The examples show some challenges, work-around, and exploitation of the features of both the tiny_pedigree function and gt tables.
Initialize the needed packages.
## 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 functionThere are a lot of individuals to fit on this pedigree diagram. Perhaps too many as the typesize, in particular, must be very small.
Note that there is an interaction between the typesize and fold parameters. Folding the names doesn’t help.
Warning: row (generation) spacing seems to be disrupted at the lowest row in a many-generation diagram if there are several individuals at the lowest level.
data <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"ID, dad, mom, gender, born, died
Charles Wentworth, NA, NA, male, 1648, 1780
Amariah Wentworth, Charles Wentworth, Bethiah Fenno, male, 1719, 1799
Bethiah Fenno, NA, NA, female, 1692, 1780
Rebecca Shepard, NA, NA, female, 1723, 1791
Elijah Wentworth, Amariah Wentworth, Rebecca Shepard, male, 1775, 1810
Elijah S. Estes, NA, NA, male, 1814, 1887
Zebiah Walker Wentworth, Elijah Wentworth, Lucy Walker, female, 1810, 1887
Lucy Walker, NA, NA, female, NA, NA
Mary Adeline Palmer, NA, NA, female, 1848, 1918
Lorenzo Langston Estes, Elijah S. Estes, Zebiah Walker Wentworth, male, 1839, 1909
Addie Estes, Lorenzo Langston Estes, Mary Adeline Palmer, female, NA, NA
Charles A. Bridges, NA, NA, male, 1877, NA
Charles L. Bridges, Charles A. Bridges, Addie Estes, male, 1912, 2001
Mary Jane Bridges, NA, NA, female, 1912, 2016
Thomas Bridges, Charles L. Bridges, Mary Jane Bridges, male, 1938, NA
Kent Bridges, Charles L. Bridges, Mary Jane Bridges, male, 1941, NA")
## Assign or calculate enhancements
data$hilite <- TRUE
data <- data |>
mutate(color = case_when(
gender == "female" ~ "lightblue",
gender == "male" ~ "lightsalmon1"))
## Create a presentation table
gt(data) |>
cols_hide(columns = c(dad, mom, gender, hilite, color)) |>
tab_source_note(source_note="Source: Bridges family documents")| ID | born | died |
|---|---|---|
| Charles Wentworth | 1648 | 1780 |
| Amariah Wentworth | 1719 | 1799 |
| Bethiah Fenno | 1692 | 1780 |
| Rebecca Shepard | 1723 | 1791 |
| Elijah Wentworth | 1775 | 1810 |
| Elijah S. Estes | 1814 | 1887 |
| Zebiah Walker Wentworth | 1810 | 1887 |
| Lucy Walker | NA | NA |
| Mary Adeline Palmer | 1848 | 1918 |
| Lorenzo Langston Estes | 1839 | 1909 |
| Addie Estes | NA | NA |
| Charles A. Bridges | 1877 | NA |
| Charles L. Bridges | 1912 | 2001 |
| Mary Jane Bridges | 1912 | 2016 |
| Thomas Bridges | 1938 | NA |
| Kent Bridges | 1941 | NA |
| Source: Bridges family documents | ||
tiny_pedigree(data=data, textsize=0.5, symbolsize=0.8, fold=FALSE)
Breaking the pedigree into smaller sets is a way around some of the limitations seen in the last pedigree diagram.
