Proteomics Data Import

---
name: proteomics-data-import
description: >-
  Import and convert proteomics data formats between MaxQuant, DIA-NN, Spectronaut, and standard CSV.
version: 0.1.0
author: OmicsClaw
license: MIT
tags: [proteomics, import, conversion, data-format]
metadata:
  omicsclaw:
    domain: proteomics
    emoji: "📥"
    trigger_keywords: [data import, convert proteomics, format conversion]
    allowed_extra_flags: []
    legacy_aliases: [data-import]
    saves_h5ad: false
---

# 📥 Proteomics Data Import

Import and convert proteomics data from various formats (MaxQuant, DIA-NN, Spectronaut output) into standardised tables.

## CLI Reference

```bash
python omicsclaw.py run proteomics-data-import --demo
python omicsclaw.py run proteomics-data-import --input <proteinGroups.txt> --output <dir>
```

## Why This Exists

- **Without it**: Each search engine (MaxQuant, DIA-NN, FragPipe) outputs completely different table structures
- **With it**: Raw vendor and search outputs are unified into a standard long-format intensity matrix
- **Why OmicsClaw**: Provides a single universal ingestion point before statistical testing

## Workflow

1. **Calculate**: Parse header shapes and metadata dictionaries.
2. **Execute**: Melt and reshape raw search engine text files.
3. **Assess**: Perform basic missing value logic checks.
4. **Generate**: Output normalized H5AD or standard CSV objects.
5. **Report**: Tabulate key protein/peptide groups parsed.

## Example Queries

- "Convert my MaxQuant proteinGroups.txt into a standard format"
- "Import DIA-NN evidence tables"

## Output Structure

```
output_directory/
├── report.md
├── result.json
├── processed.csv
├── figures/
│   └── intensity_distribution.png
├── tables/
│   └── import_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**:
- `ms-qc` — Downstream quality profiling
- `differential-abundance` — Downstream statistical execution