cellxgene-census

# CZ CELLxGENE Census ## Overview The CZ CELLxGENE Census provides programmatic access to a comprehensive, versioned collection of standardized single-cell genomics data from CZ CELLxGENE Discover. This skill enables efficient querying and analysis of millions of cells across thousands of datasets. The Census includes: - **61+ million cells** from human and mouse - **Standardized metadata** (cell types, tissues, diseases, donors) - **Raw gene expression** matrices - **Pre-calculated embeddings** and statistics - **Integration with PyTorch, scanpy, 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 ``` For machine learning workflows, install additional dependencies: ```bash uv pip install cellxgene-census[experimental] ``` ## Core Workflow Patterns ### 1. Opening the Census Always use the context manager to ensure proper resource cleanup: ```python import cellxgene_census # Open latest stable version with cellxgene_census.open_soma() as census: ...