ggplot2 Extensions for Population Genetics Plots • ggPopi

ggPopi provides tidy, publication-oriented ggplot2 workflows for common population-genomics plots. It combines typed import helpers, direct plot_*() functions, and composable ggpop() + geom_*() layers.

Supported modules include GWAS Manhattan and Q-Q plots, PCA, admixture, population statistics, LD decay, selective sweep scans, introgression summaries, and demographic / effective population size histories.

Installation

Install the development version from GitHub:

# install.packages("pak")
pak::pak("WWz33/ggPopi")

Core plotting uses CRAN-available dependencies. Optional integrations use:

flashpcaR for compute_pca(method = "flashpca");
pophelper for direct plotQ() compatibility helpers.

Quick Start

library(ggPopi)

gwas <- import_gwas(
  system.file("extdata", "gwas", "gcta.mlma", package = "ggPopi"),
  type = "gcta"
)

plot_manha(gwas)

Manhattan plot with chromosomes on the x-axis and minus log10 p-values on the y-axis.

The same imported object can be used through the layered ggplot extension path:

gwas |>
  ggpop() +
  geom_manha()

Interface

Every module follows the same shape:

import_*() reads tool output into a typed data frame.
plot_*() returns a complete ggplot object with module defaults.
ggpop() + geom_*() provides the same visual grammar inside a ggplot pipeline.

Module	Import	Direct plot	ggplot extension	Guide
GWAS	`import_gwas()`	`plot_manha()`, `plot_qq()`	`geom_manha()`, `geom_qq()`	GWAS
PCA	`import_pca()`, `compute_pca()`	`plot_pca()`	`geom_pca()`	PCA
Admixture	`import_admix()`	`plot_admix()`, `plot_admix2()`	`geom_admix()`, `geom_admix2()`	Admixture
Population statistics	`import_stats()`	`plot_stats()`	`geom_stats()`	Stats
LD decay	`import_ld_decay()`	`plot_ld_decay()`	`geom_ld_decay()`	LD decay
Selective sweeps	`import_selection()`	`plot_selection()`	`geom_selection()`	Selection
Introgression	`import_introgression()`	`plot_introgression()`	`geom_introgression()`	Introgression
Demographic / Ne history	`import_ne_history()`, `import_demographic_history()`	`plot_ne_history()`, `plot_demographic_history()`	`geom_ne_history()`, `geom_demographic_history()`	Ne history

Documentation

Getting started: https://wwz33.github.io/ggPopi/articles/ggPopi.html
Function reference: https://wwz33.github.io/ggPopi/reference/
Compatibility helpers: https://wwz33.github.io/ggPopi/articles/guides/compatibility.html

Design

ggPopi keeps the user-facing API small while preserving module-specific visual defaults. Direct plot_*() functions are the reference style, and matching geom_*() layers make those defaults available in ggplot compositions.

Palette and theme helpers such as ggpop_palette(), scale_colour_ggpop(), scale_fill_ggpop(), and theme_tidyplot() provide shared styling across modules.