knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) Biocpkg <- function (pkg){ sprintf("[%s](http://bioconductor.org/packages/%s)", pkg, pkg) } CRANpkg <- function(pkg){ cran <- "https://CRAN.R-project.org/package" fmt <- "[%s](%s=%s)" sprintf(fmt, pkg, cran, pkg) }
library(ggtreeExtra) library(ggstar) library(ggplot2) library(ggtree) library(treeio) library(ggnewscale)
Phylogenetic trees was often used with associated data in various biological studies. r Biocpkg("ggtree")
, a flexible R package to visualize phylogenetic tree, had been developed by GuangChuang Yu [@yu2017ggtree]. It provided geom_facet
function to align associated graphs to the tree [@yu2018two; @yu2020ggtree]. However, This function only works with rectangular
, roundrect
, ellipse
and slanted
layouts to present tree data on external panels. There is no direct supports in ggtree
to present associated data on the outer rings of phylogenetic tree in circular
, fan
or radial
layout. To solve the problem, We developed ggtreeExtra
, which can align associated graphs to circular
, fan
or radial
and other rectangular
layout tree. ggtreeExtra
provides function, geom_fruit
to align graphs to the tree. But the associated graphs will align at the different position of external panels of the tree. So we also developed geom_fruit_list
to add multiple layers at the same position of external panels of tree. Furthermore, axis
of external layers can be added using the axis.params=list(axis="x",...)
in geom_fruit
. The grid lines
of external layers can be added using the grid.params=list()
in geom_fruit
. These functions are based on r CRANpkg("ggplot2")
using grammar of graphics [@hadlyggplot2]. More vignettes can be found on the chapter10
of online book.
You can use the following to install it
# for devel if(!requireNamespace("remotes", quietly=TRUE)){ install.packages("remotes") } remotes::install_github("YuLab-SMU/ggtreeExtra") # for release if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") ## BiocManager::install("BiocUpgrade") ## you may need this BiocManager::install("ggtreeExtra")
To show the package profiling, I will use a tree file downloaded from plotTree. The associated datasets were simulated, All of them have one column contained taxa labels of tree.
# The path of tree file. trfile <- system.file("extdata", "tree.nwk", package="ggtreeExtra") # The path of file to plot tip point. tippoint1 <- system.file("extdata", "tree_tippoint_bar.csv", package="ggtreeExtra") # The path of first layer outside of tree. ring1 <- system.file("extdata", "first_ring_discrete.csv", package="ggtreeExtra") # The path of second layer outside of tree. ring2 <- system.file("extdata", "second_ring_continuous.csv", package="ggtreeExtra") # The tree file was imported using read.tree. If you have other tree format files, you can use corresponding functions from treeio package to read it. tree <- read.tree(trfile) # This dataset will to be plotted point and bar. dat1 <- read.csv(tippoint1) knitr::kable(head(dat1)) # This dataset will to be plotted heatmap dat2 <- read.csv(ring1) knitr::kable(head(dat2)) # This dataset will to be plotted heatmap dat3 <- read.csv(ring2) knitr::kable(head(dat3)) # The format of the datasets is the long shape for ggplot2. If you have short shape dataset, # you can use `melt` of `reshape2` or `pivot_longer` of `tidyr` to convert it. # We use ggtree to create fan layout tree. p <- ggtree(tree, layout="fan", open.angle=10, size=0.5) p ## Next, we can use %<+% of ggtree to add annotation dataset to tree. #p1 <- p %<+% dat1 #p1 ## We use geom_star to add point layer outside of tree. #p2 <- p1 + # geom_star( # mapping=aes(fill=Location, size=Length, starshape=Group), # starstroke=0.2 # ) + # scale_size_continuous( # range=c(1, 3), # guide=guide_legend( # keywidth=0.5, # keyheight=0.5, # override.aes=list(starshape=15), # order=2) # ) + # scale_fill_manual( # values=c("#F8766D", "#C49A00", "#53B400", "#00C094", "#00B6EB", "#A58AFF", "#FB61D7"), # guide="none" # don't show the legend. # ) + # scale_starshape_manual( # values=c(1, 15), # guide=guide_legend( # keywidth=0.5, # adjust width of legend # keyheight=0.5, # adjust height of legend # order=1 # adjust the order of legend for multiple legends. # ), # na.translate=FALSE # to remove the NA legend. # ) #p2 # Or if you don't use %<+% to import annotation dataset, instead of `data` parameter of `geom_fruit`. # You should specify the column contained tip labels to y