Proteomics Quantification

---
name: proteomics-quantification
description: >-
  Protein/peptide quantification (LFQ, TMT, DIA) using MaxQuant LFQ, DIA-NN, or Skyline.
version: 0.1.0
author: OmicsClaw
license: MIT
tags: [proteomics, quantification, LFQ, TMT, DIA, DIA-NN]
metadata:
  omicsclaw:
    domain: proteomics
    emoji: "📏"
    trigger_keywords: [protein quantification, LFQ, TMT, DIA, DIA-NN, Skyline]
    allowed_extra_flags: []
    legacy_aliases: [quantification]
    saves_h5ad: false
---

# 📏 Protein Quantification

Protein and peptide quantification for label-free (LFQ), isobaric labelling (TMT), and DIA workflows.

## CLI Reference

```bash
python omicsclaw.py run proteomics-quantification --demo
python omicsclaw.py run proteomics-quantification --input <data.csv> --output <dir>
```

## Why This Exists

- **Without it**: Peak heights vary wildly due to ion suppression, ionization efficiency, and LC drift
- **With it**: Powerful algorithms (MaxLFQ, DIA-NN) normalize intensities across large cohorts
- **Why OmicsClaw**: Provides a standard programmatic interface to multiple quantification paradigms (LFQ, TMT, DIA)

## Workflow

1. **Calculate**: Map identified sequences to MS1 or MS2 extraction windows.
2. **Execute**: Integrate peak areas and apply cross-run retention time alignment.
3. **Assess**: Perform global normalization (median centering, quantile).
4. **Generate**: Output structural intensity matrices.
5. **Report**: Tabulate key quantification yield metrics.

## Example Queries

- "Quantify proteins using MaxQuant LFQ"
- "Run DIA-NN on these wiff files"

## Output Structure

```
output_directory/
├── report.md
├── result.json
├── quantified.csv
├── figures/
│   └── normalization_boxplot.png
├── tables/
│   └── intensity_matrix.csv
└── reproducibility/
    ├── commands.sh
    ├── requirements.txt
    └── checksums.sha256
```

## Safety

- **Local-first**: Strict offline processing without external upload.
- **Disclaimer**: Requires OmicsClaw reporting structures and disclaimers.
- **Audit trail**: Hyperparameters and operational flow states are logged fully.

## Integration with Orchestrator

**Trigger conditions**:
- Automatically invoked dynamically based on tool metadata and user intent matching.

**Chaining partners**:
- `peptide-id` — Upstream sequence identification
- `differential-abundance` — Downstream statistical execution

## Citations

- [MaxQuant LFQ](https://doi.org/10.1074/mcp.M113.031591)
- [DIA-NN](https://doi.org/10.1038/s41592-019-0638-x)