## Divide the data into two halves
## First Half
data1 <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"ID, dad, mom, gender, born, died
Charles Wentworth, NA, NA, male, 1648, 1780
Amariah Wentworth, Charles Wentworth, Bethiah Fenno, male, 1719, 1799
Bethiah Fenno, NA, NA, female, 1692, 1780
Rebecca Shepard, NA, NA, female, 1723, 1791
Elijah Wentworth, Amariah Wentworth, Rebecca Shepard, male, 1775, 1810
Elijah S. Estes, NA, NA, male, 1814, 1887
Zebiah Walker Wentworth, Elijah Wentworth, Lucy Walker, female, 1810, 1887
Lucy Walker, NA, NA, female, NA, NA
Lorenzo Langston Estes, Elijah S. Estes, Zebiah Walker Wentworth, male, 1839, 1909")
## Second Half
data2 <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"ID, dad, mom, gender, born, died
Mary Adeline Palmer, NA, NA, female, 1848, 1918
Lorenzo Langston Estes, NA, NA, male, 1839, 1909
Addie Estes, Lorenzo Langston Estes, Mary Adeline Palmer, female, NA, NA
Charles A. Bridges, NA, NA, male, 1877, NA
Charles L. Bridges, Charles A. Bridges, Addie Estes, male, 1912, 2001
Mary Jane Bridges, NA, NA, female, 1912, 2016
Thomas Bridges, Charles L. Bridges, Mary Jane Bridges, male, 1938, NA
Kent Bridges, Charles L. Bridges, Mary Jane Bridges, male, 1941, NA")
## Assign or calculate enhancements to the first half
data1$hilite <- TRUE
data1 <- data1 |>
mutate(color = case_when(
gender == "female" ~ "lightblue",
gender == "male" ~ "lightsalmon1"))
## Generate a pedigree from the first half
tiny_pedigree(data=data1, symbolsize=1.1, fold=FALSE)
## Assign or calculate enhancements to the second half
data2$hilite <- TRUE
data2 <- data2 |>
mutate(color = case_when(
gender == "female" ~ "lightblue",
gender == "male" ~ "lightsalmon1"))
## Generate a pedigree from the second half
tiny_pedigree(data=data2, textsize=0.6, symbolsize=1.1, fold=FALSE)
## Join (row bind) the two halves
## The first two lines of second half are not needed
data <- rbind(data1, data2[3:nrow(data2),])
## Create a presentation table
gt(data) |>
cols_hide(columns=c(dad, mom, gender, hilite, color)) |>
tab_source_note(source_note="Source: Bridges family documents")| ID | born | died |
|---|---|---|
| Charles Wentworth | 1648 | 1780 |
| Amariah Wentworth | 1719 | 1799 |
| Bethiah Fenno | 1692 | 1780 |
| Rebecca Shepard | 1723 | 1791 |
| Elijah Wentworth | 1775 | 1810 |
| Elijah S. Estes | 1814 | 1887 |
| Zebiah Walker Wentworth | 1810 | 1887 |
| Lucy Walker | NA | NA |
| Lorenzo Langston Estes | 1839 | 1909 |
| Addie Estes | NA | NA |
| Charles A. Bridges | 1877 | NA |
| Charles L. Bridges | 1912 | 2001 |
| Mary Jane Bridges | 1912 | 2016 |
| Thomas Bridges | 1938 | NA |
| Kent Bridges | 1941 | NA |
| Source: Bridges family documents | ||
You can use the color coding to provide information that is not related to the demographic properties of the data.
In the following example, research progress is noted on the pedigree diagram with a color code (green means already interviewed).
## Read the basic data (all people are listed)
data <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"ID, dad, mom, gender, interviewed
Genji, NA, NA, male, no
Shizuko, NA, NA, female, yes
Hiroshi, Genji, Shizuko, male, no
Tamaru, Genji, Shizuko, male, yes
Osamu, Genji, Shizuko, male, yes
Akari, NA, NA, female, no
Fumiko, Osamu, Akari, female, no
Yui, NA, NA, female, yes
Shota, Hiroshi, Yui, male, no
Sakura, NA, NA, female, yes")
## Read links for people without children
links <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"id1, id2
Tamaru, Sakura")
## Print a presenttion table
gt(data) |>
sub_missing(missing_text = "") |>
cols_hide(columns=c(gender)) |>
tab_source_note(source_note="Source: Example data")| ID | dad | mom | interviewed |
|---|---|---|---|
| Genji | no | ||
| Shizuko | yes | ||
| Hiroshi | Genji | Shizuko | no |
| Tamaru | Genji | Shizuko | yes |
| Osamu | Genji | Shizuko | yes |
| Akari | no | ||
| Fumiko | Osamu | Akari | no |
| Yui | yes | ||
| Shota | Hiroshi | Yui | no |
| Sakura | yes | ||
| Source: Example data | |||
## Calculate and assign column properties
data <- data |>
mutate(color = case_when(
interviewed == "yes" ~ "lightgreen",
interviewed == "no" ~ "gray85")) |>
mutate(hilite = TRUE)
## Generate and plot the pedigree structure
## You need to use the link parameter for "no-children" couples
tiny_pedigree(data=data, links=links)
This is an example of the complexity when there are quite a few children. The software seems to handle this number of individuals, but it is likely close to the limit.
