Simulate Pedigrees This function simulates

Simulate Pedigrees This function simulates "balanced" pedigrees based on a group of parameters: 1) k - Kids per couple; 2) G - Number of generations; 3) p - Proportion of males in offspring; 4) r - Mating rate.

Usage

simulatePedigree(
  kpc = 3,
  Ngen = 4,
  sexR = 0.5,
  marR = 2/3,
  rd_kpc = FALSE,
  balancedSex = TRUE,
  balancedMar = TRUE,
  verbose = FALSE,
  personID = "ID",
  momID = "momID",
  dadID = "dadID",
  spouseID = "spouseID",
  code_male = "M",
  code_female = "F",
  fam_shift = 1L,
  beta = FALSE
)

SimPed(...)

Arguments

kpc

Number of kids per couple. An integer >= 2 that determines how many kids each fertilized mated couple will have in the pedigree. Default value is 3. Returns an error when kpc equals 1.

Ngen

Number of generations. An integer >= 2 that determines how many generations the simulated pedigree will have. The first generation is always a fertilized couple. The last generation has no mated individuals.

sexR

Sex ratio of offspring. A numeric value ranging from 0 to 1 that determines the proportion of males in all offspring in this pedigree. For instance, 0.4 means 40 percent of the offspring will be male.

marR

Mating rate. A numeric value ranging from 0 to 1 which determines the proportion of mated (fertilized) couples in the pedigree within each generation. For instance, marR = 0.5 suggests 50 percent of the offspring in a specific generation will be mated and have their offspring.

rd_kpc

logical. If TRUE, the number of kids per mate will be randomly generated from a poisson distribution with mean kpc. If FALSE, the number of kids per mate will be fixed at kpc.

balancedSex

Not fully developed yet. Always TRUE in the current version.

balancedMar

Not fully developed yet. Always TRUE in the current version.

verbose

logical If TRUE, message progress through stages of algorithm

personID

character. Name of the column in ped for the person ID variable

momID

character. Name of the column in ped for the mother ID variable

dadID

character. Name of the column in ped for the father ID variable

spouseID

The name of the column that will contain the spouse ID in the output data frame. Default is "spID".

code_male

The value to use for males. Default is "M"

code_female

The value to use for females. Default is "F"

fam_shift

An integer to shift the person ID. Default is 1L. This is useful when simulating multiple pedigrees to avoid ID conflicts.

beta

logical or character. Controls which algorithm version to use:

FALSE, "base", or "original" (default): Use the original algorithm. Slower but ensures exact reproducibility with set.seed().
TRUE or "optimized": Use the optimized algorithm with 4-5x speedup. Produces statistically equivalent results but not identical to base version due to different random number consumption. Recommended for large simulations where speed matters more than exact reproducibility.

Note: Both versions are mathematically correct and produce valid pedigrees with the same statistical properties (sex ratios, mating rates, etc.). The optimized version uses vectorized operations instead of loops, making it much faster for large pedigrees.

...

Additional arguments to be passed to other functions.

Value

A data.frame with each row representing a simulated individual. The columns are as follows:

fam: The family id of each simulated individual. It is 'fam1' in a single simulated pedigree.
ID: The unique personal ID of each simulated individual. The first digit is the fam id; the fourth digit is the generation the individual is in; the following digits represent the order of the individual within their pedigree. For example, 100411 suggests this individual has a family id of 1, is in the 4th generation, and is the 11th individual in the 4th generation.
gen: The generation the simulated individual is in.
dadID: Personal ID of the individual's father.
momID: Personal ID of the individual's mother.
spID: Personal ID of the individual's mate.
sex: Biological sex of the individual. F - female; M - male.

Examples

set.seed(5)
df_ped <- simulatePedigree(
  kpc = 4,
  Ngen = 4,
  sexR = .5,
  marR = .7
)
summary(df_ped)
#>      fam                  ID             gen            dadID      
#>  Length:57          Min.   :10101   Min.   :1.000   Min.   :10102  
#>  Class :character   1st Qu.:10306   1st Qu.:3.000   1st Qu.:10204  
#>  Mode  :character   Median :10320   Median :3.000   Median :10307  
#>                     Mean   :10342   Mean   :3.298   Mean   :10263  
#>                     3rd Qu.:10416   3rd Qu.:4.000   3rd Qu.:10311  
#>                     Max.   :10432   Max.   :4.000   Max.   :10320  
#>                                                     NA's   :13     
#>      momID            spID           sex           
#>  Min.   :10101   Min.   :10101   Length:57         
#>  1st Qu.:10202   1st Qu.:10205   Class :character  
#>  Median :10306   Median :10306   Mode  :character  
#>  Mean   :10263   Mean   :10266                     
#>  3rd Qu.:10316   3rd Qu.:10311                     
#>  Max.   :10318   Max.   :10320                     
#>  NA's   :13      NA's   :33