locuszoomr

locuszoomr generates publication-ready regional gene locus plots for genetic and genomic data visualization in R.

Key Features:

• Dual Graphics Systems: Plots are generated via R base graphics or ggplot2, enabling flexible and customizable visualization.
• Modular Plotting Functions: Enables layering of multiple GWAS plots for PheWAS, comparison of GWAS with eQTL signals, and alignment of multiple locus plots on the same page.
• Interactive Visualization: Interactive plots are supported through plotly for rapid identification and labelling of data points.
• Linkage Disequilibrium Integration: The LDlink API is programmatically queried to obtain linkage disequilibrium data from the 1000 Genomes Project for overlay on plots.
• Gene Annotation Queries: Ensembl databases from Bioconductor or AnnotationHub are queried for genomic information and gene track annotation for any species available in Ensembl.
• Recombination Rate Overlay: Helper functions enable recombination rate data from UCSC to be overlaid on plots.
• Embedded Example Data: Includes example GWAS data for testing features.
• Computational Performance: Identifies 50 peaks in a GWAS of approximately 8 million SNPs in approximately 0.6 seconds; exports 50 locus plots with 1 Mb window and recombination rate in approximately 30 seconds on Intel ninth generation CPU or 14 seconds on Apple ARM M3.

Scientific Applications:

• GWAS Visualization: Creates regional locus plots from genome-wide association study data for publication and presentation.
• PheWAS Analysis: Layers multiple GWAS plots to visualize phenome-wide association study results.
• eQTL Comparison: Compares GWAS signals with expression quantitative trait locus signals in integrated plots.
• Cross-Species Genomics: Generates gene track annotations for any species available in Ensembl databases.

Methodology:

The package queries the LDlink API for linkage disequilibrium data from the 1000 Genomes Project, queries Ensembl databases via Bioconductor or AnnotationHub for gene annotation, and overlays recombination rate data from UCSC. Plots are rendered through R base graphics or ggplot2, with interactive visualization via plotly.