iPSCORE QTL-GWAS Colocalizations

dataset

posted on 2024-11-13, 21:06 authored by Timothy ArthurTimothy Arthur, Jennifer NguyenJennifer Nguyen, Benjamin HensonBenjamin Henson, Kelly Frazer

This directory contains two files from the results of performing Bayesian colocalization between iPSCORE quantitative trait loci (QTLs) and GWAS loci from 15 traits and diseases. Briefly, QTLs for three molecular phenotypes (gene expression [eQTLs], chromatin accessibility [caQTLs], and H3K27ac acetylation [haQTLs]) were identified in three tissues from the iPSCORE Collection; induced pluripotent stem cells (iPSCs), iPSC-derived cardiovascular progenitor cells (CVPCs), and iPSC-derived pancreatic progenitor cells (PPCs). To assess if these QTLs overlapped GWAS loci, we performed Bayesian colocalization, using the coloc R package (Giambartolomei et al 2014).The GWAS_QTL_Colocalization_CredibleSets.txt.gz file contains 32,343 SNPs in 99% credible sets from iPSCORE QTLs that colocalized with at least one GWAS loci. These SNPs were intersected with the TFBSs in the Transcription Factor Binding Predictions directory in this repository to identify motif-overlapping causal SNPs. The file contains columns for; Tissue the corresponding tissue, Element_ID the identifier for the molecular affected by the QTL, Trait_Description the description of the GWAS trait or disease, Trait_ID the identifier for the GWAS trait, SNP_ID the identifier of the SNP in the ["VAR"_Chromosome_Position_ReferenceAllele_AlternateAllele] labeling convention, PosteriorProbability the posterior probability for the SNP, QTL_Beta the effect size of the QTL, QTL_Pvalue the P-value of the QTL, QTL_SE the standard error of the QTL, and GWAS_Beta, GWAS_SE, and GWAS_Pvalue the effect size, standard error and p-value of the SNP in the GWAS loci, respectively.The GWAS_QTL_Colocalization_Summaries.txt.gz file summarizes the QTL-GWAS colocalizations by reporting the SNP with the highest posterior probability for all 522,034 colocalizations. The file contains columns for: Tissue the corresponding tissue, Element_ID the identifier for the molecular affected by the QTL, Cluster_ID the identifier for QTL cluster, Complexity whether the QTL is "Complex" and affect multiple elements or "Singleton" and affects only one element, QTL_Combo the combination of molecular phenotypes that the QTL affects, Representative TRUE/FALSE whether the QTL signal was randomly selected to represent the QTL signal, Colocalized TRUE/FALSE based on if the QTL colocalized with the GWAS loci (PP.H4 >= 0.8, QTL_Pvalue < 5e-5, GWAS_Pvalue < 5e-8, and Number of SNPs tested >=50), Trait_Description the description of the GWAS trait or disease, Trait_ID the identifier for the GWAS trait or disease, No_SNPs_Tested the number of SNPs tested in the colocalization, PP.H0.abf, PP.H1.abf, PP.H2.abf, PP.H3.abf, PP.H4.abf the posterior probability for each of the 5 hypotheses from the coloc R package, Likely_Model the coloc hypothesis with the highest posterior probability, Top_SNP_ID the identifier of the SNP with the highest PP in the ["VAR"_Chromosome_Position_ReferenceAllele_AlternateAllele] labeling convention, TopSNP_PP the posterior probability of the top SNP, QTL_Beta, QTL_SE, QTL_Pvalue the effect size, standard error, and p-value of the top SNP in the QTL, and GWAS_Beta, GWAS_SE, GWAS_Pvalue the effect size, standard error, and p-value of the top SNP in the GWAS locus.