What does this strategy enable?
The mummichog method connects ambiguous mass-to-metabolite matches to metabolic-network structure. Enrichment is evaluated against the measured feature background, allowing collective evidence to prioritize biological hypotheses for experimental follow-up.
Transferable workflow
Workflow
- 1
Define significant and background features
Prepare significant feature masses and the full measured feature list from the comparison.
- 2
Map candidate metabolites to a network
Use mass accuracy, ionization assumptions and a suitable metabolic model to retain plausible matches.
- 3
Evaluate network and pathway enrichment
Compare observed enrichment with permutations from the feature background.
- 4
Validate prioritized hypotheses
Follow up selected metabolites and pathways with independent measurements.
Connected resources
Tools used in this strategy
Strategy profile
Related objectives
Metabolite annotation
Components
Statistical analysis, Annotation or identification, Biological validation
Scope and considerations
Designed for
- Functional interpretation when many significant features remain unidentified.
Important requirements
- Feature statistics, measured background and a relevant metabolic model.
Considerations
- Enrichment is a hypothesis, not confirmation of individual identities or a measurement of flux.
- Background selection and ambiguous ion assignments influence results.
Reusable resources
Publication
Li S, Park Y, Duraisingham S, et al. Predicting Network Activity from High Throughput Metabolomics. PLOS Computational Biology 9, e1003123 (2013).