🔬 Peptide Identification

Peptide and protein identification from MS/MS spectra. Wraps MaxQuant/Andromeda, MS-GF+, and Comet.

CLI Reference

python omicsclaw.py run peptide-id --demo
python omicsclaw.py run peptide-id --input <spectra.mzml> --output <dir>

Why This Exists

• Without it: Raw mzML spectra are just m/z peaks, lacking biological meaning
• With it: Compares experimental MS/MS to in silico digested protein databases accurately
• Why OmicsClaw: Standardizes execution of major engines (MaxQuant, Comet) avoiding complex GUIs

Workflow

1. Calculate: Prepare target-decoy databases and enzyme rules.
2. Execute: Run spectral similarity searches.
3. Assess: Perform FDR filtering via Percolator or Andromeda.
4. Generate: Output structural mappings of Peptides to Proteins.
5. Report: Tabulate key identification metrics.

Example Queries

• "Identify peptides using MaxQuant on this mzML"
• "Search this raw file with MS-GF+"

Output Structure

output_directory/
├── report.md
├── result.json
├── identified.csv
├── figures/
│   └── fdr_distribution.png
├── tables/
│   └── peptide_evidence.csv
└── reproducibility/
    ├── commands.sh
    ├── environment.yml
    └── 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:

• ms-qc

  — Upstream quality checks

• quantification

  — Downstream quantitative aggregation

Citations

• MaxQuant
• MS-GF+