2 Introduction

Pedigree diagrams show family relationships. The arrangement usually follows some simple conventions. Older people are toward the top of the diagram. Individuals from the same generation are on the same row. Gender is usually shown as either a square symbol (male) or circular symbol (female).

Building a pedigree diagram is a convenient way to store information about family structures. This may be your own family, your friends and acquaintances, or people you’re studying.

First, we’ll get some libraries initialized.

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## Activate the Core Packages
library(tidyverse) ## Brings in a core of useful functions
library(gt)        ## Tables

## special libraries
library(kinship2)  ## Core package to calculate and plot
library(R.devices) ## External plot files (e.g., PNG)
library(tinypedigree) ## For the tiny_pedigree function

You start with a table. This lists each individual and their parents. You also need the gender of each person. There is one row for each individual. Pedigree diagrams are constructed automatically from data in the table. The data are built up from linkages between children and their parents.

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## Create the main data table
data <- read_csv(col_names = TRUE, show_col_types=FALSE, file=
    "ID,    dad,  mom,  gender
     John,  NA,   NA,   male
     Mary,  NA,   NA,   female   
     Bill,  John, Mary, male
     Hank,  John, Mary, male   
     Andy,  John, Mary, male    
     Ruth,  NA,   NA,   female     
     Jane,  Andy, Ruth, female")

## Print a table 
gt(data) |>
  tab_source_note(source_note="Source: Demonstration data")

ID	dad	mom	gender
John	NA	NA	male
Mary	NA	NA	female
Bill	John	Mary	male
Hank	John	Mary	male
Andy	John	Mary	male
Ruth	NA	NA	female
Jane	Andy	Ruth	female
Source: Demonstration data

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## Generate the pedigree diagram
tiny_pedigree(data=data)

In some situations, individuals listed in the data table have no children. As a result, these people can’t be linked into the rest of the table without some additional information. This requires a second table that lists two people in the original data table who should be linked. Note that everyone needs to be listed as a row in the main data table.

If you have a situation where an individual listed in the main data table is not linked by their children, this person is not plotted in the pedigree diagram.

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## Create the main data table
data <- read_csv(col_names = TRUE, show_col_types=FALSE, file=
    "ID,    dad,  mom,  gender
     John,  NA,   NA,   male
     Mary,  NA,   NA,   female   
     Bill,  John, Mary, male
     Hank,  John, Mary, male   
     Andy,  John, Mary, male    
     Ruth,  NA,   NA,   female     
     Jane,  Andy, Ruth, female
     Lucy,  NA,   NA,   female")

## Print a table 
gt(data) |>
  tab_source_note(source_note="Source: Demonstration data")

ID	dad	mom	gender
John	NA	NA	male
Mary	NA	NA	female
Bill	John	Mary	male
Hank	John	Mary	male
Andy	John	Mary	male
Ruth	NA	NA	female
Jane	Andy	Ruth	female
Lucy	NA	NA	female
Source: Demonstration data

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## Generate the pedigree diagram
tiny_pedigree(data=data)

Did not plot the following people: Lucy

Woops. The code chunk probably didn’t run quite as expected. There is a “missing” person (“Lucy” in this example).

Married individuals without children: The “missing” person is added with an additional table. Here (and in the other examples), this table is called “links.” There are two ID columns for the ID values (from the main data table) of the two people to be linked. Note that these are married people who have no children. The need for this links table is logical as the primary use of a pedigree diagram is to show the relationships of offspring to their predecessors. In that use, a couple without children has no value and, therefore, wouldn’t be shown. As we are interested in family structure, we need to add this kind of link.

Creating links between the two married individuals is shown in the next example by using data from the previous chunk. Note that the order of the people in a link doesn’t matter. You can have two or more childless couples in this table. The order of the couples doesn’t matter, either.

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## Link married people who don't have children
links <- read_csv(col_names=TRUE, show_col_type=FALSE, file=
    "id1,   id2
     Lucy,  Bill")

## Generate the pedigree diagram
tiny_pedigree(data=data, links=links)

Tables are useful in their own right as you can store information about individuals besides their parentage. Birth and death dates are an obvious type of supplemental data. But you’re not limited to demographic information.

In the following example, additional information is added to each individual. The original data are then merged with this new set.

A column (color) is used to highlight all individuals who play a stringed instrument.

The table produced from the merged data doesn’t show all the columns. In this case, the dad and mom columns, which are required for construction of the pedigree, do not need to be shown in this more general summary of the individuals.

All the NA values are converted to blank cells in the table. This is useful so the NA values don’t distract from the more informative data.

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## The master data table from the previous chunks is used here

## New information for the data table
new <- read_csv(col_names = TRUE, show_col_types=FALSE, file=
    "ID,    born,  died, instrument, color  
     John,  1905,  1978, violin,     orange
     Mary,  1907,  1982, viola,      orange 
     Bill,  1928,  1997, NA,         gray
     Hank,  1930,  1943, NA,         gray    
     Andy,  1932,  2010, violin,     orange   
     Ruth,  1934,  2019, harp,       orange        
     Jane,  1958,  NA,   violin,     orange 
     Lucy,  1930,  2005, NA,         gray")

## Merge the data
data <- merge(data, new, by="ID")

## Build a table
gt(data) |>
  cols_hide(columns=c(dad, mom, color)) |>
  sub_missing(missing_text = "") |>
  tab_source_note(source_note="Source: Demonstration data")

ID	gender	born	died	instrument
Andy	male	1932	2010	violin
Bill	male	1928	1997
Hank	male	1930	1943
Jane	female	1958		violin
John	male	1905	1978	violin
Lucy	female	1930	2005
Mary	female	1907	1982	viola
Ruth	female	1934	2019	harp
Source: Demonstration data

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## Add a hilite column so colors will fill symbols
data$hilite <- TRUE

## Generate the pedigree
tiny_pedigree(data=data, links=links)

Note that the color column is used automatically in the pedigree diagram. This is just one of the enhancements possible to make the pedigree diagram a useful visual tool.