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Sample mixtures with known genotypes and fixed parameters

sample_mixtures_fixed_parameters.Rd

Sample mixtures with known genotypes and fixed parameters

Usage

sample_mixtures_fixed_parameters(
  genotypes,
  parameter_summary,
  model_settings,
  results_directory,
  seed,
  tag = "simulation",
  silent = FALSE
)

Arguments

genotypes

List of contributor genotypes. See sample_contributor_genotypes.

parameter_summary

DataFrame with parameters for each sample.

model_settings

List. Passed to the sample_model function.

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.

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

See also

sample_mixtures

Examples

# simulate autosomal samples with fixed parameters (from csv) and refs (from csv)
parameter_summary <- utils::read.csv(system.file(
"extdata","Example_2p_Parameter_Summary.csv",
package = "simDNAmixtures"))

gf <- gf_configuration()

filename_refs <- system.file("extdata","Example_References_DB.csv",
                            package = "simDNAmixtures")
db_refs <- utils::read.csv(filename_refs, check.names = FALSE)

genotypes <- simDNAmixtures:::.wide_references_to_allele_tables(db_refs)

samples <- sample_mixtures_fixed_parameters(genotypes = genotypes,
                                           parameter_summary = parameter_summary,
                                           model_settings = gf$log_normal_bwfw_settings,
                                           seed = 1)