| name | proteomics-ms-qc |
| description | Mass spectrometry raw data quality control using PTXQC, rawTools, or MSstatsQC. |
| version | 0.1.0 |
| author | OmicsClaw |
| license | MIT |
| tags | ["proteomics","QC","mass-spectrometry","PTXQC"] |
| metadata | {"omicsclaw":{"domain":"proteomics","emoji":"📊","trigger_keywords":["MS QC","mass spec QC","PTXQC","rawTools"],"allowed_extra_flags":[],"legacy_aliases":["ms-qc"],"saves_h5ad":false}} |
📊 Proteomics MS-QC
Mass spectrometry data quality control. Computes basic QC statistics for protein/peptide abundance tables.
CLI Reference
python omicsclaw.py run proteomics-ms-qc --demo
python omicsclaw.py run proteomics-ms-qc --input <data.csv> --output <dir>
Why This Exists
- Without it: Instrument drift, missed cleavages, or poor LC gradients ruin quantitative integrity
- With it: Identifies bad samples early before costly downstream statistical processing
- Why OmicsClaw: Provides a unified mass-spectrometer agnostic report dashboard
Workflow
- Calculate: Extract basic peptide features and contaminant ratios.
- Execute: Run descriptive statistics across raw files.
- Assess: Flag outliers outside expected robust median ranges.
- Generate: Output normalized QC matrices.
- Report: Synthesize multiple metric traces across runs.
Example Queries
- "Run mass spec QC on this data using PTXQC"
- "Assess proteomics instrument performance"
Output Structure
output_directory/
├── report.md
├── result.json
├── metrics.csv
├── figures/
│ └── qc_dashboard.pdf
├── tables/
│ └── qc_summary.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:
data-import — Upstream format parsing
quantification — Downstream normalized feature tables
Citations