Proteomics Differential Expression

Name: Proteomics Differential Expression
Rating: 85 (1 reviews)
Author: clawbio

Trust Score 85/100

Runs differential expression analysis on label-free quantitative proteomics (MaxQuant, DIA-NN) including preprocessing, imputation, statistical testing, and vis

triggers:differential expressionproteomicsLFQMaxQuantDIA-NNimputationvolcano plot

GitHub SKILL.md

What it does

Performs end-to-end differential expression analysis for LFQ proteomics: input parsing for MaxQuant and DIA-NN outputs, filtering of contaminants, log2 transformation, down-shifted Gaussian imputation, statistical testing (two-sample t-test with s0-based FDR correction), and diagnostic visualizations (PCA, volcano, imputation diagnostics). Produces a reproducible report directory with figures and tables.

When to use it

Use this skill when you have processed proteinGroups (MaxQuant) or DIA-NN output and need a reproducible DE analysis pipeline (e.g., quick exploratory DE on treatment vs control contrasts). Not for raw MS processing or biological interpretation — it's an analysis/visualization pipeline that requires user review of results.

What's included

Scripts: examples and a proteomics_de.py demo script present in the repo
References: domain decisions and statistical references included in the skill body
Instructions: detailed preprocessing rules, imputation strategy (shift=1.8, scale=0.3), default thresholds (FDR=0.05, s0=0.1), and output structure for reports.

Compatible agents

Agents able to run Python data workflows (CLI-capable agents, local OpenClaw runtimes, or Code-focused agents with python3 available).

Audit Summary

Proteomics differential expression analysis skill for MaxQuant and DIA-NN LFQ data. No bundled scripts — the SKILL.md documents a CLI tool (proteomics_de.py) that must be provided separately. Well-documented domain decisions, safety rules, input/output contracts, and academic references. Niche bioinformatics audience.

Watch Out

No bundled scripts — the referenced proteomics_de.py CLI tool is not included
Requires metadata CSV with sample_id and group columns
Imputation assumes missing values are low-abundance proteins

Notes

Clean skill, no security concerns. Well-structured SKILL.md with clear documentation. Lacks bundled scripts which limits out-of-box usability — agent would need the proteomics_de.py script available separately.

Information

Repository: clawbio
Stars: 737
Installs: 0

Trust Score

Overall85

Security100

Code Quality72

Architecture68

Usefulness35

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