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Article

mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights

1
Department of Human Genetics, McGill University, Montreal, QC H3A 0C7, Canada
2
Institute of Parasitology, McGill University, Montreal, QC H9X 3V9, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: Karsten Suhre
Metabolites 2022, 12(6), 526; https://doi.org/10.3390/metabo12060526
Received: 1 May 2022 / Revised: 24 May 2022 / Accepted: 31 May 2022 / Published: 7 June 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. View Full-Text
Keywords: mGWAS; SNP; mQTL; metabolomics; pleiotropy; cross-phenotype association analysis; network mGWAS; SNP; mQTL; metabolomics; pleiotropy; cross-phenotype association analysis; network
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MDPI and ACS Style

Chang, L.; Zhou, G.; Ou, H.; Xia, J. mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights. Metabolites 2022, 12, 526. https://doi.org/10.3390/metabo12060526

AMA Style

Chang L, Zhou G, Ou H, Xia J. mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights. Metabolites. 2022; 12(6):526. https://doi.org/10.3390/metabo12060526

Chicago/Turabian Style

Chang, Le, Guangyan Zhou, Huiting Ou, and Jianguo Xia. 2022. "mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights" Metabolites 12, no. 6: 526. https://doi.org/10.3390/metabo12060526

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