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Pydeseq2

Listed
davila7·vlatest·backend·MIT

Pydeseq2 is a Python wrapper for analyzing single-cell RNA sequencing data, streamlining workflows and accelerating research.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add davila7/claude-code-templates --skill pydeseq2 -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

davila7

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Live repository

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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.