I am hoping someone can help me with the formating from phylo.to.plot() or suggest another method that can produce a similar output.
I have followed tutorial(s) here to produce an output but it seems difficult to alter the resulting figures.
Briefly these are my questions. I will expand further below.
How to plot a subregion of a "WorldHires" map, not entire region?
Change the shape of the points on the map, but maintain the colour?
Add gradient of continuous variable to map
Reproducible example:
Here is a very basic tree with some randomly assigned geographic locations
myTree <- ape::read.tree(text='((A, B), ((C, D), (E, F)));')
plot(myTree)
# It needs to be rooted for `phylo.to.map()` to work
myTree$branch.length = NULL
rooted_cladogram = ape::compute.brlen(myTree)
# Sample information
Sample <- c("A","B","C","D","E","F")
coords <- matrix(c(56.001966,57.069417,50.70228, 51.836213, 54.678997, 54.67831,-5.636926,-2.47805,-3.8975018, -2.235444,-3.4392211, -1.751833), nrow=6, ncol=2)
rownames(coords) <- Sample
head(coords)
## Plot phylo.to.map
obj<-phylo.to.map(rooted_cladogram,coords,database="worldHires", regions="UK",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
plot(obj,direction="rightwards",fsize=0.5,cex.points=c(0,1), lwd=c(3,1),ftype="i")
Plot output here:
Question 1: How do I plot a subregion of a "WorldHires" map, not the entire region?
I would like to only have mainland Britain which is a subregion of the "UK" in the WorldHires database. To access it normally I would do:
map1 <- ggplot2::map_data(map = "worldHires", region = c("UK"),xlim=c(-11,3), ylim=c(49,59))
GB <- subset(map1, subregion=="Great Britain")
# Plot
GB_plot<- ggplot(GB )+
geom_polygon(aes(x = long, y = lat, group = group), fill = "white", colour = "black")+
theme_classic()+
theme(axis.line=element_blank(),
axis.text=element_blank(),
axis.ticks=element_blank(),
axis.title=element_blank(),
panel.border = element_blank())
Which looks like this:
I have tried but it ignore the subregion argument.
obj<-phylo.to.map(ttree,coords,database="worldHires", regions="UK", subregion="Great Britain",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
Is there a way to provide it directly with a map instead of using WorldHires?
Question 2: How do I change the shape of the points on the map but keep maintain the colour?
I want to use shapes on the map to indicate the 3 major clade on my tree geographically. However, when I add a pch argument in, it correctly changes the shapes but the points then become black instead of following the colour that they were before. The lines from the tree to the map maintain the colour, it is just the points themselves that seem to turn black.
This is how I have tried to change the shape of the points:
# Original code - points
cols <-setNames(colorRampPalette(RColorBrewer::brewer.pal(n=6, name="Dark2"))(Ntip(myTree)),myTree$tip.label)
obj<-phylo.to.map(rooted_cladogram,coords,database="worldHires", regions="UK",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
plot(obj,direction="rightwards",fsize=0.5,cex.points=c(0,1), colors=cols,lwd=c(3,1),ftype="i")
Point and lines are coloured. I would like to change the shape of points
# Code to change points = but points are no longer coloured
shapes <- c(rep(2,2),rep(1,2),rep(0,2))
obj<-phylo.to.map(rooted_cladogram,coords,database="worldHires", regions="UK",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
plot(obj,direction="rightwards",fsize=0.5,cex.points=c(0,1), colors=cols,pch=shapes,lwd=c(3,1),ftype="i")
Output: The shapes are changed but they are no longer coloured in:
Question 3: How do I add a gradient to the map?
Given this fake dataset, how to I create a smoothed gradient of the value variable?
Any help and advice on this would be very much appreciated.
