimensionality reduction?▼

The best way to load h5ad files for single-cell RNA-seq dimensionality reduction is by using anndata structures. Once loaded, you can apply PCA, UMAP, or t-SNE to reduce the dimensionality of your data.

Related Skills

Explore More Data & Analytics Skills→
CHENyiru3CHENyiru3

anndata

Organize annotated single-cell data matrices using the AnnData structure.

Community
Advanced
tondevreltondevrel
19

scanpy

Analyze single-cell gene expression data with AnnData and scRNA-seq workflows.

Community
Advanced
KetomihineKetomihine
1

rapids-singlecell-complete

Accelerate single-cell RNA-seq preprocessing and clustering on AnnData with RAPIDS.

Community
Advanced
MubasherMohammedMubasherMohammed

bioconductor-bridge

Recommend Bioconductor packages and workflows for bioinformatics analysis tasks.

Community
Intermediate