Pydeseq2
Pydeseq2 is a Python wrapper for analyzing single-cell RNA sequencing data, streamlining workflows and accelerating research.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add pydeseq2 npx -- -y @trustedskills/pydeseq2
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"pydeseq2": {
"command": "npx",
"args": [
"-y",
"@trustedskills/pydeseq2"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill provides access to a pre-configured environment for running PyDeSeq2, a Python package designed for single-cell RNA sequencing data analysis. It allows users to execute common bioinformatics workflows related to differential expression and other downstream analyses directly within the AI agent's execution context. The skill simplifies setup by handling dependencies and providing a ready-to-use framework.
When to use it
- Analyzing single-cell RNA sequencing (scRNA-seq) data for research purposes.
- Performing differential gene expression analysis between different cell populations.
- Reproducing published scRNA-seq workflows or experiments.
- Quickly prototyping and testing new bioinformatics pipelines.
Key capabilities
- Pre-configured environment with PyDeSeq2 installed.
- Simplified dependency management for scRNA-seq data analysis.
- Support for common bioinformatics tasks related to single-cell RNA sequencing.
- Ready-to-use framework for executing workflows.
Example prompts
- "Run the differential expression analysis on this dataset."
- "Generate a visualization of gene expression patterns across cell types."
- "Perform quality control checks on my scRNA-seq data using PyDeSeq2."
Tips & gotchas
- Requires familiarity with single-cell RNA sequencing data and bioinformatics concepts.
- The skill assumes the user provides valid input datasets in a supported format.
Tags
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