ggtreeSpace-Getting Started
Introduction
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.
Installation
You can use the following commands to install
ggtreeSpace:
Demonstration
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.
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 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.
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 30741 rows containing non-finite outside the scale range
## (`stat_contour_filled()`).
Session information
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: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 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: Etc/UTC
## 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_1.3.0 ggtree_3.13.2 BiocStyle_2.35.0
##
## 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_1.29.2
## [25] mnormt_2.1.1 munsell_0.5.1 combinat_0.0-8
## [28] codetools_0.2-20 ggfun_0.1.7 htmltools_0.5.8.1
## [31] sys_3.4.3 buildtools_1.0.0 sass_0.4.9
## [34] yaml_2.3.10 lazyeval_0.2.2 pillar_1.9.0
## [37] jquerylib_0.1.4 tidyr_1.3.1 MASS_7.3-61
## [40] cachem_1.1.0 clusterGeneration_1.3.8 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 labeling_0.4.3 maketools_1.3.1
## [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