eQTLs in the poly-unsaturated fat metabolism cluster
datasetposted on 07.11.2018 by Tayaza Fadason, William Schierding, Thomas Lumley, Justin O'Sullivan
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
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). Convex biclustering was then used to segregate phenotypes that share eGenes, which implies a common underlying molecular mechanism. In the cluster that is built around the FADS locus, SNPs have inverse eQTL effects on FADS1, FADS2, and the other genes in the region. Here, the reference and alternate alleles of the SNP positions are given with their frequencies.