ggtreeSpace 1.2.0
In the evolving field of evolutionary biology and phylogenetics, visualizing phylomorphospace plays a pivotal role in understanding the diversification of traits across species within a phylogenetic framework. Phylomorphospace is a graphical representation that combines phylogenetic information and morphological (trait) data, mapping the evolutionary trajectories of species in a multidimensional space. However, as research progresses, datasets not only increase in size but also in the complexity of their relationships, which makes the visualization process more challenging and demands advanced visualization solutions.
Here, we introduce ggtreeSpace
, a comprehensive visualization tool designed
for plotting fully annotated phylomorphospaces using the grammar of graphics,
offering researchers with extensive control and customization options for
their phylomorphospace plots.
Currently, there are other Bioconductor packages like phytools
that also
support creating a phylomorphospace. phytools
facilitates plotting with
its phylomorphospace
function, which allows for customization and
annotation, including the ability to set edge and node colors. And it also
supports plotting 3d phylomorphospace with phylomorphospace3d
function.
Compares to phytools
, ggtreeSpace
focus on crafting 2D phylomorphospaces
using the grammar of graphics, enabling the creation of fully annotated
visualizations through a layer-by-layer annotation approach. This method
provides researchers with a more intuitive and user-friendly experience in
plotting, enhancing the logic and visualization clarity. ggtreeSpace
not
only includes unique layers specifically designed for phylomorphospace
annotations but also supports layers from the ggplot2 and ggtree communities,
offering a wide range of customization options. Additionally, it supports
adding phylomorphospace as a graphic layer, enabling the combination of
tree-like structures with various types of spaces, such as maps or
histological staining images, thus broadening the applications of
phylomorphospace analysis.
You can use the following commands to install ggtreeSpace
:
if (!require("BiocManager"))
install.packages("BiocManager")
BiocManager::install("ggtreeSpace")
library(ggtree)
library(ggtreeSpace)
library(phytools)
library(ggplot2)
library(dplyr)
ggtreeSpace
serves as a wrapper for ggtree
package. In the past, when
users tried to plot phylomorphospace with ggtree
, they needed to be
familiar with the infrastructure of it and take multiple steps to
achieve the most basic effects. This was not only inconvenient but also
limited its usage in more complex analyses.
tr <- rtree(15)
td <- fastBM(tr, nsim = 2)
tda1 <- fastAnc(tr, td[, 1])
tda2 <- fastAnc(tr, td[, 2])
tda <- cbind(tda1, tda2)
tdn <- rbind(td, tda)
trd <- fortify(tr)
trd <- trd |>
select(-c("x", "y")) |>
mutate(
x = tdn[, 1],
y = tdn[, 2])
p <- ggtree(tr = trd,
layout = "unrooted") +
theme_bw()
## "daylight" method was used as default layout for unrooted tree.
p
Now with ggtreeSpace
, users can plot basic phylomorphospace easily with
the ggtreespace
function, and add annotation to it with the +
operator.
In this example, we add symbolic point to the tip of phylomorphospace.
From the phylomorphospace plot, we can observe the evolutionary trajectories
of different species, illustrating how they diverge and adapt in their
respective trait dimensions. This visual representation allows us to identify
patterns of convergence and divergence among species, highlight instances of
adaptive radiation, and so on.
ggtreespace(tr, td) +
geom_tippoint()
ggtreeSpace also supports adding phylomorphospace as a graphic layer. This can broaden the applications of phylomorphospace analysis by combine the tree-like structure with different types of spaces.
tr1 <- rtree(15)
td1 <- fastBM(tr1, nsim = 2)
ggplot() +
geom_treespace(tr1, td1)
You can also introduce an additional heatmap layer based on your data, adding another dimension of data to better elucidate how this data can affect evolutionary patterns. For example, species may cluster together in the morphospace due to shared environmental adaptations, and we can visualize this through the heatmap. This can provide insights into the underlying mechanisms driving species evolution and diversification.
tr <- rtree(15)
td <- fastBM(tr, nsim = 2, bounds = c(0, Inf))
col <- colorRampPalette(c(
"#FFFFCC", "#FFEDA0", "#FED976", "#FEB24C",
"#FD8D3C", "#FC4E2A", "#E31A1C", "#B10026"
))(24)
tdex <- data.frame(
z = fastBM(tr, nsim = 1, bounds = c(0, Inf)),
node = 1:15
)
p <- ggtreespace(tr, td)
p %<+% tdex +
geom_tippoint() +
geom_tsheatmap(
trait = "z", alpha = 0.7,
resolution = 0.01, bin = 24
) +
scale_fill_manual(
values = col,
guide = guide_colorsteps(show.limits = TRUE)
) +
theme_treespace2() +
theme(
legend.key.height = unit(1, "null"),
legend.justification.top = "right"
)
## Warning: Removed 53303 rows containing non-finite outside the scale range
## (`stat_contour_filled()`).
Here is the output of sessionInfo()
on the system on which this document
was compiled:
## R version 4.4.1 (2024-06-14)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.20-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] dplyr_1.1.4 ggplot2_3.5.1 phytools_2.3-0 maps_3.4.2
## [5] ape_5.8 ggtreeSpace_1.2.0 ggtree_3.14.0 BiocStyle_2.34.0
##
## loaded via a namespace (and not attached):
## [1] fastmatch_1.1-4 gtable_0.3.6 xfun_0.48
## [4] bslib_0.8.0 lattice_0.22-6 numDeriv_2016.8-1.1
## [7] quadprog_1.5-8 vctrs_0.6.5 tools_4.4.1
## [10] generics_0.1.3 yulab.utils_0.1.7 parallel_4.4.1
## [13] tibble_3.2.1 fansi_1.0.6 highr_0.11
## [16] pkgconfig_2.0.3 Matrix_1.7-1 ggplotify_0.1.2
## [19] scatterplot3d_0.3-44 lifecycle_1.0.4 compiler_4.4.1
## [22] farver_2.1.2 deldir_2.0-4 treeio_1.30.0
## [25] tinytex_0.53 munsell_0.5.1 mnormt_2.1.1
## [28] combinat_0.0-8 codetools_0.2-20 ggfun_0.1.7
## [31] htmltools_0.5.8.1 sass_0.4.9 yaml_2.3.10
## [34] lazyeval_0.2.2 pillar_1.9.0 jquerylib_0.1.4
## [37] tidyr_1.3.1 MASS_7.3-61 cachem_1.1.0
## [40] clusterGeneration_1.3.8 magick_2.8.5 iterators_1.0.14
## [43] foreach_1.5.2 nlme_3.1-166 phangorn_2.12.1
## [46] tidyselect_1.2.1 aplot_0.2.3 digest_0.6.37
## [49] purrr_1.0.2 bookdown_0.41 labeling_0.4.3
## [52] fastmap_1.2.0 grid_4.4.1 colorspace_2.1-1
## [55] expm_1.0-0 cli_3.6.3 magrittr_2.0.3
## [58] patchwork_1.3.0 optimParallel_1.0-2 utf8_1.2.4
## [61] withr_3.0.2 scales_1.3.0 DEoptim_2.2-8
## [64] rmarkdown_2.28 igraph_2.1.1 interp_1.1-6
## [67] coda_0.19-4.1 evaluate_1.0.1 knitr_1.48
## [70] doParallel_1.0.17 gridGraphics_0.5-1 rlang_1.1.4
## [73] isoband_0.2.7 Rcpp_1.0.13 glue_1.8.0
## [76] tidytree_0.4.6 BiocManager_1.30.25 jsonlite_1.8.9
## [79] R6_2.5.1 fs_1.6.4