NETMAGE: a humaN-disEase phenoType MAp GEnerator for the Visualization of PheWAS

Abstract

Summary: Given genetic associations from a PheWAS, a disease-disease network can be constructed where nodes represent phenotypes and edges represent shared genetic associations between phenotypes. To improve the accessibility of the visualization of shared genetic components across phenotypes, we developed the humaN-disEase phenoType MAp GEnerator (NETMAGE), a web-based tool that produces interactive phenotype network visualizations from summarized PheWAS results. Users can search the map by a variety of attributes, and they can select nodes to view information such as related phenotypes, associated SNPs, and other network statistics. As a test case, we constructed a network using UK BioBank PheWAS summary data. By examining the associations between phenotypes in our map, we can potentially identify novel instances of pleiotropy, where loci influence multiple phenotypic traits. Thus, our tool provides researchers with a means to identify prospective genetic targets for drug design, contributing to the exploration of personalized medicine. Availability and implementation: Our service runs at https://hdpm.biomedinfolab.com. Source code can be downloaded at https://github.com/dokyoonkimlab/netmage.

Multi-ancestry GWAS deciphers genetic architecture of abdominal aortic aneurysm and highlightsPCSK9as a therapeutic target

“…The full summary statistics were then filtered to exclude the following phenotypes: mQTLs, pQTLs, eQTLs, sex specific GWAS and non-EUR and non-mixed ancestry GWAS. After calculating the node and edge maps using NETMAGE (Sriram et al, 2020), only connections that represent a weight of >3 SNPs were used to make the graph more interpretable. Raw network statistics were calculated in Gephi (Bastian et al, 2009) including modularity or cluster ID using Blondel et al (Blondel et al, 2008).…”