mGWAS-Explorer

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

Publications

Chang, L., Zhou, G., Xia, J. mGWAS-Explorer 2.0: causal analysis and interpretation of metabolite-phenotype associations Metabolites 2023, 13(7), 826.
Chang, L., Zhou, G., Ou, H., Xia, J. mGWAS-Explorer: linking SNPs, genes, metabolites and diseases for functional insights Metabolites 2022, 12(6), 526.

News & Updates

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);
Added a new module to support browsing the results of phenome-wide MR of metabolome (03/14/2023);

Main Features

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.

Acknowledgements

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