Phylogenetics
Last updated: 2022-02-23
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Knit directory: Amphibolis_Posidonia_Comparison/
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Here I make a subtree from the Open Tree Of Life API for the species we have.
library(rotl)Warning: package 'rotl' was built under R version 4.1.2library(ggtree)ggtree v3.0.4 For help: https://yulab-smu.top/treedata-book/
If you use ggtree in published research, please cite the most appropriate paper(s):
1. Guangchuang Yu. Using ggtree to visualize data on tree-like structures. Current Protocols in Bioinformatics, 2020, 69:e96. doi:10.1002/cpbi.96
2. Guangchuang Yu, Tommy Tsan-Yuk Lam, Huachen Zhu, Yi Guan. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Molecular Biology and Evolution 2018, 35(12):3041-3043. doi:10.1093/molbev/msy194
3. Guangchuang Yu, David Smith, Huachen Zhu, Yi Guan, Tommy Tsan-Yuk Lam. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution 2017, 8(1):28-36. doi:10.1111/2041-210X.12628library(cowplot)Warning: package 'cowplot' was built under R version 4.1.1library(ggplot2)Warning: package 'ggplot2' was built under R version 4.1.1library(tidyverse)Warning: package 'tidyverse' was built under R version 4.1.1-- Attaching packages --------------------------------------- tidyverse 1.3.1 --v tibble 3.1.5 v dplyr 1.0.7
v tidyr 1.1.4 v stringr 1.4.0
v readr 2.0.2 v forcats 0.5.1
v purrr 0.3.4 Warning: package 'tibble' was built under R version 4.1.1Warning: package 'tidyr' was built under R version 4.1.1Warning: package 'readr' was built under R version 4.1.1Warning: package 'purrr' was built under R version 4.1.1Warning: package 'dplyr' was built under R version 4.1.1Warning: package 'stringr' was built under R version 4.1.1Warning: package 'forcats' was built under R version 4.1.1-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x tidyr::expand() masks ggtree::expand()
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()species <- c('Zostera marina', 'Zostera muelleri', 'Arabidopsis thaliana', 'Thellungiella parvula', 'Populus trichocarpa', 'Vitis vinifera', 'Amborella trichopoda', 'Oryza sativa', 'Zea mays', 'Brachypodium distachyon', 'Spirodela polyrhiza', 'Selaginella moellendorffi', 'Physcomitrella patens', 'Chlamydomonoas reinhardtii', 'Ostreococcus lucimarinus', 'Lemna gibba', 'Posidonia australis' ,'Amphibolis antarctica', 'Wolffia australiana')Let’s call the API to get the OTT IDs for these species, and to double-check we got the right names :)
We should get a tree for 19 species.
taxon_search <- tnrs_match_names(names = species, context_name = "All life")knitr::kable(taxon_search)| search_string | unique_name | approximate_match | ott_id | is_synonym | flags | number_matches |
|---|---|---|---|---|---|---|
| zostera marina | Zostera marina | FALSE | 814202 | FALSE | sibling_higher | 1 |
| zostera muelleri | Zostera muelleri | FALSE | 766348 | FALSE | sibling_higher | 1 |
| arabidopsis thaliana | Arabidopsis thaliana | FALSE | 309263 | FALSE | 1 | |
| thellungiella parvula | Schrenkiella parvula | FALSE | 991614 | TRUE | incertae_sedis_inherited | 1 |
| populus trichocarpa | Populus trichocarpa | FALSE | 8861 | FALSE | 2 | |
| vitis vinifera | Vitis vinifera | FALSE | 756728 | FALSE | 2 | |
| amborella trichopoda | Amborella trichopoda | FALSE | 303950 | FALSE | 1 | |
| oryza sativa | Oryza sativa | FALSE | 709894 | FALSE | 1 | |
| zea mays | Zea mays | FALSE | 605194 | FALSE | 1 | |
| brachypodium distachyon | Brachypodium distachyon | FALSE | 413237 | FALSE | 1 | |
| spirodela polyrhiza | Spirodela polyrhiza | FALSE | 814207 | FALSE | 1 | |
| selaginella moellendorffi | Selaginella moellendorffii | TRUE | 799880 | FALSE | 3 | |
| physcomitrella patens | Physcomitrella patens | FALSE | 821359 | FALSE | 1 | |
| chlamydomonoas reinhardtii | Chlamydomonas reinhardtii | TRUE | 33153 | FALSE | 3 | |
| ostreococcus lucimarinus | Ostreococcus sp. ‘lucimarinus’ | FALSE | 851102 | TRUE | incertae_sedis | 1 |
| lemna gibba | Lemna gibba | FALSE | 431383 | FALSE | 1 | |
| posidonia australis | Posidonia australis | FALSE | 91976 | FALSE | 1 | |
| amphibolis antarctica | Amphibolis antarctica | FALSE | 460583 | FALSE | 1 | |
| wolffia australiana | Wolffia australiana | FALSE | 1059895 | FALSE | 1 |
Let’s write the species names out again for timetree.org
cat(capture.output(cat(taxon_search$unique_name, sep='\n'), file="data/species.csv"))That looks good to me!