data <- read_csv(col_names = TRUE, show_col_types=FALSE, file=
"ID, father, mother, sex, status
Howard, NA, NA, male, 1
Viola, NA, NA, female, 1
William, Howard, Viola, male, 0
Alice, Howard, Viola, female, 1
Wesley, Howard, Viola, male, 0
David, Howard, Viola, male, 0
Nancy, Howard, Viola, female, 0
Kimo, Howard, Viola, male, 0
Edward, Howard, Viola, male, 0
Claudia, NA, NA, female, 0
Karen, NA, NA, female, 1
Ayesha, NA, NA, female, 0
Laurie, NA, NA, female, 0
Michael, NA, NA, male, 0
Michiko, NA, NA, female, 0
Linda, NA, NA, female, 0
Kim, NA, NA, male, 0
Angel, William, Claudia, female, 0
Jolene, William, Claudia, female, 0
Pono, Wesley, Karen, male, 0
Gabriel, Wesley, Ayesha, male, 0
Sokah, Wesley, Laurie, female, 0
Jessie, Edward, Michiko, male, 0
Nalani, Kimo, Linda, female, 0
Leilani, Michael, Alice, female, 0
Sefu, Michael, Alice, male, 0
Eric, NA, NA, male, 0
Scott, NA, NA, male, 0
Shane, Scott, Angel, male, 0
Skyler, Scott, Angel, female, 0
Kalani, NA, NA, male, 0
Dysen, Kalani, Jolene, male, 0
Jordyn, Kalani, Jolene, female, 0
Laura, NA, NA, female, 0
Salem, Sefu, Laura, male, 0
Jennifer, NA, NA, female, 0
Christopher, Gabriel, Jennifer, male, 0
Vik, NA, NA, female, 0")
## Links for individuals without children
links <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"id1, id2
Kim, Nancy
Eric, Leilani
Jessie, Vik")
## Generate a presentation table
gt(data) |>
cols_hide(columns=c(sex, status)) |>
sub_missing(missing_text = "") |>
tab_source_note(source_note="Source: Fuxxxxto family data")| ID | father | mother |
|---|---|---|
| Howard | ||
| Viola | ||
| William | Howard | Viola |
| Alice | Howard | Viola |
| Wesley | Howard | Viola |
| David | Howard | Viola |
| Nancy | Howard | Viola |
| Kimo | Howard | Viola |
| Edward | Howard | Viola |
| Claudia | ||
| Karen | ||
| Ayesha | ||
| Laurie | ||
| Michael | ||
| Michiko | ||
| Linda | ||
| Kim | ||
| Angel | William | Claudia |
| Jolene | William | Claudia |
| Pono | Wesley | Karen |
| Gabriel | Wesley | Ayesha |
| Sokah | Wesley | Laurie |
| Jessie | Edward | Michiko |
| Nalani | Kimo | Linda |
| Leilani | Michael | Alice |
| Sefu | Michael | Alice |
| Eric | ||
| Scott | ||
| Shane | Scott | Angel |
| Skyler | Scott | Angel |
| Kalani | ||
| Dysen | Kalani | Jolene |
| Jordyn | Kalani | Jolene |
| Laura | ||
| Salem | Sefu | Laura |
| Jennifer | ||
| Christopher | Gabriel | Jennifer |
| Vik | ||
| Source: Fuxxxxto family data | ||
## Generate the pedigree data structure (with no-children couples)
tiny_pedigree(data=data, links=links,
symbolsize=0.8, textsize = 0.4, fold=FALSE)
## Read the data
data <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"ID, dad, mom, gender, dead
Yuji Soxxxxbo, NA, NA, male, 1
