--> --- name: bio-metabolomics-annotation description: Metabolite annotation and structural identification using SIRIUS, CSI:FingerID, GNPS, or MetFrag. tool_type: mixed primary_tool: metabolomics measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Metabolite annotation and structural identification against spectral libraries. Supports SIRIUS/CSI:FingerID, GNPS, and MetFrag.
Scanned 9/7/2026
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---
name: bio-metabolomics-annotation
description: Metabolite annotation and structural identification using SIRIUS, CSI:FingerID,
GNPS, or MetFrag.
tool_type: mixed
primary_tool: metabolomics
measurable_outcome: Execute skill workflow successfully with valid output within 15
minutes.
allowed-tools:
- read_file
- run_shell_command
---
# 🏷️ Metabolite Annotation
Metabolite annotation and structural identification against spectral libraries. Supports SIRIUS/CSI:FingerID, GNPS, and MetFrag.
## CLI Reference
```bash
python omicsclaw.py run met-annotate --demo
python omicsclaw.py run met-annotate --input <features.csv> --output <dir>
```
## Why This Exists
- **Without it**: LC-MS peaks remain anonymous "features" defined only by m/z and retention time
- **With it**: Converts features into candidate chemical structures via spectral networking and in-silico fragmentation
- **Why OmicsClaw**: Centralizes access to fragmented knowledgebases (SIRIUS, GNPS, MetFrag)
## Workflow
1. **Calculate**: Extract pure MS2 spectra representations.
2. **Execute**: Query spectral libraries or generate fragmentation trees.
3. **Assess**: Score candidate chemical formulas and structures.
4. **Generate**: Output structural mappings of features to molecules.
5. **Report**: Tabulate top compound identifications with confidence tiers.
## Example Queries
- "Annotate these metabolomics features using SIRIUS"
- "Match MS2 spectra against GNPS libraries"
## Output Structure
```
output_directory/
├── report.md
├── result.json
├── annotated.csv
├── figures/
│ └── chemical_class_distribution.png
├── tables/
│ └── compound_identifications.csv
└── reproducibility/
├── commands.sh
├── environment.yml
└── checksums.sha256
```
## Safety
- **Local-first**: Local database matching where possible; transparent interactions for external APIs (like GNPS).
- **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**:
- `peak-detection` — Upstream feature extraction
- `met-diff` — Downstream structural interpretation of significant hits
## Citations
- [SIRIUS](https://doi.org/10.1038/s41592-019-0344-8)
- [GNPS](https://doi.org/10.1038/nbt.3597)
- [MetFrag](https://doi.org/10.1186/s13321-016-0115-9)
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