scanpy

Analyze single-cell RNA-seq data with quality control, clustering, and differential expression.

Updated Mar 10, 2026

Search Tags:#data analysis #bioinformatics #genomics #single-cell #scanpy #scrna-seq

Ready to run

npx skills add https://github.com/Yezez9/Research-Agent --skill scanpy-yezez9

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scanpy
Source: https://github.com/Yezez9/Research-Agent/tree/main/scientific-skills/scanpy
Command: npx skills add https://github.com/Yezez9/Research-Agent --skill scanpy-yezez9

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the complex process of analyzing single-cell RNA-seq data, enabling researchers to quickly gain insights into cellular heterogeneity and function.

Core Features & Use Cases

End-to-End Analysis: Handles the entire scRNA-seq workflow from QC to visualization.
Standardized Workflows: Implements best practices for normalization, dimensionality reduction, clustering, and marker gene identification.
Use Case: A biologist has generated scRNA-seq data and needs to identify distinct cell populations, find marker genes for each population, and visualize the results. This Skill can perform all these steps automatically.

Quick Start

Use the scanpy skill to perform a standard single-cell RNA-seq analysis on the provided 'expression_matrix.h5ad' file.

Frequently Asked Questions about scanpy

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

FAQPage Schema

How do I analyze single-cell RNA-seq data from an h5ad file?▼

Yes, single-cell RNA-seq analysis integrates natively with AnnData objects, allowing you to handle expression matrices and visualize cellular heterogeneity directly within the established bioinformatics pipeline without manual format conversion.

Can I use AnnData objects for single-cell RNA-seq quality control and normalization?▼

What is the standard workflow for identifying cell types in scRNA-seq data?▼

No external dependencies are required to run the single-cell RNA-seq analysis pipeline, but you need a valid AnnData h5ad expression matrix as input to automatically execute the end-to-end bioinformatics workflow and generate visualizations.

Do I need any external dependencies to run scRNA-seq clustering and visualization?▼

What's the best way to find marker genes for distinct cell populations in genomics data?▼

Single-cell RNA-seq analysis covers the entire workflow from raw expression matrices through quality control, normalization, dimensionality reduction, clustering, and differential expression, outputting visualizations of cellular heterogeneity and identified cell types.