It would also be useful to know how to change the size of points
Thank you very much in advance,
Eve
I improved (somewhat) on my comments by using the map you made in your question. Here's the code:
library(mapdata)
library(phytools)
library(ggplot2)
myTree <- ape::read.tree(text='((A, B), ((C, D), (E, F)));')
plot(myTree)
# It needs to be rooted for `phylo.to.map()` to work
myTree$branch.length = NULL
rooted_cladogram = ape::compute.brlen(myTree)
# Sample information
Sample <- c("A","B","C","D","E","F")
coords <- matrix(
c(56.001966,
57.069417,
50.70228,
51.836213,
54.678997,
54.67831,
-5.636926,
-2.47805,
-3.8975018,
-2.235444,
-3.4392211,
-1.751833),
nrow=6,
ncol=2)
rownames(coords) <- Sample
head(coords)
obj <- phylo.to.map(
rooted_cladogram,
coords,
database="worldHires",
regions="UK",
plot=FALSE,
xlim=c(-11,3),
ylim=c(49,59),
direction="rightwards")
# Disable default map
obj2 <- obj
obj2$map$x <- obj$map$x[1]
obj2$map$y <- obj$map$y[1]
# Set plot parameters
cols <- setNames(
colorRampPalette(
RColorBrewer::brewer.pal(n=6, name="Dark2"))(Ntip(myTree)),myTree$tip.label)
shapes <- c(rep(2,2),rep(1,2),rep(0,2))
sizes <- c(1, 2, 3, 4, 5, 6)
# Plot phylomap
plot(
obj2,
direction="rightwards",
fsize=0.5,
cex.points=0,
colors=cols,
pch=shapes,
lwd=c(3,1),
ftype="i")
# Plot new map area that only includes GB
uk <- map_data(
map = "worldHires",
region = "UK")
gb <- uk[uk$subregion == "Great Britain",]
points(x = gb$long,
y = gb$lat,
cex = 0.001)
# Plot points on map
points(
x = coords[,2],
y = coords[,1],
pch = shapes,
col = cols,
cex = sizes)
e: Use sf object instead of points to illustrate GB. It is tough to provide more advice beyond this on how to add symbology for your spatially varying variable, but sf is popular and very well documented, e.g. https://r-spatial.github.io/sf/articles/sf5.html. Let me know if you have any other questions!
ee: Added lines to plot name and symbol on tips.
eee: Added gradient dataset to map.
library(phytools)
library(mapdata)
library(ggplot2)
library(sf)
myTree <- ape::read.tree(text='((A, B), ((C, D), (E, F)));')
plot(myTree)
# It needs to be rooted for `phylo.to.map()` to work
myTree$branch.length = NULL
rooted_cladogram = ape::compute.brlen(myTree)
# Sample information
Sample <- c("A","B","C","D","E","F")
coords <- matrix(c(56.001966,57.069417,50.70228, 51.836213, 54.678997, 54.67831,-5.636926,-2.47805,-3.8975018, -2.235444,-3.4392211, -1.751833), nrow=6, ncol=2)
rownames(coords) <- Sample
head(coords)
obj <- phylo.to.map(
rooted_cladogram,
coords,
database="worldHires",
regions="UK",
plot=FALSE,
xlim=c(-11,3),
ylim=c(49,59),
direction="rightwards")
# Disable default map
obj2 <- obj
obj2$map$x <- obj$map$x[1]
obj2$map$y <- obj$map$y[1]
## Plot tree portion of map
# Set plot parameters
cols <- setNames(
colorRampPalette(
RColorBrewer::brewer.pal(n=6, name="Dark2"))(Ntip(myTree)),myTree$tip.label)
shapes <- c(rep(2,2),rep(1,2),rep(0,2))
sizes <- c(1, 2, 3, 4, 5, 6)
# Plot phylomap
plot(
obj2,
direction="rightwards",
fsize=0.5,
cex.points=0,
colors=cols,
pch=shapes,
lwd=c(3,1),
ftype="i")
tiplabels(pch=shapes, col=cols, cex=0.7, offset = 0.2)
tiplabels(text=myTree$tip.label, col=cols, cex=0.7, bg = NA, frame = NA, offset = 0.2)
## Plot GB portion of map
# Plot new map area that only includes GB
uk <- map_data(map = "worldHires", region = "UK")
gb <- uk[uk$subregion == "Great Britain",]
# Convert GB to sf object
gb_sf <- st_as_sf(gb, coords = c("long", "lat"))
# Covert to polygon
gb_poly <- st_sf(
aggregate(
x = gb_sf$geometry,
by = list(gb_sf$region),
FUN = function(x){st_cast(st_combine(x), "POLYGON")}))
# Add polygon to map
plot(gb_poly, col = NA, add = TRUE)
## Load and format gradient data as sf object
# Load data
g <- read.csv("gradient_data.txt", sep = " ", na.strings = c("NA", " "))
