Cellxgene Census

What it does

This skill allows AI agents to interact with Cellxgene Census, a tool for analyzing single-cell gene expression data. It enables users to query and retrieve information about cell types, marker genes, and other relevant features within datasets. The agent can perform tasks such as identifying the most abundant cell types or finding genes that are differentially expressed between different groups of cells.

When to use it

• Biological Research: A researcher wants to quickly identify the dominant cell populations in a newly generated single-cell dataset.
• Data Exploration: A data scientist is exploring a public Cellxgene Census dataset and needs help understanding its contents.
• Report Generation: An analyst needs to automatically generate reports summarizing key findings from a Cellxgene Census analysis.
• Educational Purposes: A student wants to learn about single-cell gene expression analysis using a conversational interface.

Key capabilities

• Querying cell type abundances
• Identifying marker genes for specific cell types
• Retrieving information about datasets
• Performing differential expression analysis (implied)

Example prompts

• "What are the most abundant cell types in the 'Mouse_Immune_v1' dataset?"
• "Can you tell me which genes are markers for T cells in this dataset?"
• "Show me a list of all available datasets."

Tips & gotchas

This skill requires familiarity with Cellxgene Census terminology and data structure. The agent’s responses will depend on the quality and completeness of the underlying Cellxgene Census data.