Overview
MS-RIDD interprets oxygen-attachment-dissociation spectra to prioritize lipid double-bond positions. It combines OAD-MS/MS with MS-DIAL lipid annotations derived from CID measurements and supports single-sample and batch projects.
What can this tool do?
Common uses
- Interpret OAD-MS/MS spectra for detailed lipid structural annotation.
- Consume MS-DIAL peak-list and alignment exports as inputs to a lipid-structure workflow.
Scientific fit
Primary function
Metabolite annotation and identification
Other functions
Spectral processing and comparison
Analysis types
Lipidomics
MS level
MS/MS
Acquisition
Targeted MS/MS, Data-dependent acquisition (DDA)
Ion mobility
Not specified
Data compatibility
Inputs
Mass spectra, Feature or peak table
Outputs
Compound list or annotations, Human-readable report
Input formats
mzML, CSV or TSV
Output formats
Pickle project files with analysis tables and CID/OAD structural evidence
Scope and considerations
Designed for
- Lipid structural interpretation using radical-induced dissociation, currently documented for OAD-MS/MS.
Not designed for
- General metabolite identification from ordinary CID spectra without the specialized OAD evidence.
Important requirements
- The documented Python environment, OAD-MS/MS mzML files and MS-DIAL peak/alignment exports with CID-derived lipid annotations. Batch work also requires the associated PeakID and per-sample peak lists.
Considerations
- Double-bond assignments depend on observed diagnostic fragments and the starting lipid annotations; unresolved candidates require further evidence.
Access and documentation
The README specifies LGPL-3.0 for source code and CC-BY-4.0 for the distributed assembly. Keep those scopes distinct when obtaining or redistributing the software.
License: LGPL-3.0-only (source); CC-BY-4.0 (assembly)
Evidence and review
Enveda intake rechecked against official README/documentation, repository access terms and primary publication metadata on 2026-10-27. Editorial source review only; no software execution or independent benchmarking. See docs/enveda-expansion-review-2026-10-27.md.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- Computational mass spectrometry accelerates C = C position-resolved untargeted lipidomics using oxygen attachment dissociation. Communications Chemistry (2022). doi:10.1038/s42004-022-00778-1
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-10-27 · First committed entry
Add 27 source-reviewed tools from Enveda intake
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