Start by creating a dataset and a graph object using the igraph package.
# Libraries
library(ggraph)
library(igraph)
library(tidyverse)
theme_set(theme_void())
# data: edge list
d1 <- data.frame(from="origin", to=paste("group", seq(1,7), sep=""))
d2 <- data.frame(from=rep(d1$to, each=7), to=paste("subgroup", seq(1,49), sep="_"))
edges <- rbind(d1, d2)
# We can add a second data frame with information for each node!
name <- unique(c(as.character(edges$from), as.character(edges$to)))
vertices <- data.frame(
name=name,
group=c( rep(NA,8) , rep( paste("group", seq(1,7), sep=""), each=7)),
cluster=sample(letters[1:4], length(name), replace=T),
value=sample(seq(10,30), length(name), replace=T)
)
# Create a graph object
mygraph <- graph_from_data_frame( edges, vertices=vertices)Circular or linear layout
First of all, you can use a linear or a circular representation using the circular option thanks to the layout argument of ggraph.
Note: a customized version of the circular dendrogram is available here, with more node features and labels.
Edge style
Then you can choose between different styles for your edges. The ggraph package comes with 2 main functions: geom_edge_link and geom_edge_diagonal.
Note that the most usual “elbow” representation is not implemented for hierarchical data yet.
Labels and Nodes
You probably want to add labels to give more insight to your tree. And eventually nodes. This can be done using the geom_node_text and geom_node_point respectively.
Note: the label addition is a bit more tricky for circular dendrogram, a solution is suggested in graph #339.
# Left
ggraph(mygraph, layout = 'dendrogram') +
geom_edge_diagonal() +
geom_node_text(aes( label=name, filter=leaf) , angle=90 , hjust=1, nudge_y = -0.01) +
ylim(-.4, NA)# Right
ggraph(mygraph, layout = 'dendrogram') +
geom_edge_diagonal() +
geom_node_text(aes( label=name, filter=leaf) , angle=90 , hjust=1, nudge_y = -0.04) +
geom_node_point(aes(filter=leaf) , alpha=0.6) +
ylim(-.5, NA)Customize aesthetics
It is a common task to add color or shapes to your dendrogram. It allows to show more clearly the organization of the dataset.
ggraph works the same way as ggplot2. In the aesthetics part of each component, you can use a column of your initial data frame to be mapped to a shape, a color, a size or other..
