Differential Expression Analysis
Use when analyzing bulk RNA-seq or microarray expression data to identify...
Install
npx skills add aipoch/medical-research-skills --skill differential-expression-analysis -g -a claude-code -y- Repository
- aipoch/medical-research-skills2k
- Category
- Engineering
- Updated
- 2mo ago
- License
- MIT
- Context cost
- Lightabout 1,432 tokens
- Runs scripts
- No, instructions only
What it does
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.
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.
