Overview
GCMSFormer combines transformer predictions with orthogonal-projection resolution and least-squares fitting to separate overlapping GC-MS signals.
What can this tool do?
Common uses
- Resolve overlapping GC-MS peaks into component spectra and profiles.
Scientific fit
Primary function
Preprocessing and feature extraction
Data compatibility
Inputs
Raw instrument data, Spectral library
Outputs
Mass spectra, Feature or peak table
Input formats
GC-MS netCDF files plus trained model and reference vocabulary
Output formats
Resolved component spectra and chromatographic concentration profiles
Scope and considerations
Designed for
- GCMSFormer combines transformer predictions with orthogonal-projection resolution and least-squares fitting to separate overlapping GC-MS signals.
Not designed for
- LC-MS/MS processing or guaranteed identification of components absent from model/reference coverage.
Important requirements
- Python/PyTorch environment, trained model and matching reference vocabulary; see test.ipynb.
Considerations
- Training uses augmented overlapping-peak simulations; validate separation on representative experimental mixtures.
- The provided reader works with netCDF; arbitrary vendor-native support is not established.
Access and documentation
MIT license verified in the official source repository. Training datasets and model downloads may have separate terms. No execution or independent performance benchmark.
License: MIT
Evidence and review
Enveda intake checked against official documentation, license information and primary DOI/title/year on 2026-10-22. Editorial review only; no execution or independent benchmark.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- GCMSFormer: A Fully Automatic Method for the Resolution of Overlapping Peaks in Gas Chromatography–Mass Spectrometry. Analytical Chemistry (2024). doi:10.1021/acs.analchem.3c05772
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-10-23 · First committed entry
Add ten reviewed Enveda tools with input and applicability limits
View change · Entry at this revision