Package: ggwas 0.99.10

Bartosz Czech

ggwas: Modern 'ggplot2' Visualizations for Genome-Wide Association Studies

Create publication-ready visualizations for genome-wide association studies. Provides 21 plot types including Manhattan, value Manhattan, QQ, Miami, locus zoom, PheWAS, colocalization, fine-mapping, genetic correlation, SNP density, and density-signal comparison plots. Reads PLINK, REGENIE, GCTA, and GEMMA formats natively. All plot functions return 'ggplot2' objects for full customization. Smart downsampling handles datasets with 10 million+ variants.

Authors:Bartosz Czech [aut, cre]

ggwas_0.99.10.tar.gz
ggwas_0.99.10.zip(r-4.7-any)ggwas_0.99.10.zip(r-4.6-any)ggwas_0.99.10.zip(r-4.5-any)
ggwas_0.99.10.tgz(r-4.6-any)ggwas_0.99.10.tgz(r-4.5-any)
ggwas_0.99.10.tar.gz(r-4.7-any)ggwas_0.99.10.tar.gz(r-4.6-any)
ggwas_0.99.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ggwas/json (API)

# Install 'ggwas' in R:

install.packages('ggwas', repos = c('https://biocstaging.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bczech/ggwas/issues

Pkgdown/docs site:https://bczech.github.io

Datasets:

example_gwas - Example GWAS dataset

On CRAN:

visualization genomewideassociation annotation dataimport software

3.60 score 7 scripts 63 exports 28 dependencies

Last updated from:cb0c15f82f. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	207
linux-devel	OK	187
source / vignettes	OK	334
linux-release	OK	226
macos-release	OK	152
macos-oldrel	OK	147
windows-devel	OK	184
windows-release	OK	176
windows-oldrel	OK	179
wasm-release	OK	126

Exports:annotate_genes annotate_positions architecture_plot as_granges as_gwas_data calc_lambda chr_info_cattle chr_info_human chr_info_mouse chr_info_ucsc circular_manhattan coloc_plot density_signal_plot effect_compare_plot enrichment_manhattan filter_region finemapping_plot forest_plot gene_annotation gene_track genetic_correlation get_loci gwas_palette gwas_palettes gwas_preset gwas_summary highlight_regions locus_plot maf_filter manhattan_genes manhattan_plot merge_gwas miami_plot multitrait_manhattan phewas_plot pvalue_heatmap qq_plot read_gcta_mlma read_gemma read_gtf read_gwas_table read_plink_assoc read_plink_linear read_plink_logistic read_regenie scale_color_chromosome scale_color_gwas scale_fill_chromosome scale_fill_gwas set_sex_chr_map snp_density theme_cell theme_gwas theme_nature theme_plos theme_poster theme_presentation theme_science top_hits trumpet_plot validate_gwas_data value_manhattan volcano_plot

Dependencies:BiocGenerics cli cpp11 data.table farver generics GenomicRanges ggplot2 ggrepel glue gridExtra gtable IRanges isoband labeling lifecycle patchwork R6 RColorBrewer Rcpp rlang S4Vectors S7 scales Seqinfo vctrs viridisLite withr

ggwas: Modern GWAS Visualizations

Rendered fromggwas.Rmdusingknitr::rmarkdown

Last update: 2026-07-22
Started: 2026-06-23

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Annotate peaks with nearest gene names	annotate_genes
Map gene IDs or symbols to genome coordinates	annotate_positions
Genetic architecture plot	architecture_plot
Convert GWAS results to a GRanges object	as_granges
Create a gwas_data object	as_gwas_data
Calculate genomic inflation factor (lambda GC)	calc_lambda
Chromosome information for common species	chr_info chr_info_cattle chr_info_human chr_info_mouse
Fetch chromosome information from UCSC	chr_info_ucsc
Circular Manhattan plot	circular_manhattan
Colocalization locus plot	coloc_plot
Density-signal dual-track plot	density_signal_plot
Compare variant effects between two GWAS	effect_compare_plot
Enrichment Manhattan plot	enrichment_manhattan
Example GWAS dataset	example_gwas
Filter variants by genomic region	filter_region
Fine-mapping credible set plot	finemapping_plot
Forest plot of effect estimates	forest_plot
Built-in protein-coding gene annotations	gene_annotation
Gene annotation track	gene_track
Genetic correlation matrix	genetic_correlation
Get significant loci	get_loci
GWAS Color Palettes	gwas_palette
List available GWAS palettes	gwas_palettes
GWAS plot presets	gwas_preset
GWAS Summary Panel	gwas_summary
Add highlighted regions to a Manhattan plot	highlight_regions
Journal-specific themes for GWAS plots	journal_themes theme_cell theme_nature theme_plos theme_poster theme_presentation theme_science
Locus zoom plot	locus_plot
Filter variants by minor allele frequency	maf_filter
Add gene labels to a Manhattan plot	manhattan_genes
Manhattan plot	manhattan_plot
Merge multiple GWAS datasets	merge_gwas
Miami plot (mirrored Manhattan)	miami_plot
Multi-trait Manhattan plot	multitrait_manhattan
PheWAS plot	phewas_plot
Genome-wide p-value heatmap	pvalue_heatmap
QQ plot for GWAS p-values	qq_plot
Read GCTA MLMA results	read_gcta_mlma
Read GEMMA association results	read_gemma
Read gene annotations from GTF/GFF3 file	read_gtf
Read GWAS summary statistics from any tabular file	read_gwas_table
Read PLINK association results	read_plink_assoc
Read PLINK linear regression results	read_plink_linear
Read PLINK logistic regression results	read_plink_logistic
Read REGENIE results	read_regenie
Chromosome color scale	scale_color_chromosome scale_fill_chromosome
Colorblind-safe chromosome color scale	scale_color_gwas scale_fill_gwas
Configure sex chromosome mapping	set_sex_chr_map
SNP density karyogram	snp_density
Minimal GWAS theme for ggplot2	theme_gwas
Extract top hits from GWAS results	top_hits
Trumpet plot: effect size versus allele frequency with power contours	trumpet_plot
Validate a gwas_data object	validate_gwas_data
Manhattan plot of an arbitrary per-feature value	value_manhattan
GWAS effect-size volcano plot	volcano_plot