Basic hierarchical edge bundling

# Libraries
library(ggraph)
library(igraph)
library(tidyverse)
 
# create a data frame giving the hierarchical structure of your individuals
set.seed(1234)
d1 <- data.frame(from="origin", to=paste("group", seq(1,10), sep=""))
d2 <- data.frame(from=rep(d1$to, each=10), to=paste("subgroup", seq(1,100), sep="_"))
hierarchy <- rbind(d1, d2)
 
# create a dataframe with connection between leaves (individuals)
all_leaves <- paste("subgroup", seq(1,100), sep="_")
connect <- rbind( 
  data.frame( from=sample(all_leaves, 100, replace=T) , to=sample(all_leaves, 100, replace=T)), 
  data.frame( from=sample(head(all_leaves), 30, replace=T) , to=sample( tail(all_leaves), 30, replace=T)), 
  data.frame( from=sample(all_leaves[25:30], 30, replace=T) , to=sample( all_leaves[55:60], 30, replace=T)), 
  data.frame( from=sample(all_leaves[75:80], 30, replace=T) , to=sample( all_leaves[55:60], 30, replace=T)) )
connect$value <- runif(nrow(connect))
 
# create a vertices data.frame. One line per object of our hierarchy
vertices  <-  data.frame(
  name = unique(c(as.character(hierarchy$from), as.character(hierarchy$to))) , 
  value = runif(111)
) 
# Let's add a column with the group of each name. It will be useful later to color points
vertices$group  <-  hierarchy$from[ match( vertices$name, hierarchy$to ) ]
 
 
# Create a graph object
mygraph <- graph_from_data_frame( hierarchy, vertices=vertices )
 
# The connection object must refer to the ids of the leaves:
from  <-  match( connect$from, vertices$name)
to  <-  match( connect$to, vertices$name)
 
# Basic graph
ggraph(mygraph, layout = 'dendrogram', circular = TRUE) + 
  geom_conn_bundle(data = get_con(from = from, to = to), alpha=0.2, colour="skyblue", tension = .5) + 
  geom_node_point(aes(filter = leaf, x = x*1.05, y=y*1.05)) +
  theme_void()

Playing with tension

The first thing we can play with is the tension of the connections. A tension of 0 means straight lines. A connection of 1 means maximal curvature: the connections follow the hierarchical structure of the network as much as they can.

Let’s have a look to the effect of different values.

p <- ggraph(mygraph, layout = 'dendrogram', circular = TRUE) + 
  geom_node_point(aes(filter = leaf, x = x*1.05, y=y*1.05)) +
  theme_void()

# 0.1
p +  geom_conn_bundle(data = get_con(from = from, to = to), alpha=0.2, colour="skyblue", width=0.9, 
                      tension=0.1) 
# 0.7
p +  geom_conn_bundle(data = get_con(from = from, to = to), alpha=0.2, colour="skyblue", width=0.9, 
                      tension=0.7) 
#1
p +  geom_conn_bundle(data = get_con(from = from, to = to), alpha=0.2, colour="skyblue", width=0.9, 
                      tension=1) 

Connection features

Then we can play with the colour and transparency of connections. We have seen how to pick up a unique color in the example above. We can also map a specific variable to it like we are used to do with ggplot2 (chart 1 and 2 below)! Another possibility is to make the color evolves along the trajectory: the ‘from’ and the ‘to’ have different color. This is useful if your connection is directed, and gives the nice effect figure 4.

# Use the 'value' column of the connection data frame for the color:
p +  geom_conn_bundle(data = get_con(from = from, to = to), aes(colour=value, alpha=value)) 
 
# In this case you can change the color palette
p +  
  geom_conn_bundle(data = get_con(from = from, to = to), aes(colour=value)) +
  scale_edge_color_continuous(low="white", high="red")
p +  
  geom_conn_bundle(data = get_con(from = from, to = to), aes(colour=value)) +
  scale_edge_colour_distiller(palette = "BuPu")
 
# Color depends of the index: the from and the to are different
p +  
  geom_conn_bundle(data = get_con(from = from, to = to), width=1, alpha=0.2, aes(colour=..index..)) +
  scale_edge_colour_distiller(palette = "RdPu") +
  theme(legend.position = "none")

Node features

Finally we can custom the points as well, like for a classic ggplot2 graphic. It is a good practice to make the color depends of the classification of the point, it allows to make the hierarchy more obvious. In the last example, I map a column to the size of the points!

# Basic usual argument
p=ggraph(mygraph, layout = 'dendrogram', circular = TRUE) + 
  geom_conn_bundle(data = get_con(from = from, to = to), width=1, alpha=0.2, aes(colour=..index..)) +
  scale_edge_colour_distiller(palette = "RdPu") +
  theme_void() +
  theme(legend.position = "none")
 
# just a blue uniform color. Note that the x*1.05 allows to make a space between the points and the connection ends
p + geom_node_point(aes(filter = leaf, x = x*1.05, y=y*1.05), colour="skyblue", alpha=0.3, size=3)
 
# It is good to color the points following their group appartenance
library(RColorBrewer)
p + geom_node_point(aes(filter = leaf, x = x*1.05, y=y*1.05, colour=group),   size=3) +
  scale_colour_manual(values= rep( brewer.pal(9,"Paired") , 30))
 
# And you can adjust the size to whatever variable quite easily!
p + 
  geom_node_point(aes(filter = leaf, x = x*1.05, y=y*1.05, colour=group, size=value, alpha=0.2)) +
  scale_colour_manual(values= rep( brewer.pal(9,"Paired") , 30)) +
  scale_size_continuous( range = c(0.1,10) )