datasetposted on 22.05.2019 by Tayaza Fadason, William Schierding, Jiamou Liu, 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.
We identified proximal and distal target genes for 145 genome-wide significant metabolite-associated SNPs by the systematic integration of chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology (KEGG), protein classification (The Human Protein Atlas), drug-gene interaction (DGIdb), and literature text mining (PubMed) data. Our approach revealed that ~90% of the metabolite-associated SNPs are eQTLs. These SNPs form 612 distinct eSNP-eGene interactions via chromatin looping across 48 human tissues.