alterlab-pydeseq2

Community

End-to-end differential expression analysis in Python.

AuthorAlterLab-IEU
Version1.0.0
Installs0

System Documentation

What problem does it solve?

PyDESeq2 delivers a Python-based, end-to-end differential expression analysis workflow for bulk RNA-seq data, enabling users to perform normalization, dispersion estimation, log fold-change fitting, and multiple testing correction in Python.

Core Features & Use Cases

  • Single-factor and multi-factor design support to model complex experiments.
  • Wald tests with Benjamini-Hochberg FDR correction and flexible contrasts.
  • Optional LFC shrinkage for visualization and ranking of genes.
  • Tight integration with pandas and AnnData for seamless data handling.
  • Export of results and basic plots (volcano/MA) for reporting.

Quick Start

Load your counts and metadata, initialize the PyDESeq2 workflow with an appropriate design, run the DESeq2 pipeline, perform Wald tests, and review the results.

Dependency Matrix

Required Modules

pydeseq2pandasmatplotlib

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: alterlab-pydeseq2
Download link: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/archive/main.zip#alterlab-pydeseq2

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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