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Pedigree Simulation and Visualization with BGmisc

Source: vignettes/v2_pedigree.Rmd
v2_pedigree.Rmd

Introduction

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 functionality, let us generate a pedigree. This pedigree has a total of four generations (Ngen), in which each person who “mates”, grows a family with four offspring (kpc). In our scenario, the number of male and female newborns is equal, but can be adjusted via (sexR). In this illustration 70% of individuals will mate and bear offspring (marR). Such a pedigree structure can be simulated by running the following code:

## Loading Required Libraries
library(BGmisc)
library(ggpedigree)
set.seed(5)
df_ped <- simulatePedigree(
  kpc = 4,
  Ngen = 4,
  sexR = .5,
  marR = .7
)
summary(df_ped)
#>         fam           ID             gen            dadID           momID      
#>  Length   :57   Min.   :10101   Min.   :1.000   Min.   :10102   Min.   :10101  
#>  N.unique : 1   1st Qu.:10306   1st Qu.:3.000   1st Qu.:10204   1st Qu.:10202  
#>  N.blank  : 0   Median :10320   Median :3.000   Median :10307   Median :10306  
#>  Min.nchar: 5   Mean   :10342   Mean   :3.298   Mean   :10263   Mean   :10263  
#>  Max.nchar: 5   3rd Qu.:10416   3rd Qu.:4.000   3rd Qu.:10311   3rd Qu.:10316  
#>                 Max.   :10432   Max.   :4.000   Max.   :10320   Max.   :10318  
#>                                                 NAs    :13      NAs    :13     
#>     spouseID            sex    
#>  Min.   :10101   Length   :57  
#>  1st Qu.:10205   N.unique : 2  
#>  Median :10306   N.blank  : 0  
#>  Mean   :10266   Min.nchar: 1  
#>  3rd Qu.:10311   Max.nchar: 1  
#>  Max.   :10320                 
#>  NAs    :33

The simulation output is a data.frame with 57 rows and 7 columns. Each row corresponds to a simulated individual.

df_ped[21, ]
#>      fam    ID gen dadID momID spouseID sex
#> 21 fam 1 10312   3 10204 10202    10317   M

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.

Summarizing Pedigrees 

summarizeFamilies(df_ped, famID = "fam")$family_summary
#>       fam count gen_mean gen_median gen_min gen_max    gen_sd spouseID_mean
#>    <char> <int>    <num>      <num>   <num>   <num>     <num>         <num>
#> 1:  fam 1    57 3.298246          3       1       4 0.8229935         10266
#>    spouseID_median spouseID_min spouseID_max spouseID_sd
#>              <num>        <num>        <num>       <num>
#> 1:         10305.5        10101        10320    68.79206

Plotting Pedigree

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. The sister package ggpedigree has a much nicer plotting function. It’s also available on CRAN, but it is not a dependency of BGmisc. If you want to use ggpedigree, you can install it with install.packages("ggpedigree") and then use ggplot2 syntax to plot pedigrees.

Single Pedigree Visualization

To visualize a single simulated pedigree, use the the plotPedigree function allows you to visualize the pedigree structure, including family relationships and individual characteristics. The plot displays individuals across generations, with lines connecting parents to their children, and spouses connected by horizontal lines.

library(ggpedigree)

df_ped_recoded <- recodeSex(df_ped, code_male = "M", recode_male = 1, recode_female = 0)

ggpedigree::ggpedigree(df_ped_recoded,
  personID = "ID",
  code_male = 1
)

In the resulting plot, biological males are represented by squares, while biological females are represented by circles, following the standard pedigree conventions.

Visualizing Multiple Pedigrees Side-by-Side

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.

set.seed(8)
# Simulate a family with 3 generations
df_ped_3 <- simulatePedigree(Ngen = 3)

# Simulate a family with 4 generations
df_ped_4 <- simulatePedigree(Ngen = 4)

You can use the ggpedigree package to plot multiple pedigrees side by side. This package allows for more customization and better aesthetics in pedigree visualization.

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.