LargeMetabo

LargeMetabo performs large-scale metabolomic data integration, metabolite annotation, enrichment analysis, and biomarker identification to support biomarker discovery and mechanistic studies of disease using untargeted mass spectrometry data.

Key Features:

• Data Integration: Integrates data from multiple analytical experiments to increase statistical power for large-scale metabolomic analyses.
• Intelligent Biomarker Identification: Implements an assessment feature to select appropriate biomarker identification methods for large-scale metabolic datasets.
• Metabolite Annotation: Provides advanced metabolite annotation tailored for untargeted mass spectrometry-based metabolomics.
• Enrichment Analysis: Performs enrichment analysis to interpret annotated metabolites in biological context.
• Enhanced Metabolite Database: Leverages an enhanced metabolite database to improve accuracy of metabolite identification.
• Batch Effect and Unwanted Variation Correction: Addresses diverse unwanted variations and batch effects to improve data reliability.

Scientific Applications:

• Biomarker discovery: Identification of biomarkers in biomedical studies using large-scale metabolomic datasets.
• Disease mechanism elucidation: Investigation of metabolic alterations to elucidate mechanisms underlying complex diseases.

Methodology:

Implemented in R; includes data integration, an intelligent assessment for choosing biomarker identification methods, metabolite annotation and enrichment analysis using an enhanced metabolite database, and procedures to address unwanted variation and batch effects.