rnaseq-de
CommunityPerform RNA-seq differential expression analysis with quality control and visualization.
AuthorMubasherMohammed
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill streamlines RNA-seq differential expression analysis, offering a streamlined approach with built-in quality control, visualization, and report generation.
Core Features & Use Cases
- Differential Expression Analysis: Conduct differential expression testing on bulk RNA-seq data.
- Quality Control: Includes pre-processing checks like library size normalization and filtering of low-count genes.
- Visualization: Provides PCA and volcano plots for visualization of results.
- Report Generation: Automatically generates a comprehensive markdown report including reproducibility information.
Quick Start
Run the rnaseq-de skill with the command: python rnaseq_de.py --counts counts.csv --metadata metadata.csv --formula "~ condition" --contrast "condition,treated,control" --output report_dir
Dependency Matrix
Required Modules
pandasnumpymatplotlibscikit-learnpydeseq2
Components
scriptsreferencesassets
💻 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: rnaseq-de Download link: https://github.com/MubasherMohammed/opencode-BioInfo/archive/main.zip#rnaseq-de Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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