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knitr::opts_chunk$set(echo = TRUE) knitr::opts_chunk$set(fig.width = 6)
library(GenomeAdmixR) library(ggplot2) packageVersion("GenomeAdmixR")
To demonstrate the applicability and versatility of joyplots, we create a population, and select on this population on two separate locations, for two different ancestors.
select_matrix <- matrix(ncol = 5, nrow = 2) s <- 0.1 select_matrix[1, ] <- c(0.23, 1.0, 1 + 0.5 * s, 1 + s, 0) select_matrix[2, ] <- c(0.27, 1.0, 1 + 0.5 * s, 1 + s, 1) markers <- seq(from = 0.2, to = 0.3, length.out = 100)
We track frequencies of all ancestors in the range [0.2, 0.3], using 100 markers.
selected_pop <- simulate_admixture( module = ancestry_module(number_of_founders = 2, morgan = 1, markers = markers), pop_size = 100, total_runtime = 1001, select_matrix = select_matrix)
We can now plot all the ancestors over time, we choose here to plot them only for a select subset of times.
time_points <- seq(from = 0, to = 1000, by = 100) plot_joyplot_frequencies(selected_pop$frequencies, time_points, picked_ancestor = "ALL")
Alternatively, we can plot them separately.
p1 <- plot_joyplot_frequencies(selected_pop$frequencies, time_points, picked_ancestor = 0) p1 + ggplot2::geom_vline(xintercept = 0.23, lty = 2)
And for the other ancestor:
p2 <- plot_joyplot_frequencies(selected_pop$frequencies, time_points, picked_ancestor = 1) p2 + ggplot2::geom_vline(xintercept = 0.27, lty = 2)
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