I'd like to share ggwas, an R package I developed for visualizing GWAS summary statistics. It addresses the gap between simple tools like qqman (Manhattan + QQ only, base R graphics) and the need for modern post-GWAS visualizations.

What it does:

• 17 plot types: Manhattan, QQ, Miami, locus zoom, circular Manhattan, PheWAS, colocalization, fine-mapping (PIP), genetic correlation matrix, genome-wide heatmap, SNP density karyogram, density-vs-signal QC, and more
• Broken y-axis for Manhattan plots with extreme p-values
• Built on ggplot2 — every function returns a ggplot object, fully composable with patchwork
• 6 journal themes (Nature, Science, Cell, PLOS) + 14 colorblind-safe palettes
• Smart downsampling: renders 1.37M variants in <1s (up to 9x faster than qqman)
• Reads PLINK, REGENIE, GCTA, GEMMA natively with auto-detection
• Species-agnostic: built-in chromosome data for human, mouse, cattle + UCSC integration for any species

Links:

• GitHub: https://github.com/bczech/ggwas
• Documentation & gallery: https://bczech.github.io/ggwas/
• DOI: 10.5281/zenodo.20815110