Kunichi Fuxxxxto, NA, NA, male, 1
Kiyo Soxxxxbo, NA, NA, female, 1
Ayako Soxxxxbo, Yuji Soxxxxbo, Kiyo Soxxxxbo, female, 1
Satayoshi Fuxxxxto, Yuji Soxxxxbo, Kiyo Soxxxxbo, male, 1
Shigeo Soxxxxbo, Yuji Soxxxxbo, Kiyo Soxxxxbo, male, 1
Howard Fuxxxxto, Kunichi Fuxxxxto, Kiyo Soxxxxbo, male, 1
Hirui Fuxxxxto, Kunichi Fuxxxxto, Kiyo Soxxxxbo, female, 1
Hisano Fuxxxxra, Kunichi Fuxxxxto, Kiyo Soxxxxbo, female, 1
George Fuxxxxra, NA, NA, male, 1
Mom Soxxxxbo, NA, NA, female, 1
Carol Soxxxxbo, NA, NA, female, 0
Clyde Soxxxxbo, Satayoshi Fuxxxxto, Mom Soxxxxbo, male, 1
Jane Soxxxxbo, Satayoshi Fuxxxxto, Mom Soxxxxbo, female, 0
Karen Soxxxxbo, Clyde Soxxxxbo, Carol Soxxxxbo, female, 0
Amy Soxxxxbo, Clyde Soxxxxbo, Carol Soxxxxbo, female, 1
Kiyoko Soxxxxbo, NA, NA, female, 1
Michael Soxxxxbo, Shigeo Soxxxxbo, Kiyoko Soxxxxbo, male, 0
Wendy Soxxxxbo, NA, NA, female, 0
Myra Yamachi, George Fuxxxxra, Hisano Fuxxxxra, male, 0
David Yamachi, NA, NA, male, 1")
## Links for the individuals without children
links <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"id1, id2
Michael Soxxxxbo, Wendy Soxxxxbo
Myra Yamachi, David Yamachi")
## Create a presentation table
gt(data) |>
cols_hide(columns=c(gender, dead)) |>
sub_missing(missing_text = "") |>
tab_source_note(source_note="Source: Fuxxxxto family data")| ID | dad | mom |
|---|---|---|
| Yuji Soxxxxbo | ||
| Kunichi Fuxxxxto | ||
| Kiyo Soxxxxbo | ||
| Ayako Soxxxxbo | Yuji Soxxxxbo | Kiyo Soxxxxbo |
| Satayoshi Fuxxxxto | Yuji Soxxxxbo | Kiyo Soxxxxbo |
| Shigeo Soxxxxbo | Yuji Soxxxxbo | Kiyo Soxxxxbo |
| Howard Fuxxxxto | Kunichi Fuxxxxto | Kiyo Soxxxxbo |
| Hirui Fuxxxxto | Kunichi Fuxxxxto | Kiyo Soxxxxbo |
| Hisano Fuxxxxra | Kunichi Fuxxxxto | Kiyo Soxxxxbo |
| George Fuxxxxra | ||
| Mom Soxxxxbo | ||
| Carol Soxxxxbo | ||
| Clyde Soxxxxbo | Satayoshi Fuxxxxto | Mom Soxxxxbo |
| Jane Soxxxxbo | Satayoshi Fuxxxxto | Mom Soxxxxbo |
| Karen Soxxxxbo | Clyde Soxxxxbo | Carol Soxxxxbo |
| Amy Soxxxxbo | Clyde Soxxxxbo | Carol Soxxxxbo |
| Kiyoko Soxxxxbo | ||
| Michael Soxxxxbo | Shigeo Soxxxxbo | Kiyoko Soxxxxbo |
| Wendy Soxxxxbo | ||
| Myra Yamachi | George Fuxxxxra | Hisano Fuxxxxra |
| David Yamachi | ||
| Source: Fuxxxxto family data | ||
## Color all the symbols
data$color <- "gray85"
data$hilite <- TRUE
## Modify the color of a specific row
data$color[7] <- "pink"
## Generate the plot the pedigree
tiny_pedigree(data=data, links=links,
textsize = 0.7,
symbolsize = 0.8)
## Read the data
data <- read_csv(col_names = TRUE, show_col_types=FALSE, file=
"ID, father, mother, sex, status
Herbert Kaxxxxra, NA, NA, male, 1
Hideko Kaxxxxra, NA, NA, female, 1
Brian Kaxxxxra, Herbert Kaxxxxra, Hideko Kaxxxxra, male, 0
Nancy Kaxxxxra, NA, NA, female, 0
