Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(fig.width = 6)
## ----load libraries-----------------------------------------------------------
library(GenomeAdmixR)
library(ggplot2)
packageVersion("GenomeAdmixR")
## ----create populations-------------------------------------------------------
pops <-
simulate_admixture(
module = ancestry_module(),
migration = migration_settings(migration_rate = 0,
population_size = c(100, 100),
initial_frequencies =
list(c(1, 1, 1, 1, 0, 0, 0, 0),
c(0, 0, 0, 0, 1, 1, 1, 1))),
total_runtime = 1000)
pop_1 <- pops$population_1
pop_2 <- pops$population_2
## ----calculate LD-------------------------------------------------------------
mean(calculate_ld(pop = pop_1,
sampled_individuals = 10,
markers = 30)$ld_matrix,
na.rm = TRUE)
mean(calculate_ld(pop = pop_2,
sampled_individuals = 10,
markers = 30)$ld_matrix,
na.rm = TRUE)
## ----create isofemale lines---------------------------------------------------
iso_females_pop_1 <- create_iso_female(
module = ancestry_module(input_population = pop_1),
n = 2,
inbreeding_pop_size = 100)
iso_females_pop_2 <- create_iso_female(
module = ancestry_module(input_population = pop_2),
n = 2,
inbreeding_pop_size = 100)
## ----create from individuals--------------------------------------------------
pop_1_1 <- simulate_admixture(
module = ancestry_module(input_population = iso_females_pop_1),
pop_size = 1000,
total_runtime = 1000)
pop_1_2 <- simulate_admixture(
module = ancestry_module(input_population =
list(iso_females_pop_1[[1]],
iso_females_pop_2[[1]])),
pop_size = 1000,
total_runtime = 1000)
pop_2_2 <- simulate_admixture(
module = ancestry_module(input_population = iso_females_pop_2),
pop_size = 1000,
total_runtime = 1000)
## ----FST calculation----------------------------------------------------------
f1 <- calculate_fst(pop_1_1, pop_1_2,
sampled_individuals = 10, number_of_markers = 100)
# this one should be highest
f2 <- calculate_fst(pop_1_1, pop_2_2,
sampled_individuals = 10, number_of_markers = 100)
f3 <- calculate_fst(pop_1_2, pop_2_2,
sampled_individuals = 10, number_of_markers = 100)
f1
f2
f3
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