iPSCORE QTL-GWAS Colocalizations

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.

本目录包含两个文件，这些文件是通过对 iPSCORE 定量性状位点（QTLs）与来自 15 种性状和疾病的全基因组关联研究（GWAS）位点进行贝叶斯共定位分析的结果。简而言之，从 iPSCORE 收集中三个组织（诱导多能干细胞（iPSCs）、iPSC 衍生的心血管祖细胞（CVPCs）和 iPSC 衍生的胰腺祖细胞（PPCs））中鉴定了三种分子表型（基因表达 [eQTLs]、染色质可及性 [caQTLs] 和 H3K27ac 乙酰化 [haQTLs]）的 QTLs。为了评估这些 QTLs 是否与 GWAS 位点重叠，我们使用了 coloc R 包（Giambartolomei 等，2014）执行了贝叶斯共定位。GWAS_QTL_Colocalization_CredibleSets.txt.gz 文件包含来自 iPSCORE QTLs 的 32,343 个单核苷酸多态性（SNPs），这些 SNPs 至少与一个 GWAS 位点共定位，并以 99% 的可信集进行记录。这些 SNPs 与存储在本存储库转录因子结合预测目录中的 TFBSs 进行交集，以识别 motif-overlapping causal SNPs。该文件包含以下列：组织（对应组织）、元素标识符（受 QTL 影响的分子标识符）、性状描述（GWAS 特性或疾病的描述）、性状标识符（GWAS 特性的标识符）、SNP 标识符（在 ["VAR"_Chromosome_Position_ReferenceAllele_AlternateAllele] 标记法下的 SNP 标识符）、后验概率（SNP 的后验概率）、QTL_Beta（QTL 的影响大小）、QTL_Pvalue（QTL 的 P 值）、QTL_SE（QTL 的标准误差）以及 GWAS_Beta、GWAS_SE 和 GWAS_Pvalue（分别表示 GWAS 位点中 SNP 的影响大小、标准误差和 p 值）。GWAS_QTL_Colocalization_Summaries.txt.gz 文件通过报告所有 522,034 次共定位中后验概率最高的 SNP 来总结 QTL-GWAS 的共定位。该文件包含以下列：组织（对应组织）、元素标识符（受 QTL 影响的分子标识符）、聚类标识符（QTL 聚类的标识符）、复杂性（QTL 是否为“复杂”并影响多个元素或“单一”且仅影响一个元素）、QTL_Combo（QTL 影响的分子表型的组合）、代表性（TRUE/FALSE，表示 QTL 信号是否被随机选择以代表 QTL 信号）、共定位（TRUE/FALSE，基于 QTL 是否与 GWAS 位点共定位（PP.H4 >= 0.8，QTL_Pvalue < 5e-5，GWAS_Pvalue < 5e-8，以及测试的 SNPs 数量 >=50））、性状描述（GWAS 特性或疾病的描述）、性状标识符（GWAS 特性或疾病的标识符）、测试的 SNPs 数量（共定位中测试的 SNPs 数量）、PP.H0.abf、PP.H1.abf、PP.H2.abf、PP.H3.abf、PP.H4.abf（来自 coloc R 包的 5 个假设中的每个假设的后验概率）、Likely_Model（具有最高后验概率的 coloc 假设）、Top_SNP_ID（在 ["VAR"_Chromosome_Position_ReferenceAllele_AlternateAllele] 标记法下的最高后验概率 SNP 的标识符）、TopSNP_PP（最高 SNP 的后验概率）、QTL_Beta、QTL_SE、QTL_Pvalue（最高 SNP 在 QTL 中的影响大小、标准误差和 p 值）以及 GWAS_Beta、GWAS_SE、GWAS_Pvalue（最高 SNP 在 GWAS 位点中的影响大小、标准误差和 p 值）。