Multiomic iPSCORE QTLs

<p>This collection contains processed data from "Multiomic QTL mapping reveals phenotypic complexity of GWAS loci and prioritizes putative causal variants" Arthur and Nguyen et al, 2025, Cell Genomics. </p> <p><br></p> <p>In this study, we identified quantitative trait loci (QTLs) that affect gene expression (eQTLs), chromatin accessibility (caQTLs), and histone acetylation (haQTLs), using RNA-seq, ATAC-seq, and H3K27ac ChIP-seq, respectively, generated from induced pluripotent stem cells (iPSCs), and derived cardiovascular progenitor cells (CVPCs), and pancreatic progenitors (PPCs).</p> <p><br></p> <p>There are six items in this collection, including:</p> <p>1) Summary statistics for the QTL analyses</p> <p>2) Results from an analysis to identify temporal regulatory variation using mashr</p> <p>3) Coordinate information for ATAC-seq and H3K27ac ChIP-seq peaks</p> <p>4) Phenotype count matrices for the eight datasets</p> <p>5) Bayesian QTL-GWAS Colocalization results</p> <p>6) Transcription factor predictions in ATAC-seq peaks</p> <p><br></p> <p>Please see the descriptions in the individual items for more detail. </p> <p><br></p>