# Cellxgene Census

Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and...

- Repository: https://github.com/K-Dense-AI/scientific-agent-skills (55651 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-10-26
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add K-Dense-AI/scientific-agent-skills --skill cellxgene-census -g -a claude-code -y`
Codex: `npx skills add K-Dense-AI/scientific-agent-skills --skill cellxgene-census -g -a codex -y`
Cursor: `npx skills add K-Dense-AI/scientific-agent-skills --skill cellxgene-census -g -a cursor -y`
Gemini CLI: `npx skills add K-Dense-AI/scientific-agent-skills --skill cellxgene-census -g -a gemini-cli -y`

## Description

Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons across organisms, tissues, diseases, assays, and cell types. For analyzing your own local single-cell data use scanpy, anndata, or scvi-tools.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# CZ CELLxGENE Census

## Overview

The CZ CELLxGENE Census provides programmatic access to a comprehensive, versioned collection of standardized single-cell and spatial transcriptomics data from CZ CELLxGENE Discover. This skill enables efficient querying and analysis of public Census releases without downloading whole datasets first.

The Census includes:
- **217+ million total cells** and **125+ million unique cells** in the 2025-11-08 stable LTS release
- **1,845 datasets** in the 2025-11-08 stable LTS release
- **Human, mouse, marmoset, rhesus macaque, and chimpanzee** data in the current schema
- **Standardized metadata** (cell types, tissues, diseases, donors)
- **Raw gene expression** matrices and source H5AD lookup/download helpers
- **Pre-calculated summary counts, embeddings, and spatial data**
- **Integration with AnnData, Scanpy, TileDB-SOMA, TileDB-SOMA-ML, and other analysis tools**

## When to Use This Skill

This skill should be used when:
- Querying single-cell expression data by cell type, tissue, or disease
- Exploring available single-cell datasets and metadata
- Training machine learning models on single-cell data
- Performing large-scale cross-dataset analyses
- Integrating Census data with scanpy or other analysis frameworks
- Computing statistics across millions of cells
- Accessing pre-calculated embeddings or model predictions

## Installation and Setup

Install the Census API:
```bash
uv pip install "cellxgene-census==1.18.0"
```

For spatial workflows:
```bash
uv pip install "cellxgene-census[spatial]==1.18.0"
```

For PyTorch model training, use TileDB-SOMA-ML. The old `cellxgene_census.experimental.ml` loaders are absent from 1.18.0:

```bash
uv pip install "cellxgene-census==1.18.0" tiledbsoma-ml
```

## Core Workflow Patterns

Eight patterns, each with code, are in
[references/core_workflow_patterns.md](references/core_workflow_patterns.md):

The rest: https://github.com/K-Dense-AI/scientific-agent-skills/blob/HEAD/skills/cellxgene-census/SKILL.md