Candy Kaxxxxra, Herbert Kaxxxxra, Hideko Kaxxxxra, female, 0
Debbie Kaxxxxra, Herbert Kaxxxxra, Hideko Kaxxxxra, female, 0
Neil Naxxta, NA, NA, male, 0
Doreen Kaxxxxra, Herbert Kaxxxxra, Hideko Kaxxxxra, female, 0
Ayako Soxxxxbo, NA, NA, female, 1
Jinpachi Naxxxxxma, NA, NA, male, 1
Colleen Kaxxxxra, Herbert Kaxxxxra, Hideko Kaxxxxra, female, 0
Kevin Naxxxxxma, Jason Naxxxxxma, Eleanor Oyxma, male, 0
Terry Naxxxxxma, Jason Naxxxxxma, Eleanor Oyxma, male, 0
Cory Naxxxxxma, Terry Naxxxxxma, Colleen Kaxxxxra, male, 0
Karen Naxxxxxma, Terry Naxxxxxma, Colleen Kaxxxxra, female, 0
Jason Naxxxxxma, Jinpachi Naxxxxxma, Ayako Soxxxxbo, male, 1
Sachiko Naxxxxxma, Jinpachi Naxxxxxma, Ayako Soxxxxbo, female, 1
Jerry Naxxxxxma, Jinpachi Naxxxxxma, Ayako Soxxxxbo, male, 1
Eleanor Oyxma, NA, NA, female, 1
Sharon Naxxxxxma, Jason Naxxxxxma, Eleanor Oyxma, female, 0
Alyssa Dexxxon, David Dexxxon, Sharon Naxxxxxma, female, 0
Kellianne Dexxxon, David Dexxxon, Sharon Naxxxxxma, female, 0
Christopher Dexxxon, David Dexxxon, Sharon Naxxxxxma, male, 0
David Dexxxon, NA, NA, male, 0")
## Links for married individuals with no children
links <- read_csv(col_names=TRUE, show_col_types=FALSE, file=
"id1, id2
Brian Kaxxxxra, Nancy Kaxxxxra
Neil Naxxta, Debbie Kaxxxxra")
## Create a presentation table
gt(data) |>
cols_hide(columns=c(sex, status)) |>
sub_missing(missing_text = "") |>
tab_source_note(source_note="Source: Kaxxxxra family data")| ID | father | mother |
|---|---|---|
| Herbert Kaxxxxra | ||
| Hideko Kaxxxxra | ||
| Brian Kaxxxxra | Herbert Kaxxxxra | Hideko Kaxxxxra |
| Nancy Kaxxxxra | ||
| Candy Kaxxxxra | Herbert Kaxxxxra | Hideko Kaxxxxra |
| Debbie Kaxxxxra | Herbert Kaxxxxra | Hideko Kaxxxxra |
| Neil Naxxta | ||
| Doreen Kaxxxxra | Herbert Kaxxxxra | Hideko Kaxxxxra |
| Ayako Soxxxxbo | ||
| Jinpachi Naxxxxxma | ||
| Colleen Kaxxxxra | Herbert Kaxxxxra | Hideko Kaxxxxra |
| Kevin Naxxxxxma | Jason Naxxxxxma | Eleanor Oyxma |
| Terry Naxxxxxma | Jason Naxxxxxma | Eleanor Oyxma |
| Cory Naxxxxxma | Terry Naxxxxxma | Colleen Kaxxxxra |
| Karen Naxxxxxma | Terry Naxxxxxma | Colleen Kaxxxxra |
| Jason Naxxxxxma | Jinpachi Naxxxxxma | Ayako Soxxxxbo |
| Sachiko Naxxxxxma | Jinpachi Naxxxxxma | Ayako Soxxxxbo |
| Jerry Naxxxxxma | Jinpachi Naxxxxxma | Ayako Soxxxxbo |
| Eleanor Oyxma | ||
| Sharon Naxxxxxma | Jason Naxxxxxma | Eleanor Oyxma |
| Alyssa Dexxxon | David Dexxxon | Sharon Naxxxxxma |
| Kellianne Dexxxon | David Dexxxon | Sharon Naxxxxxma |
| Christopher Dexxxon | David Dexxxon | Sharon Naxxxxxma |
| David Dexxxon | ||
| Source: Kaxxxxra family data | ||
## Generate and plot the pedigree diagram
tiny_pedigree(data = data, links = links,
symbolsize = 0.8,
textsize = 0.6)