Cellxgene Census
Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and...
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill cellxgene-census -g -a claude-code -y- Repository
- K-Dense-AI/scientific-agent-skills55.7k
- Category
- Engineering
- Updated
- 9d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
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.
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:
uv pip install "cellxgene-census==1.18.0"
For spatial workflows:
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:
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:
