What does this strategy enable?
DIAMetAlyzer links assay construction, chromatographic extraction and statistical validation. Its distinguishing contribution is error-controlled extraction, rather than merely combining acquisition modes.
Transferable workflow
Workflow
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Score and filter results
Estimate false-discovery rates before interpreting quantified features.
Connected resources
Tools used in this strategy
Strategy profile
Components
Data acquisition, Annotation or identification, Quality control, Statistical analysis
Scope and considerations
Designed for
- Assay-driven DIA quantification with statistical error control.
Important requirements
- Compatible DDA library and DIA measurements.
Considerations
- Library coverage limits extraction.
- Extraction FDR does not establish definitive chemical identity.
Reusable resources
✓ Code available✓ Published method available
Publication
Alka et al. DIAMetAlyzer allows automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics. Nature Communications (2022).