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PheGWAS: A new dimension to visualize GWAS across multiple phenotypes

By Gittu George, Sushrima Gan, Yu Huang, Philip Appleby, A.S. Nar, Radha Venkatesan, Viswanathan Mohan, Colin N.A. Palmer, Alex S.F Doney

Posted 08 Jul 2019
bioRxiv DOI: 10.1101/694794 (published DOI: 10.1093/bioinformatics/btz944)

Motivation PheGWAS was developed to enhance exploration of phenome-wide pleiotropy at the genome-wide level through the efficient generation of a dynamic visualization combining Manhattan plots from GWAS with PheWAS to create a three-dimensional “landscape”. Pleiotropy in sub-surface GWAS significance strata can be explored in a sectional view plotted within user defined levels. Further complexity reduction is achieved by confining to a single chromosomal section. Comprehensive genomic and phenomic coordinates can be displayed. Results PheGWAS is demonstrated using summary data from Global Lipids Genetics Consortium (GLGC) GWAS across multiple lipid traits. For single and multiple traits PheGWAS highlighted all eight-eight and sixty-nine loci respectively. Further, the genes and SNPs reported in GLGC were identified using additional functions implemented within PheGWAS. Not only is PheGWAS capable of identifying independent signals but also provide insights to local genetic correlation (verified using HESS) and in identifying the potential regions that share causal variants across phenotypes (verified using colocalization tests). Availability and Implementation The PheGWAS software and code are freely available at (<https://github.com/georgeg0/PheGWAS>). Contact a.doney{at}dundee.ac.uk, g.z.george{at}dundee.ac.uk

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