bioRxivBioinformaticsPreprint
Bridging the gap between genome-wide association studies and network medicine with GNExT
Lis ArendiD, Fabian WolleriD, Bastienne RehoriD, David B. EmmertiD, Johannes FrasnelliiD, Christian FuchsbergeriD, David B. BlumenthaliD, Markus ListiD
Abstract
MotivationA growing volume of large-scale genome-wide association study (GWAS) datasets offers unprecedented power to uncover the genetic determinants of complex traits, but existing web-based platforms for GWAS data exploration provide limited support for interpreting these findings within broader biological systems. Systems medicine is particularly well-suited to fill this gap, as its network-oriented view of molecular interactions enables the integration of genetic signals into coherent network modules, thereby opening opportunities for disease mechanism mining and drug repurposing. ResultsWe introduce GNExT (GWAS Network Exploration Tool), a web-based platform that significantly extends the scope of exploration of variant-level effects and significance beyond those provided by existing solutions. By including MAGMA and Drugst.One, GNExT allows its users to study genetic variants in the context of the latest systems medicine approaches, extending to the identification of potential drug repurposing candidates. Moreover, GNExT advances platform implementation well beyond the current state of the art by offering a highly standardized Nextflow pipeline for data import and preprocessing, allowing researchers to deploy their study results on a sophisticated web interface with minimal implementation overhead. We demonstrate the utility of GNExT using a genome-wide association meta-analysis of human olfactory identification, in which the framework translated isolated GWAS signals to potential pharmacological targets in human olfaction. Furthermore, the deployment of a GNExT instance on European-ancestry Pan-UK Biobank data demonstrates the frameworks scalability, resulting in a comprehensive large-scale resource encompassing thousands of traits and enabling new network medicine-based investigations. Availability and ImplementationThe complete GNExT ecosystem, including the Nextflow preprocessing pipeline, the backend service, and frontend interface, is publicly available on GitHub (https://github.com/dyhealthnet/gnext_nf_pipeline, https://github.com/dyhealthnet/gnext_platform). The public instances of the GNExT platform on olfaction and Pan-UKBB are available under https://olfaction.gnext.gm.eurac.edu and https://panukbb-eur.gnext.gm.eurac.edu.
- organism: human
- assay: GWAS summary statistics
- research focus: database / resource
- research focus: drug response / drug discovery
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Performing highly parallelized and reproducible GWAS analysis on biobank-scale data
Sebastian Schönherr, Johanna F. Schachtl‐Riess, … Lukas Forer·NAR Genomics and BioinformaticsPeer-reviewed·Jan 5, 2024
- A GWAS platform built on iPlant cyber-infrastructure
Liya Wang, Doreen Ware, … Lincoln Stein·bioRxiv·Feb 20, 2014
- GeneNetwork: a continuously updated tool for systems genetics analyses
Pamela M. Watson, David George Ashbrook·bioRxiv·Dec 23, 2020
- martini: an R package for genome-wide association studies using SNP networks
Héctor Climente-González, Chloé‐Agathe Azencott·bioRxiv·Jan 25, 2021
- The MRC IEU OpenGWAS data infrastructure
Benjamin Elsworth, Matthew Lyon, … Gibran Hemani·bioRxiv·Aug 10, 2020
- Network based conditional genome wide association analysis of human metabolomics
Yakov A. Tsepilov, Sodbo Sharapov, … Yurii S. Aulchenko·GigaSciencePeer-reviewed·Nov 29, 2018