Is differential-expression-analysis safe to install?

SaferSkills independently audited differential-expression-analysis (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

awesome-med-research-skills/Data Analysis/differential-expression-analysis/SKILL.md · 1 file

awesome-med-research-skills/Data Analysis/differential-expression-analysis/SKILL.md5.9 KB · Markdown

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

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

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

differential-expression-analysis— agent skill

Is differential-expression-analysis safe to install?

Differential Expression Analysis

When to Read External Files

Usage

Arguments

Input Format

Expression Matrix (input_file)

Group File (group_file)

Output Files

Workflow

Step 1: Validate Input

Step 2: Run Differential Expression

Step 3: Filter Results

Step 4: Generate Visualizations

Methods

limma

DESeq2

edgeR

t-test / Wilcoxon

Examples

Basic Usage (limma)

With DESeq2 for Count Data

Custom Thresholds

Error Handling

Common Errors

Testing

Test with Sample Data

Validation Commands

Implementation Checklist

Audit the pieces. Scan the whole. Decide.