This vignette provides a detailed guide to the pedigree-related
functions within the BGmisc
package.
Unlike Tolstoy, where only happy families are alike, all
pedigrees are alike – or at least, all simulated pedigrees are alike.
The simulatePedigree
function generates a pedigree with a
user-specified number of generations and individuals per generation.
This function provides users the opportunity to test family models in
pedigrees with a customized pedigree length and width.
These pedigrees can be simulated as a function of several parameters, including the number of children per mate, generations, sex ratio of newborns, and mating rate. Given that large family pedigrees are difficult to collect or access, simulated pedigrees serve as an efficient tool for researchers. These simulated pedigrees are useful for building family-based statistical models, and evaluating their statistical properties, such as power, bias, and computational efficiency.
To illustrate this, let us generate a pedigree. This pedigree has a total of four generations, in which each person who “mates”, grows a family with four offspring. In our scenario, the number of male and female newborns is equal. In this illustration 70% of individuals will mate and bear offspring. Such a pedigree structure can be simulated by running:
set.seed(5)
df_ped <- simulatePedigree(kpc = 4,
Ngen = 4,
sexR = .5,
marR = .7)
summary(df_ped)
#> fam ID gen dadID
#> Length:57 Min. : 10011 Min. :1.000 Min. : 10012
#> Class :character 1st Qu.: 10036 1st Qu.:3.000 1st Qu.: 10024
#> Mode :character Median :100312 Median :3.000 Median : 10037
#> Mean : 59171 Mean :3.298 Mean : 42859
#> 3rd Qu.:100416 3rd Qu.:4.000 3rd Qu.:100311
#> Max. :100432 Max. :4.000 Max. :100320
#> NA's :13
#> momID spt sex
#> Min. : 10011 Min. : 10011 Length:57
#> 1st Qu.: 10022 1st Qu.: 10025 Class :character
#> Median : 10036 Median : 10036 Mode :character
#> Mean : 42859 Mean : 40124
#> 3rd Qu.:100316 3rd Qu.:100311
#> Max. :100318 Max. :100320
#> NA's :13 NA's :33
The simulation output is a data.frame
with 57 rows and 7
columns. Each row corresponds to a simulated individual.
The columns represents the individual’s family ID, the individual’s personal ID, the generation the individual is in, the IDs of their father and mother, the ID of their spouse, and the biological sex of the individual, respectively.
Pedigrees are visual diagrams that represent family relationships
across generations. They are commonly used in genetics to trace the
inheritance of specific traits or conditions. This vignette will guide
you through visualizing simulated pedigrees using the
plotPedigree
function. This function is a wrapper function
for Kinship2’s base R plotting.
To visualize a single simulated pedigree, use the
plotPedigree()
function.
# Plot the simulated pedigree
plotPedigree(df_ped)
#> Pedigree object with 57 subjects, family id= 1
#> Bit size= 75
#> Did not plot the following people: 10032
In the resulting plot, biological males are represented by squares, while biological females are represented by circles, following the standard pedigree conventions.
If you wish to compare different pedigrees side by side, you can plot them together. For instance, let’s visualize pedigrees for families spanning three and four generations, respectively.
# Simulate a family with 3 generations
df_ped_3 <- simulatePedigree(Ngen = 3)
# Simulate a family with 4 generations
df_ped_4 <- simulatePedigree(Ngen = 4)
# Set up plotting parameters for side-by-side display
par(mfrow = c(1, 2))
# Plot the 3-generation pedigree
plotPedigree(df_ped_3, width = 3)
#> Pedigree object with 13 subjects, family id= 1
#> Bit size= 14
# Plot the 4-generation pedigree
plotPedigree(df_ped_4, width = 1)
#> Pedigree object with 29 subjects, family id= 1
#> Bit size= 34
By examining the side-by-side plots, you can contrast and analyze the structures of different families, tracing the inheritance of specific traits or conditions if needed.