mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights.
Le ChangGuangyan ZhouHuiting OuJianguo XiaPublished in: Metabolites (2022)
Tens of thousands of single-nucleotide polymorphisms (SNPs) have been identified to be significantly associated with metabolite abundance in over 65 genome-wide association studies with metabolomics (mGWAS) to date. Obtaining mechanistic or functional insights from these associations for translational applications has become a key research area in the mGWAS community. Here, we introduce mGWAS-Explorer, a user-friendly web-based platform to help connect SNPs, metabolites, genes, and their known disease associations via powerful network visual analytics. The application of the mGWAS-Explorer was demonstrated using a COVID-19 and a type 2 diabetes case studies.
Keyphrases
- genome wide association
- genome wide
- type diabetes
- ms ms
- dna methylation
- coronavirus disease
- sars cov
- healthcare
- mass spectrometry
- mental health
- cardiovascular disease
- big data
- bioinformatics analysis
- insulin resistance
- genome wide identification
- machine learning
- glycemic control
- weight loss
- antibiotic resistance genes
- case control
- microbial community
- respiratory syndrome coronavirus