axis of `mapping`, here is `y=ID`. # the `position` parameter was set to `identity` to add the points on the tip nodes. p2 <- p + geom_fruit( data=dat1, geom=geom_star, mapping=aes(y=ID, fill=Location, size=Length, starshape=Group), position="identity", starstroke=0.2 ) + scale_size_continuous( range=c(1, 3), # the range of size. guide=guide_legend( keywidth=0.5, keyheight=0.5, override.aes=list(starshape=15), order=2 ) ) + scale_fill_manual( values=c("#F8766D", "#C49A00", "#53B400", "#00C094", "#00B6EB", "#A58AFF", "#FB61D7"), guide="none" ) + scale_starshape_manual( values=c(1, 15), guide=guide_legend( keywidth=0.5, keyheight=0.5, order=1 ) ) p2 # Next, we will add a heatmap layer on the outer ring of p2 using `geom_tile` of `ggplot2`. # Since we want to map some variable of dataset to the `fill` aesthetics of `geom_tile`, but # the `fill` of p2 had been mapped. So I need use `new_scale_fill` of `ggnewscale` package to initialize it. p3 <- p2 + new_scale_fill() + geom_fruit( data=dat2, geom=geom_tile, mapping=aes(y=ID, x=Pos, fill=Type), offset=0.08, # The distance between external layers, default is 0.03 times of x range of tree. pwidth=0.25 # width of the external layer, default is 0.2 times of x range of tree. ) + scale_fill_manual( values=c("#339933", "#dfac03"), guide=guide_legend(keywidth=0.5, keyheight=0.5, order=3) ) p3 # You can also add heatmap layer for continuous values. p4 <- p3 + new_scale_fill() + geom_fruit( data=dat3, geom=geom_tile, mapping=aes(y=ID, x=Type2, alpha=Alpha, fill=Type2), pwidth=0.15, axis.params=list( axis="x", # add axis text of the layer. text.angle=-45, # the text angle of x-axis. hjust=0 # adjust the horizontal position of text of axis. ) ) + scale_fill_manual( values=c("#b22222", "#005500", "#0000be", "#9f1f9f"), guide=guide_legend(keywidth=0.5, keyheight=0.5, order=4) ) + scale_alpha_continuous( range=c(0, 0.4), # the range of alpha guide=guide_legend(keywidth=0.5, keyheight=0.5, order=5) ) # Then add a bar layer outside of the tree. p5 <- p4 + new_scale_fill() + geom_fruit( data=dat1, geom=geom_bar, mapping=aes(y=ID, x=Abundance, fill=Location), #The 'Abundance' of 'dat1' will be mapped to x pwidth=0.4, stat="identity", orientation="y", # the orientation of axis. axis.params=list( axis="x", # add axis text of the layer. text.angle=-45, # the text size of axis. hjust=0 # adjust the horizontal position of text of axis. ), grid.params=list() # add the grid line of the external bar plot. ) + scale_fill_manual( values=c("#F8766D", "#C49A00", "#53B400", "#00C094", "#00B6EB", "#A58AFF", "#FB61D7"), guide=guide_legend(keywidth=0.5, keyheight=0.5, order=6) ) + theme(#legend.position=c(0.96, 0.5), # the position of legend. legend.background=element_rect(fill=NA), # the background of legend. legend.title=element_text(size=7), # the title size of legend. legend.text=element_text(size=6), # the text size of legend. legend.spacing.y = unit(0.02, "cm") # the distance of legends (y orientation). ) p5
In the section, we generated a simulated tree and simulated associated datasets. Then, geom_fruit_list
was used to add multiple layers at the same position of external panels of the tree.
# To reproduce. set.seed(1024) # generate 100 tip point tree. tr <- rtree(100) # generate three datasets, which are the same except the third column name. dt <- data.frame(id=tr$tip.label, value=abs(rnorm(100)), group=c(rep("A",50),rep("B",50))) df <- dt dtf <- dt colnames(df)[[3]] <- "group2" colnames(dtf)[[3]] <- "group3" # plot tree p <- ggtree(tr, layout="fan", open.angle=0) p # the first ring. p1 <- p + geom_fruit( data=dt, geom=geom_bar, mapping=aes(y=id, x=value, fill=group), orientation="y", stat="identity" ) + new_scale_fill() p1 # the second ring # geom_fruit_list is a list, which first element must be layer of geom_fruit. p2 <- p1 + geom_fruit_list( geom_fruit( data = df, geom = geom_bar, mapping = aes(y=id, x=value, fill=group2), orientation = "y", stat = "identity" ), scale_fill_manual(values=c("blue", "red")), # To map group2 new_scale_fill(), # To initialize fill scale. geom_fruit( data = dt, geom = geom_star, mapping = aes(y=id, x=value, fill=group), size = 2.5, color = NA, starstroke = 0 ) ) + new_scale_fill() p2 # The third ring p3 <- p2 + geom_fruit( data=dtf, geom=geom_bar, mapping = aes(y=id, x=value, fill=group3), orientation = "y", stat = "identity" ) + scale_fill_manual(values=c("#00AED7", "#009E73")) p3
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