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Rnaseq de

Skill BioTender-max/awesome-bio-agent-skills/skills/clawbio/rnaseq-de

Differential expression analysis for bulk RNA-seq and pseudo-bulk count matrices with QC, PCA, and contrast testing.From its SKILL.md

Install
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill rnaseq-de

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SKILL.md

2.3 KB, 367 tokens by cl100k_base, as published. Nobody here has run it

🧬 RNA-seq Differential Expression

This skill performs differential expression on bulk RNA-seq or pseudo-bulk count matrices.

Core Capabilities

  1. Input validation for count matrix and sample metadata
  2. Pre-DE QC (library size, detected genes, low-count filtering)
  3. PCA visualisation on normalized expression
  4. Differential expression from formula + contrast
  5. Volcano and MA plots
  6. Markdown report with reproducibility files

Input Contract

  • Count matrix (.csv or .tsv): rows are genes, columns are samples, first column is gene identifier
  • Metadata table (.csv or .tsv): one row per sample, must include sample_id
  • Formula: e.g. ~ condition or ~ batch + condition
  • Contrast: factor,numerator,denominator (e.g. condition,treated,control)

Output Structure

rnaseq_de_report/
β”œβ”€β”€ report.md
β”œβ”€β”€ figures/
β”‚   β”œβ”€β”€ pca.png
β”‚   β”œβ”€β”€ volcano.png
β”‚   └── ma_plot.png
β”œβ”€β”€ tables/
β”‚   β”œβ”€β”€ qc_summary.csv
β”‚   β”œβ”€β”€ normalized_counts.csv
β”‚   └── de_results.csv
└── reproducibility/
    β”œβ”€β”€ commands.sh
    β”œβ”€β”€ environment.yml
    └── checksums.sha256

Usage

python rnaseq_de.py \
  --counts counts.csv \
  --metadata metadata.csv \
  --formula "~ batch + condition" \
  --contrast "condition,treated,control" \
  --output report_dir

Safety

  • Local-only processing
  • Warn before overwriting existing output
  • Report-level disclaimer required

What ships with it: 6 files

27.3 KB alongside SKILL.md, 2 of them executable

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