Can I use this skill for machine learning tasks?

Yes, the skill includes patterns for experimental PyTorch integration, allowing you to create dataloaders to train models directly on census data.

How can I ensure my genomic analysis is reproducible?

The skill provides patterns to specify a specific census_version, ensuring your analysis runs against a fixed snapshot of the data.

How does it handle datasets that are too large for RAM?

It supports iterative out-of-core processing using tiledbsoma, enabling you to process millions of cells in manageable batches.

Which species are supported in the census?

The Census currently contains standardized, versioned data for both Homo sapiens (human) and Mus musculus (mouse).

What is the CZ CELLxGENE Census skill?

It is a specialized capability for Claude Code that allows the AI to interact with the 61M+ cell census provided by the Chan Zuckerberg Initiative for genomics research.

CZ CELLxGENE Census Genomics

Name: CZ CELLxGENE Census Genomics
Author: jimmc414

byjimmc414

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324

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데이터 과학 및 ML

Accesses and analyzes over 61 million standardized single-cell genomics records from the CZ CELLxGENE Discover census.

This skill provides Claude with the specialized capability to programmatically query, filter, and analyze massive single-cell genomics datasets from the Chan Zuckerberg CELLxGENE Census. It streamlines the process of retrieving gene expression data, filtering metadata by cell type, tissue, or disease, and integrating this data directly into bioinformatics workflows using scanpy and PyTorch. Designed for bioinformaticians and researchers, it enables population-scale analyses and machine learning model training on standardized genomic data while managing memory efficiency through out-of-core processing.

주요 기능

01Seamless integration with scanpy and AnnData for downstream analysis

02324 GitHub stars

03Efficient querying of 61M+ cells across human and mouse species

04Standardized metadata filtering by cell type, tissue, disease, and donor

05Experimental PyTorch support for training models on population-scale data

06Iterative out-of-core processing for queries exceeding system memory

사용 사례

01Training machine learning models on standardized genomic expression matrices

02Performing population-scale cross-dataset single-cell analysis and statistics

03Discovering cell-type specific gene expression patterns across different disease states

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jimmc414/kosmos cellxgene-census

For use in Claude.ai and ChatGPT