Overview
DeepRTAlign uses a deep-learning-based workflow to match extracted LC-MS features across samples, with alignment scoring and quality-control output. The primary paper includes metabolomics as well as proteomics.
What can this tool do?
Common uses
- Align retention times across large LC-MS sample collections.
Scientific fit
Primary function
Preprocessing and feature extraction
Data compatibility
Inputs
Feature or peak table, Sample metadata
Outputs
Feature or peak table
Input formats
Feature lists containing m/z, charge, RT and intensity; sample mapping workbook
Output formats
Aligned feature groups and scores in CSV files
Scope and considerations
Designed for
- DeepRTAlign uses a deep-learning-based workflow to match extracted LC-MS features across samples, with alignment scoring and quality-control output. The primary paper includes metabolomics as well as proteomics.
Not designed for
- Metabolite identification or peak extraction directly from instrument raw files.
Important requirements
- Python, PyTorch and feature extraction completed upstream.
- Input column mappings and sample-file relationships prepared as documented.
Considerations
- Match quality depends on chromatography, extraction and alignment parameters; confirm suitability for the study.
Access and documentation
License checked against official repository/package metadata. Installation and execution were not tested.
License: GPL-3.0
Evidence and review
Enveda intake candidate checked against official documentation, license information and primary publication on 2026-10-21. Editorial review only; no execution or independent benchmark.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- DeepRTAlign: toward accurate retention time alignment for large cohort mass spectrometry data analysis. Nature Communications (2023). doi:10.1038/s41467-023-43909-5
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-10-21 · First committed entry
Add nine reviewed Enveda tools and reconcile intake coverage
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