deseq2-differential-expression

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DESeq2 differential expression analysis skill with normalization, statistical modeling, and visualization

General

What this skill does


# DESeq2 Differential Expression Skill

## Purpose
Provide DESeq2 differential expression analysis with normalization, statistical modeling, and visualization.

## Capabilities
- Size factor normalization
- Negative binomial modeling
- Shrinkage estimation
- Batch effect modeling
- Multi-factor designs
- Result visualization (MA plots, volcano plots)

## Usage Guidelines
- Design experiments with appropriate replication
- Include batch effects in model when present
- Apply appropriate shrinkage estimators
- Use multiple testing correction
- Generate publication-quality visualizations
- Document analysis parameters and thresholds

## Dependencies
- DESeq2
- edgeR
- limma-voom

## Process Integration
- RNA-seq Differential Expression Analysis (rnaseq-differential-expression)
- Single-Cell RNA-seq Analysis (scrnaseq-analysis)
- CRISPR Screen Analysis (crispr-screen-analysis)

Files: 1

Size: 1.3 KB

Complexity: 9/100

Category: General

Source: https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/bioinformatics/skills/deseq2-differential-expression

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