AntDAS-DDA

AntDAS-DDA processes UHPLC-HRMS data acquired in data-dependent acquisition (DDA) mode to perform automated MS1 and MS/MS feature extraction and spectrum construction for improved untargeted metabolomics compound identification.

Key Features:

• Automated Data Processing: Implements extracted ion chromatogram extraction, feature extraction, MS/MS spectrum construction, fragment ion identification, and MS1 spectrum construction for UHPLC-HRMS DDA datasets.
• Enhanced Compound Identification: Leverages comprehensive MS/MS information and recognition of insource fragment ions to improve compound identification efficiency by approximately 20%.
• Robust Algorithmic Framework: Incorporates advanced algorithms tailored to handle both standard and complex sample matrices for precise feature and spectrum construction.
• Comparative Advantage: Demonstrates superior performance in generating MS/MS spectra across multiple samples when benchmarked against other data analysis approaches.

Scientific Applications:

• Untargeted Metabolomics: Enables comprehensive profiling of metabolites within biological samples using DDA-mode UHPLC-HRMS data.
• Plant Metabolomics: Facilitates identification and quantification of plant-derived compounds.
• Pharmacological Research: Supports drug discovery and biomarker identification via improved metabolite annotation.
• Environmental Studies: Assists analysis of environmental samples for pollutant detection and ecological interaction studies.

Methodology:

Automated processing implements algorithms for extracted ion chromatogram extraction, feature extraction, MS/MS and MS1 spectrum construction, and insource fragment ion recognition.