Start with Metabolites

Connect metabolites to SNPs, genes or diseases

Start with SNPs

Connect SNPs to genes, metabolites or diseases

Start with Genes

Connect genes to SNPs, metabolites or diseases

Integrated Search

Joint search of individual SNP and/or metabolite

MR Analysis

Perform Mendelian randomization analysis

Browse mPheWAS

Browse phenome-wide MR of metabolome

Browse mGWAS

Browse 65 manually curated mGWAS studies

mGWASR Package

Use R package for batch processing or extension

Please use OmicsForum for support & troubleshooting request
  • Upgraded to Java 17 and R 4.3.2 (04/11/2024);
  • Our mGWAS 2.0 paper is now published on Metabolites! (07/03/2023);
  • Fixed a bug with the seed number count for complex queries (06/22/2023);
  • New tutorials are now available! Explore MR Analysis and the Browse mPheWAS module with our latest guides (06/07/2023);
  • Added R command history panel (05/30/2023);
  • Minor code cleaning and fixed home page navigation (05/27/2023);
  • Switched to using local plink files for LD proxy search (05/05/2023);
  • Switched to MyVariant for SNP annotation (03/21/2023);
  • Added Miami plot to visualize significant results of mPheWAS in both phenome-wide and metabolome-wide view (03/17/2023);
  • Added support for auto-complete when searching exposures/outcomes (03/16/2023);
Read more .....
Comprehensive Libraries

Comprehensive collection and deep annotation of results from 65 mGWAS publications. Integrated with HaploReg, VEP, KEGG, Transporter Classification Database (TCDB), Recon3D, as well as common PPI databases.

Causal Analysis

Leverage known diseases associated with SNPs, genes or metabolites to perform causal analysis causal analysis between >4000 metabolites and various disease phenotypes based on two sample Mendelian randomization, with comprehensive support for data harmonization

Functional Insights

Create and visually explore SNP, gene, metabolite, eQTL, pQTL, or disease networks, coupled with enrichment analysis; Or perform semantic triples analysis for triangulation of evidence based on literature mining.