Sample mixtures with known genotypes and random parameters according to priors

Usage

sample_mixtures_from_genotypes(
  n,
  genotypes,
  sampling_parameters,
  model_settings,
  sample_model,
  results_directory,
  seed,
  number_of_replicates = 1L,
  tag = "simulation",
  silent = FALSE
)

Arguments

n: Integer. Number of samples.
genotypes: List of contributor genotypes. See sample_contributor_genotypes.
sampling_parameters: List. Passed to the sample_model function.
model_settings: List. Passed to the sample_model function.
sample_model: Function such as sample_log_normal_model.
results_directory: (optionally) Character with path to directory where results are written to disk.
seed: (optionally) Integer seed value that can be used to get reproducible runs. If results are written to disk, the 'Run details.txt' file will contain a seed that can be used for reproducing the result.
number_of_replicates: Integer. Number of replicate simulations for each sample.
tag: Character. Used for sub directory name when results_directory is provided.
silent: Logical. If TRUE, then no message will be printed about where the output (if any) was written to disk.

Value

If results_directory is provided, this function has the side effect of writing results to disk.

Return value is a list with simulation results:

call matched call
smash DataFrame with all samples in SMASH format (see SMASH_to_wide_table)
samples Detailed results for each sample
parameter_summary DataFrame with parameters for each sample

Examples

# define two known GlobalFiler genotypes
K1 <- data.frame(
  `Sample Name` = "K1",
  Locus = c("D3S1358", "vWA", "D16S539", "CSF1PO", "TPOX", "D8S1179",
            "D21S11", "D18S51", "D2S441", "D19S433", "TH01", "FGA",
            "D22S1045", "D5S818", "D13S317", "D7S820", "SE33",
            "D10S1248", "D1S1656", "D12S391", "D2S1338"),
  Allele1 = c("14", "15", "11", "11", "8",
              "11", "28", "14", "11", "14", "9.3",
              "21", "15", "9", "9", "10", "14",
              "14", "12", "21", "20"),
  Allele2 = c("16", "18", "13", "11", "11",
              "12", "30", "16", "12", "14", "9.3",
              "24", "16", "11", "12", "10", "18",
              "14", "15", "22", "24"), check.names = FALSE
)

K2 <- data.frame(
  `Sample Name` = "K2",
  Locus = c("D3S1358", "vWA", "D16S539", "CSF1PO", "TPOX", "D8S1179",
            "D21S11", "D18S51", "D2S441", "D19S433", "TH01", "FGA",
            "D22S1045", "D5S818", "D13S317", "D7S820", "SE33",
            "D10S1248", "D1S1656", "D12S391", "D2S1338"),
  Allele1 = c("16", "16", "10", "13", "8",
              "11", "27", "17", "10", "13", "6",
              "23", "16", "11", "11", "9", "22.2",
              "14", "12", "22", "21"),
  Allele2 = c("16", "17", "12", "14", "8",
              "13", "30", "18", "11", "14", "6",
              "25", "17", "11", "11", "12", "28.2",
              "15", "14", "22", "23"), check.names = FALSE
)

# first sample three replicates of a low-level profile of K1 only
gf <- gf_configuration()

sampling_parameters <- list(min_template = 75., max_template = 75,
                            degradation_shape = 2.5, degradation_scale = 1e-3)

single_source_results <- sample_mixtures_from_genotypes(n = 1,
                genotypes = list(K1), sampling_parameters = sampling_parameters,
                number_of_replicates = 3, sample_model = sample_log_normal_model,
                model_settings = gf$log_normal_bwfw_settings)

# now sample two mixtures of K1 and K2 with two replicates each

mix_results <- sample_mixtures_from_genotypes(n = 2,
                genotypes = list(K1, K2), sampling_parameters = sampling_parameters,
                number_of_replicates = 3, sample_model = sample_log_normal_model,
                model_settings = gf$log_normal_bwfw_settings)

Sample mixtures with known genotypes and random parameters according to priors

Usage

Arguments

Value

See also

Examples