mGWAS-Explorer

mGWAS-Explorer enables integrative analysis of associations between single-nucleotide polymorphisms (SNPs), metabolites, genes, and diseases to support interpretation of genome-wide association studies with metabolomics (mGWAS).

Key Features:

• Network Visual Analytics: Employs network visual analytics to create visual representations that connect SNPs, metabolites, genes, and disease associations.
• SNP–Metabolite–Gene–Disease Linking: Integrates associations to explicitly link SNPs with metabolites, mapped genes, and known disease relationships.
• Large-Scale mGWAS Integration: Aggregates associations from mGWAS comprising tens of thousands of SNPs across over 65 studies.
• Case Study Demonstrations: Includes example analyses applied to COVID-19 and type 2 diabetes to illustrate interpretation of mechanistic relationships.

Scientific Applications:

• Mechanistic Insight Discovery: Supports derivation of mechanistic or functional insights from mGWAS associations linking genotype to metabolite changes.
• Pathway and Etiology Investigation: Facilitates investigation of biological pathways underlying complex diseases by connecting genetic variation to metabolic alterations.
• Target Prioritization: Aids prioritization of genes and metabolites for follow-up as potential therapeutic targets or biomarkers based on integrated associations.

Methodology:

Integrates large-scale genomic and metabolomic datasets to construct networks that elucidate SNP–metabolite–gene–disease relationships and uses network visual analytics to represent those networks.