Overview
MS2DECIDE is a Python library implementing an expert-informed decision model. Its K-estimation workflow aggregates complementary annotation results and exports scored features for follow-up investigation.
What can this tool do?
Common uses
- Prioritize natural-product features using multiple annotation sources and an explicit decision model.
Scientific fit
Primary function
Metabolite annotation and identification
Data compatibility
Inputs
Feature or peak table, Mass spectra, Compound list or annotations
Outputs
Feature or peak table, Statistical results
Input formats
CSV or TSV, MGF
Output formats
CSV or TSV, Filtered dataframe and TSV file with K-values
Scope and considerations
Designed for
- Combine GNPS, ISDB-LOTUS and SIRIUS annotations into scores for natural-product feature prioritization.
Not designed for
- Replacing experimental confirmation of compound identity.
- Raw-data feature detection or chromatographic alignment.
Important requirements
- A quantitative feature table, corresponding MGF spectra and compatible SIRIUS identification results with matching feature identifiers.
- A supported Python environment, GNPS account and network access for the documented workflow.
- The documentation describes SIRIUS 6 and MZmine FBMN-compatible exports; check current format compatibility before use.
Considerations
- K-values reflect the decision model and available annotations, not probabilities of correct identification or proof of chemical novelty.
- Results depend on reference coverage and agreement between annotation sources. Inspect spectra and investigate prioritized features experimentally.
Access and documentation
MIT license verified in the official repository. Software was not installed or execution-tested; dependencies and external services have their own requirements.
License: MIT
From tool to strategy
Strategies using MS2DECIDE
Evidence and review
Enveda intake reviewed against the primary publication, official repository documentation and license on 2026-10-05. Editorial review only; no execution or independent benchmark.
Core publications
Resource papers, direct updates and tool-specific methods. Selection policy.
- MS2DECIDE: Aggregating Multiannotated Tandem Mass Spectrometry Data with Decision Theory Enhances Natural Products Prioritization. Chemistry–Methods (2025). doi:10.1002/cmtd.202400088
Related tools
Entry history
Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.
- 2026-10-06 · First committed entry
Add annotation software and link existing Strategy implementations
View change · Entry at this revision