The University of Auckland
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Visualisation files for multimorbidity analysis

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posted on 2018-11-07, 16:25 authored by Tayaza FadasonTayaza Fadason
Chromatin interactions (using Hi-C) and functional (using eQTL) data were used to identify long-range regulatory associations involving >20,000 GWAS variants and their target genes (i.e. eGenes) in >1,350 phenotypes in the GWAS Catalog. Using convex biclustering, we segregated phenotypes based on the eGenes they share, which implies a common underlying molecular mechanism. Understanding the roles the eGenes play has potential applications in understanding multimorbidities and drug repurposing.<div>This datasource underlie the figures generated in the study</div>

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University of Auckland