DBDIpy

DBDIpy analyzes untargeted, time-resolved plasma ionization mass spectrometry (MS) datasets to identify in-source fragments, detect adducts and competing ionization pathways for accurate interpretation of volatiles, aerosols, and metabolomics samples.

Key Features:

• In-Source Fragment Identification: Detects and characterizes in-source fragments generated during plasma ionization.
• Competing Ionization Pathway Elucidation: Identifies and differentiates rival ionization pathways producing multiple ion species for the same analytes in time-sensitive datasets.
• Adduct and Plasma-Specific Ion Species Detection: Detects adducts and other ion species specific to plasma ionization that can confound untargeted analysis.
• Untargeted Metabolomics Processing Functions: Provides elementary processing functions tailored to untargeted metabolomics data from plasma ionization MS.
• Analysis of Volatiles and Aerosols: Targets the interpretation of ionization behavior in studies of volatiles and aerosols commonly analyzed by plasma ionization.

Scientific Applications:

• Volatile and Aerosol Analysis: Interpret complex ionization patterns in studies of volatiles and aerosols.
• Untargeted Metabolomics: Support formal analysis and preprocessing of untargeted metabolomics datasets acquired by plasma ionization MS.
• Ionization Mechanism Studies: Dissect ion formation mechanisms by combining in-source fragment and pathway detection.
• Time-Resolved MS Experiments: Resolve temporal changes in ion species and pathway dominance within real-time plasma ionization experiments.

Methodology:

Computational methods perform detection and analysis of in-source fragments, identification of adducts and competing ionization pathways, and provide elementary processing functions for untargeted, time-sensitive plasma ionization MS datasets.