medRxiv [Preprint]. 2026 Jul 21:2026.07.15.26358129. doi: 10.64898/2026.07.15.26358129.
ABSTRACT
SUMMARY: It has become standard practice to visualize regional signals from genome-wide association studies (GWAS) using LocusZoom plots. Similarly, GWAS signals are compared to regionally matched quantitative trait loci (QTLs), i.e. variant-to-gene regulation data, using LocusCompare plots to aid assessment of candidate trait-related genes. Despite broad usage, these tools annotate variants by linkage disequilibrium (LD) to a single lead or index variant. This single-index representation has limitations for visualizing complex loci that contain multiple independent signals. We present LocusBlend, an interactive web application for multi-index LD-blended visualization of genomic loci. LocusBlend supports one or two genomic association summary-statistic datasets and one to three index variants, multi-index LocusZoom color-blended plots, and matching LocusCompare visualizations. Applications to Alzheimer’s disease GWAS and QTL signals illustrate LocusBlend enables visualization and separation of independent signals despite shared LD and high genomic complexity. Overall, LocusBlend is aimed at supporting researchers handle the continuously expanding complexity of human genomics findings.
AVAILABILITY AND IMPLEMENTATION: LocusBlend is freely available at https://locusblend.wustl.edu . Publication ready plots are generated in <1min. Source code, documentation, example datasets, input templates, and reproducibility instructions are available at https://github.com/Belloy-Lab/LocusBlend . LocusBlend is implemented in Python using Streamlit, Plotly, and PLINK.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
PMID:42539024 | PMC:PMC13419561 | DOI:10.64898/2026.07.15.26358129
