ArticleBioData mining2021
eQTpLot: a user-friendly R package for the visualization of colocalization between eQTL and GWAS signals.
Article in BioData mining, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Sequence-based GWAS meta-analyses for beef production traits.Genetics, selection, evolution : GSE · 2023Pooled it
- Mendelian pathway analysis of laboratory traits reveals distinct roles for ciliary subcompartments in common disease pathogenesis.American journal of human genetics · 2021Pooled it
- Genome-wide association study of coronary flow reserve assessed by cardiac perfusion PET suggests a role for NF-κB pathway.Nature cardiovascular research · 2026Article
- Genetic determinants of fatigue up to 2 years after radiotherapy in prostate cancer patients.Nature communications · 2026Article
- Neuroimaging transcriptomic analyses of Parkinson's disease highlight molecular, cellular, and neurobiological mechanisms.NPJ Parkinson's disease · 2025Article
- Multi-omics analysis for identifying cell-type-specific and bulk-level druggable targets in Alzheimer's disease.Journal of translational medicine · 2025Article
- Psychiatric Genomics 2025: State of the Art and the Path Forward.The Psychiatric clinics of North America · 2025Review
- Missing Regulation Between Genetic Association and Transcriptional Abundance for Hypercholesterolemia Genes.Genes · 2025Article
- Article
- Long Noncoding RNA TRIBAL Links the 8q24.13 Locus to Hepatic Lipid Metabolism and Coronary Artery Disease.Circulation. Genomic and precision medicine · 2024Article
- Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes.Nature communications · 2024Article
- Article
- xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs.Briefings in bioinformatics · 2023Article
- eQTL colocalization analysis highlights novel susceptibility genes in Autism Spectrum Disorders (ASD).Translational psychiatry · 2023Article
- The Progression in Developing Genomic Resources for Crop Improvement.Life (Basel, Switzerland) · 2023Review
- The IPDGC/GP2 Hackathon - an open science event for training in data science, genomics, and collaboration using Parkinson's disease data.NPJ Parkinson's disease · 2023Article
- ANKLE1 cleaves mitochondrial DNA and contributes to cancer risk by promoting apoptosis resistance and metabolic dysregulation.Communications biology · 2023Article
- ezQTL: A Web Platform for Interactive Visualization and Colocalization of QTLs and GWAS Loci.Genomics, proteomics & bioinformatics · 2022Article
- Interpreting coronary artery disease GWAS results: A functional genomics approach assessing biological significance.PloS one · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundGenomic studies increasingly integrate expression quantitative trait loci (eQTL) information into their analysis pipelines, but few tools exist for the visualization of colocalization between eQTL and GWAS results. Those tools that do exist are limited in their analysis options, and do not integrate eQTL and GWAS information into a single figure panel, making the visualization of colocalization difficult.
resultsTo address this issue, we developed the intuitive and user-friendly R package eQTpLot. eQTpLot takes as input standard GWAS and cis-eQTL summary statistics, and optional pairwise LD information, to generate a series of plots visualizing colocalization, correlation, and enrichment between eQTL and GWAS signals for a given gene-trait pair. With eQTpLot, investigators can easily generate a series of customizable plots clearly illustrating, for a given gene-trait pair: 1) colocalization between GWAS and eQTL signals, 2) correlation between GWAS and eQTL p-values, 3) enrichment of eQTLs among trait-significant variants, 4) the LD landscape of the locus in question, and 5) the relationship between the direction of effect of eQTL signals and the direction of effect of colocalizing GWAS peaks. These clear and comprehensive plots provide a unique view of eQTL-GWAS colocalization, allowing for a more complete understanding of the interaction between gene expression and trait associations.
conclusionseQTpLot provides a unique, user-friendly, and intuitive means of visualizing eQTL and GWAS signal colocalization, incorporating novel features not found in other eQTL visualization software. We believe eQTpLot will prove a useful tool for investigators seeking a convenient and customizable visualization of eQTL and GWAS data colocalization. AVAILABILITY AND IMPLEMENTATION: the eQTpLot R package and tutorial are available at https://github.com/RitchieLab/eQTpLot.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.