cellxgene-census

原文涵盖的主题

• CZ CELLxGENE Census
• Overview
• When to Use This Skill
• Installation and Setup
• Core Workflow Patterns
• 1. Opening the Census
• 2. Exploring Census Information
• 3. Querying Expression Data (Small to Medium Scale)

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 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 Install the Census API: For machine learning workflows, install additional dependencies: Always use the context manager to ensure proper resource cleanup: Key points: Use context manager (with statement) for automatic cleanup Specify censusversion for reproduc

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