num_markers <- 100
num_indiv <- 100
chosen_markers <- 1:num_markers
fake_input_data1 <- list()
fake_input_data1$genomes <- matrix(data = 1,
nrow = num_indiv,
ncol = num_markers)
fake_input_data1$markers <- chosen_markers
fake_input_data2 <- list()
fake_input_data2$genomes <- matrix(data = 2,
nrow = num_indiv,
ncol = num_markers)
fake_input_data2$markers <- chosen_markers
class(fake_input_data1) <- "genomeadmixr_data"
class(fake_input_data2) <- "genomeadmixr_data"
select_matrix <- matrix(ncol = 5, nrow = 1)
s <- 1.0
select_matrix[1, ] <- c(50, 1.0, 1 + 0.5 * s, 1 + s, 1)
simul_two_pop <- simulate_admixture(
module = sequence_module(molecular_data = list(fake_input_data1,
fake_input_data2),
markers = chosen_markers),
migration = migration_settings(
population_size = c(100, 100),
migration_rate = 0.01),
select_matrix = select_matrix,
total_runtime = 100)
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