differential-expression-analysis

name	differential-expression-analysis
description	Use when analyzing bulk RNA-seq or microarray expression data to identify differentially expressed genes between two biological groups (case vs control), with volcano plots and heatmap visualization. NOT for:single-cell RNA-seq, methylation analysis, non-expression data.
license	MIT
author	AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Differential Expression Analysis

When to Read External Files

Situation	File to Read	Purpose
Need algorithm details	references/algorithm.md	Statistical methods, formulas, assumptions
Need to run analysis	scripts/main.R	Execute: Rscript scripts/main.R --input_file ... --group_file ...
Encounter errors	references/troubleshooting.md	Common errors and solutions
Need CLI examples	references/cli-guide.md	Detailed CLI usage examples
Need test data	tests/data/	Sample input files for testing

---

Usage

Rscript scripts/main.R \
  --input_file ./expression_matrix.csv \
  --group_file ./group_info.csv \
  --output_dir ./output/ \
  --diff_method limma \
  --p_threshold 0.05 \
  --logfc_threshold 0.1 \
  --seed 42

---

Arguments

Short	Long	Type	Default	Description
-i	--input_file	character	required	Expression matrix file (genes as rows, samples as columns)
-g	--group_file	character	required	Group information file (sample ID + group columns)
-o	--output_dir	character	./output/	Output directory
-m	--diff_method	character	limma	Method: limma, deseq2, edger, t, wilcox
-n	--norm_method	character	TMM	Normalization for edgeR: TMM, RLE, upperquartile
-p	--p_threshold	numeric	0.05	P-value threshold
-f	--logfc_threshold	numeric	0.1	Log fold change threshold
-s	--seed	integer	42	Random seed for reproducibility

---

Input Format

Expression Matrix (input_file)

Genes as rows, samples as columns, CSV format with gene ID in first column.

"","GSM1442228","GSM1442229","GSM1442230"
"0610006L08Rik",3.438,3.237,3.265
"0610007P14Rik",6.734,7.017,6.807

Group File (group_file)

CSV with sample ID and group columns.

"ID","group"
"GSM1442228","Control"
"GSM1442229","Control"
"GSM1442230","DIC"

---

Output Files

File	Description
Diffanalysis.csv	Complete DE results with gene_id, logFC, Pvalue, Padj
volcano_plot.pdf	Volcano plot with significance thresholds
heatmap.pdf	Heatmap of top upregulated/downregulated genes
session_info.txt	R session and package version info
temp/rdegs.csv	Significant differentially expressed genes
temp/Diffanalysis_filtered.csv	Full results with group annotations

---

Workflow

Step 1: Validate Input

• Check file existence
• Validate sample matching between expression matrix and group file
• Verify at least 2 samples per group

Step 2: Run Differential Expression

• Choose method: limma, DESeq2, edgeR, t-test, or Wilcoxon
• Calculate logFC and p-values
• Apply multiple testing correction (Benjamini-Hochberg)

Step 3: Filter Results

• Filter by p-value and logFC thresholds
• Classify genes as Up, Down, or Not significant

Step 4: Generate Visualizations

• Volcano plot showing significance vs fold change
• Heatmap of top differential genes

---

Methods

limma

Linear models for microarray and RNA-seq with empirical Bayes moderation. Recommended for normalized expression data (FPKM, TPM).

DESeq2

Negative binomial GLM with variance stabilization. Recommended for raw count data.

edgeR

Empirical Bayes methods with TMM normalization. Supports robust dispersion estimation.

t-test / Wilcoxon

Simple pairwise statistical tests. t-test for parametric, Wilcoxon for non-parametric.

---

Examples

Basic Usage (limma)

Rscript scripts/main.R \
  -i expression_matrix.csv \
  -g group_info.csv \
  -o ./output \
  -m limma

With DESeq2 for Count Data

Rscript scripts/main.R \
  -i count_matrix.csv \
  -g group_info.csv \
  -o ./output \
  -m deseq2

Custom Thresholds

Rscript scripts/main.R \
  -i expression_matrix.csv \
  -g group_info.csv \
  -o ./output \
  -p 0.01 \
  -f 0.5

---

Error Handling

Common Errors

Error	Cause	Solution
SKILL_FILE_NOT_FOUND	Input file doesn't exist	Check file path
SKILL_SAMPLE_MISMATCH	Sample names don't match	Verify group file matches expression matrix columns
SKILL_INVALID_DATA	Less than 2 groups or samples per group	Check group file
SKILL_FILTER_ERROR	No significant genes found	Relax thresholds or check data quality
SKILL_DEPENDENCY_MISSING	R package not installed	Install required packages

IF error persists, READ: references/troubleshooting.md

---

Testing

Test with Sample Data

# Check help
Rscript scripts/main.R --help

# Run with sample data
Rscript scripts/main.R \
  -i tests/data/Combined_Datasets_Matrix_mus.csv \
  -g tests/data/Combined_Datasets_mus_Group.csv \
  -o tests/output/

Validation Commands

# Count lines in output
wc -l output/Diffanalysis.csv

# Check volcano plot exists
ls -la output/volcano_plot.pdf

---

Implementation Checklist

• CLI parsing with optparse
• set.seed() for reproducibility
• requireNamespace() dependency checks
• Session info recording
• Temp file cleanup
• File reading instructions in SKILL.md
• Modular script structure (<100 lines per file)
• Test data provided
• Error handling with SKILL_* codes
• Scripts in scripts/ directory
• References in references/ directory

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Last updated: 2026-04-01 | Version: 2.0.0