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cellxgene-census

Query and analyze CZ CELLxGENE Census single-cell genomics data with scanpy and PyTorch.

8|Updated Nov 19, 2025
Search Tags:#data analysis#bioinformatics#genomics#pytorch#single-cell#cellxgene#scanpy
One-click install
npx skills add https://github.com/sanand0/scientific-research --skill cellxgene-census-sanand0
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cellxgene-census
Source: https://github.com/sanand0/scientific-research/tree/main/.claude/skills/cellxgene-census
Command: npx skills add https://github.com/sanand0/scientific-research --skill cellxgene-census-sanand0

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires cellxgene-census, scanpy, pytorch, tiledbsoma, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides programmatic access to a massive, standardized collection of single-cell genomics data, enabling complex population-scale analyses that would otherwise be computationally prohibitive.

Core Features & Use Cases

  • Massive Data Access: Query over 61 million cells from human and mouse.
  • Flexible Filtering: Filter cells by cell type, tissue, disease, and more.
  • Integration: Seamlessly integrate with analysis tools like scanpy and PyTorch for machine learning.
  • Use Case: Analyze gene expression patterns across thousands of cell types in the human brain to identify novel biomarkers for neurological disorders.

Quick Start

Use the cellxgene-census skill to query human brain cells and retrieve expression data for the gene 'FOXP2'.

Frequently Asked Questions about cellxgene-census

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

FAQPage Schema
How do I query single-cell genomics data for specific cell types and tissues?▼

To query single-cell genomics data, you can filter over 61 million cells by cell type, tissue, and disease to retrieve specific expression data for population-scale analysis.

Can I use scanpy and PyTorch to analyze single-cell gene expression data?▼

Yes, you can integrate retrieved single-cell gene expression data seamlessly with analysis frameworks like scanpy for bioinformatics workflows and PyTorch for machine learning applications.

What is the best way to access large-scale single-cell data for machine learning?▼

The best way to access large-scale single-cell data for machine learning is querying the standardized CZ CELLxGENE Census, which provides programmatic access to 61 million human and mouse cells.

Does this single-cell data query approach support filtering by disease status?▼

Yes, this single-cell data query approach supports flexible filtering by disease status, alongside cell type and tissue, enabling targeted retrieval of expression data for specific biological contexts.

How do I retrieve expression data for a specific gene like FOXP2 across human brain cells?▼

You retrieve expression data for a specific gene like FOXP2 by querying human brain cells within the dataset, filtering by the relevant tissue to extract targeted expression profiles.

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