--> --- name: bio-proteomics-quantification description: Protein/peptide quantification (LFQ, TMT, DIA) using MaxQuant LFQ, DIA-NN, or Skyline. tool_type: mixed primary_tool: proteomics measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Protein and peptide quantification for label-free (LFQ), isobaric labelling (TMT), and DIA workflows.
Scanned 9/7/2026
Install to Claude Code
npx -y skills add mdbabumiamssm/LLMs-Universal-Life-Science-and-Clinical-Skills- --skill proteomics-quantification --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Proteomics Quantification?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/mdbabumiamssm-proteomics-quantification-llms-universal-life-science-an)More formats (shields.io, HTML) on the badges page.
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
-->
---
name: bio-proteomics-quantification
description: Protein/peptide quantification (LFQ, TMT, DIA) using MaxQuant LFQ, DIA-NN,
or Skyline.
tool_type: mixed
primary_tool: proteomics
measurable_outcome: Execute skill workflow successfully with valid output within 15
minutes.
allowed-tools:
- read_file
- run_shell_command
---
# 📏 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
├── 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**:
- `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)
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!