DaDIA

DaDIA integrates data-dependent acquisition (DDA) and data-independent acquisition (DIA) in LC-MS metabolomics to improve MS² spectral coverage and increase detection and annotation of metabolites.

Key Features:

• Hybrid Acquisition Workflow: Combines DIA for untargeted analysis of individual biological samples and DDA for pooled quality control (QC) samples to leverage DIA's high feature number and DDA's superior MS² spectral quality.
• Enhanced Metabolome Coverage: Integrates DDA and DIA strategies to increase metabolome and MS² coverage relative to conventional single-mode acquisition methods.
• Improved Data Quality: Increases the number of detected features and annotated metabolites through the complementary use of high-coverage DIA and high-quality DDA MS² spectra.
• Automated Feature Extraction and Annotation: Includes DaDIA.R to process heterogeneous DDA and DIA datasets for automated extraction of metabolic features and metabolite annotation.

Scientific Applications:

• Human urine metabolomics: Demonstrated increased numbers of detected features and annotated metabolites compared with standalone DDA or DIA workflows.
• Leukemia metabolomics study: Enabled detection and annotation of approximately four times more significant metabolites than conventional DDA workflows, providing broad MS² coverage for downstream statistical analysis and biological interpretation.

Methodology:

Individual samples are acquired in DIA mode and pooled QC samples in DDA mode, and the resulting datasets are processed with DaDIA.R for feature extraction and metabolite annotation.