Simulating Samples

Requires PopGenSims.jl

To perfom simulations, you will need add and import the package PopGenSims.jl (available here).

Simulate samples within populations

simulate(data::PopData; n::Int)
simulate(data::PopData; n::Dict{String,Int})
simulate(data::PopData; scale::Int)

Simulate data using per-population allele frequencies. The simulated samples will have the naming convention sim_1...sim_# where # is the total number of simulated samples in the new PopData.

fixed samples

simulate(data::PopData; n::Int)

If you want to simulate data with a fixed number of individuals per population, you can do so with simulate(PopData, n = Int), which takes a PopData object and simulates n number of individuals per population. Returns a new PopData with samples having the same ploidy as the source PopData, but will not work on mixed-ploidy data.

In the example below, we simulate 100 individuals per population using the nancycats data, which has 17 populations, therefore the resulting PopData will have 1700 samples (100 samples x 17 populations).

Example

julia> cats = @nancycats;

julia> sims = simulate(cats , n = 100)
PopData{Diploid, 9 Microsatellite loci}
  Samples: 1700
  Populations: 17

arbitrary samples

simulate(data::PopData; n::Dict{Population,Int})

To simulate an arbitrary number of individuals for arbitrary populations, use simulate(PopData, n = Dict{String, Int}), which takes a PopData object and simulates samples within populations as specified in the input Dict, where keys => values are population => n_samples. Returns a new PopData with samples having the same ploidy as the source PopData, but will not work on mixed-ploidy data.

In the example below, we create a dictionary with the notation Population => #samples to simulate a specific number of samples for 3 particular populations. The resulting PopData will have 28 samples (5+3+20) across 3 populations ("1", "8", "11").

julia> cats = @nancycats;

julia> simscheme = Dict("1" => 5, "8" => 3, "11" => 20) ;

julia> simulate(cats, n = simscheme)
PopData{Diploid, 9 Microsatellite loci}
  Samples: 28
  Populations: 3

proportional samples

simulate(data::PopData; scale::Int)

If you want to simulate data while keeping the proportion of individuals per population consistent with the source PopData, use simulate(PopData, scale = Int), which takes a PopData object and simulates the same number of individuals per population multiplied by scale (i.e. if scale=2, there will be twice the number of simulated individuals compared to the original PopData). Returns a new PopData with samples having the same ploidy as the source PopData, but will not work on mixed-ploidy data.

In the example below, we simulate 3x the number of samples of the original nancycats data, which has 237 samples x 17 populations, therefore the resulting PopData will have 711 samples (237 samples x 3).

Example

julia> cats = @nancycats;

julia> sims = simulate(cats , scale = 3)
PopData{Diploid, 9 Microsatellite loci}
  Samples: 711
  Populations: 17