# Check for, then remove NAs
table(is.na(g))
g2 <- g[!is.na(g$Lng),]
# For demonstration purposes, make dataset easier to manage
# Delete this sampling line to use the full dataset
g2 <- g2[sample(1:nrow(g2), size = 1000),]
# Create sf point object
gpt <- st_as_sf(g2, coords = c("Lng", "Lat"))
## Set symbology and plot
# Cut data into 5 groups based on "value"
groups <- cut(gpt$value,
breaks = seq(min(gpt$value), max(gpt$value), len = 5),
include.lowest = TRUE)
# Set colors
gpt$colors <- colorRampPalette(c("yellow", "red"))(5)[groups]
# Plot
plot(gpt$geometry, pch = 16, col = gpt$colors, add = TRUE)
## Optional legend for gradient data
# Order labels and colors for the legend
lev <- levels(groups)
# Used rev() here to make colors in correct order
fil <- rev(levels(as.factor(gpt$colors)))
legend("topright", legend = lev, fill = fil, add = TRUE)
## Plot sample points on GB
# Plot points on map
points(
x = coords[,2],
y = coords[,1],
pch = shapes,
col = cols,
cex = sizes)
see here for more info on gradient symbology and legends: R: Gradient plot on a shapefile
I am trying to plot a dendritic network (a river network) in R, using the ggnet2 function, and I want the y axis on the plot to be meaningful... specifically I want it to represent the basin area. I am looking for a method, then, that will calculate x coordinates so that the network displays nicely, with no crossing lines. How might I do this? See the code and example images below. In the first image, the y coordinates are specified to equal the area, which is what I want, but the x-coordinates are non-optimized so the graph looks ugly. In the second image, Fruchterman-Rhinegold placement looks great but the y coordinates are obviously arbitrary. I'm not wedded to using ggnet2, but I do want the network links to be angular (e.g. not like a clustering dendrogram with vertical links between nodes). Thanks!
[![library(GGally)
library(network)
library(sna)
graphmatrix <- matrix(c(0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0), nrow=33)
sitenumbers <- c(26,27,30,3,31,6,4,18,32,5,11,21,29,16,8,7,14,25,13,19,23,9,15,12,17,20,28,10,1,2,24,22,33)
areas <- c(4.2,4.2,4.5,2.2,4.8,2.5,2.4,3.6,5.3,2.5,3.1,3.7,4.4,3.4,2.8,2.7,3.3,4.2,3.3,3.6,3.9,3.1,3.4,3.1,3.5,3.7,4.3,3.1,1,1.6,4.1,3.7,5.7)
wsnet <- network(graphmatrix, directed=TRUE)
layout <- gplot.layout.fruchtermanreingold(wsnet, NULL)
wsnet %v% 'sitenumber' = sitenumbers
wsnet %v% 'area' = areas
wsnet %v% 'randomnumber'= sample(sitenumbers)
ggnet2(wsnet, label='sitenumber')
#You can specify y coordinates, but then you need to also specify x coords, so there's tons of line crossing... I want to "optimize" the x coords.
ggnet2(wsnet, label='sitenumber', mode=c('randomnumber','area'))][1]][1]
Here would be a ggraph solution to the problem. We'll start out by laying out a dendrogram and then tell ggraph to use the area as y positions.
library(tidygraph)
library(ggraph)
gr <- as_tbl_graph(wsnet)
lay <- create_layout(gr, "dendrogram")
lay$y <- lay$area
ggraph(lay) +
geom_edge_link() +
geom_node_point(size = 10, shape = 21, fill = "white") +
geom_node_text(aes(label = sitenumber))
Now obviously this is not perfect with intersecting lines and such, but it's a good starting point. You could tweak some positions manually:
lay$x[lay$sitenumber %in% c(12, 10, 17, 20, 28)] <- lay$x[lay$sitenumber %in% c(12, 10, 17, 20, 28)] + 1
lay$x[lay$sitenumber %in% c(1, 2)] <- lay$x[lay$sitenumber %in% c(1, 2)] - 2
lay$x[lay$sitenumber == 27] <- lay$x[lay$sitenumber == 27] + 2
lay$x[lay$sitenumber == 26] <- lay$x[lay$sitenumber == 26] + 3
ggraph(lay) +
geom_edge_link() +
geom_node_point(size = 10, shape = 21, fill = "white") +
geom_node_text(aes(label = sitenumber))
Adjust flavours to taste.