cellxgene-census

Name: cellxgene-census
Availability: InStock
Author: Jack

Query CZ CELLxGENE Census data for single-cell analysis with scanpy or PyTorch.

16|7|Updated Nov 20, 2025

Search Tags:#pytorch #single-cell #cellxgene #census #anndata #scanpy

Ready to run

npx skills add https://github.com/jackspace/ClaudeSkillz --skill cellxgene-census

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: cellxgene-census
Source: https://github.com/jackspace/ClaudeSkillz/tree/main/skills/scientific-pkg-cellxgene-census
Command: npx skills add https://github.com/jackspace/ClaudeSkillz --skill cellxgene-census

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides programmatic access to the CZ CELLxGENE Census for population-scale single-cell data across millions of cells and datasets.

Core Features & Use Cases

Open census, filter by tissue/disease/cell type
Retrieve expression matrices, embeddings, and pre-calculated statistics
Integration with scanpy and PyTorch for ML workflows
Support large-scale, out-of-core analyses

Quick Start

Install the cellxgene-census package, open the census with open_soma, and load expression data.

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 data from CELLxGENE Census at population scale?▼

Query CELLxGENE Census using open_soma to access millions of cells across datasets. Filter by tissue, disease, and cell type; retrieve expression matrices and embeddings; then load into scanpy or PyTorch for analysis.

Can I filter single-cell datasets by cell type, tissue, and disease in CELLxGENE Census?▼

Yes. CELLxGENE Census supports filtering by cell type, tissue, and disease through metadata APIs. Explore available datasets and their characteristics before retrieving expression data for your analysis.

How do I integrate CELLxGENE Census data with scanpy and PyTorch workflows?▼

Load CELLxGENE Census expression data as AnnData objects using get_anndata, then integrate directly into scanpy pipelines or convert for PyTorch machine-learning workflows. Supports cross-dataset analysis and out-of-core processing.

What data access patterns does CELLxGENE Census support for large-scale queries?▼

CELLxGENE Census provides get_anndata, axis_query, and metadata APIs for flexible data retrieval. Context-managed opening and versioning enable reproducible analyses across small-to-large queries without loading entire datasets into memory.

Can I perform out-of-core analysis on CELLxGENE Census data?▼

Yes. CELLxGENE Census supports out-of-core analyses for large-scale population studies. Use axis_query and metadata APIs to retrieve subsets by cell type, tissue, or disease, enabling analyses across millions of cells without memory constraints.

Does CELLxGENE Census work with AnnData and existing single-cell workflows?▼

Yes. CELLxGENE Census integrates seamlessly with AnnData and scanpy. Retrieve data as AnnData objects via get_anndata, then apply standard single-cell analysis, visualization, and machine-learning workflows directly.