ott_in_tree <- ott_id(taxon_search)[is_in_tree(ott_id(taxon_search))]tr <- tol_induced_subtree(ott_ids = ott_in_tree)Warning in collapse_single_cpp(ances = tree$edge[, 1], desc = tree$edge[, :
printing of extremely long output is truncatedWarning in collapse_single_cpp(ances = tree$edge[, 1], desc = tree$edge[, :
printing of extremely long output is truncatedWarning in collapse_singles(tr, show_progress): Dropping singleton nodes
with labels: Streptophyta ott916750, mrcaott2ott50189, mrcaott2ott108668,
mrcaott2ott59852, mrcaott2ott8171, mrcaott2ott70394, Euphyllophyta ott1007992,
Spermatophyta ott10218, mrcaott2ott2645, mrcaott2ott35778, Mesangiospermae
ott5298374, mrcaott2ott10930, mrcaott2ott2441, mrcaott2ott969, mrcaott2ott62529,
mrcaott2ott8379, eudicotyledons ott431495, Gunneridae ott853757, Pentapetalae
ott5316182, mrcaott2ott2464, fabids ott565281, mrcaott2ott371, mrcaott2ott1479,
mrcaott2ott345, Malpighiales ott429482, mrcaott345ott3853, mrcaott3853ott8858,
mrcaott8858ott33097, mrcaott8858ott12186, mrcaott8858ott98085, Salicaceae
ott530183, mrcaott8858ott270454, mrcaott8858ott703490, mrcaott8858ott33085,
mrcaott8858ott102531, mrcaott8858ott502530, mrcaott8858ott737360,
mrcaott8858ott474976, Saliceae ott509390, Populus ott530178, mrcaott8858ott8861,
mrcaott8861ott815941, mrcaott8861ott320722, mrcaott8861ott8867, malvids
ott565277, mrcaott96ott14140, mrcaott96ott50744, mrcaott96ott378,
mrcaott378ott29446, mrcaott378ott1697, Brassicales ott8844, mrcaott378ott307071,
mrcaott378ott32461, mrcaott378ott509555, mrcaott378ott318175,
mrcaott378ott9635, mrcaott378ott125843, mrcaott378ott509568, mrcaott378ott28763,
mrcaott378ott83547, Brassicaceae ott309271, mrcaott378ott299734,
mrcaott378ott4671, mrcaott4671ott58909, mrcaott4671ott6278, mrcaott6278ott15318,
mrcaott6278ott158438, mrcaott6278ott10585, mrcaott6278ott34460,
mrcaott6278ott9083, mrcaott9083ott19798, mrcaott19798ott31487,
mrcaott31487ott88883, mrcaott31487ott152275, mrcaott11023ott24850,
mrcaott11023ott56298, mrcaott11023ott95692, mrcaott11023ott25468,
mrcaott11023ott25476, Schrenkiella (genus in kingdom Archaeplastida)
ott5740975, Vitales ott1069308, mrcaott8384ott10050, mrcaott10050ott337881,
mrcaott10050ott194302, mrcaott10050ott302228, mrcaott10050ott24244,
mrcaott24244ott240260, mrcaott24244ott39768, mrcaott39768ott211705,
mrcaott39768ott175159, mrcaott175159ott602495, mrcaott175159ott246514,
mrcaott175159ott903683, mrcaott175159ott568892, mrcaott175159ott235835,
mrcaott175159ott941927, mrcaott175159ott568880, mrcaott175159ott175164,
mrcaott175159ott509603, mrcaott509603ott805071, Liliopsida ott1058517,
Petrosaviidae ott5308424, mrcaott121ott4474, mrcaott121ott1439,
mrcaott121ott334, commelinids ott225270, mrcaott252ott213153, Poales ott921871,
mrcaott252ott128594, mrcaott252ott1477, mrcaott252ott7120, mrcaott252ott285512,
mrcaott252ott3717, mrcaott252ott272812, mrcaott252ott334529,
mrcaott252ott427739, Poaceae ott508090, mrcaott252ott196505, mrcaott252ott43427,
mrcaott252ott751372, mrcaott252ott11561, Oryzoideae ott641467, Oryzeae
ott415723, mrcaott36487ott890607, Oryzinae ott5744622, Oryza ott135764,
mrcaott67120ott709900, mrcaott67120ott272949, mrcaott67120ott709898,
mrcaott67120ott135756, mrcaott135756ott709892, mrcaott135756ott709887,
mrcaott656ott1473, mrcaott1473ott33975, Brachypodieae ott693951, Brachypodium
ott413242, mrcaott1787ott2051, mrcaott1787ott1985, Panicoideae ott641461,
mrcaott6065ott9925, Andropogonodae ott5737327, Andropogoneae ott475213,
Tripsacinae ott5759522, Zea ott605186, Araceae ott481972, mrcaott290ott3983,
Lemna ott1008186, mrcaott338992ott338994, mrcaott338994ott431388,
mrcaott338994ott431383, mrcaott66494ott407568, mrcaott407568ott432842,
mrcaott407568ott1059896, mrcaott407568ott1059895, mrcaott1059895ott1059900,
Spirodela ott431386, mrcaott5202ott159280, mrcaott5202ott30666,
mrcaott30666ott106181, mrcaott30666ott208913, mrcaott30666ott814198,
mrcaott30666ott40117, Zosteraceae ott637476, mrcaott40117ott91951,
mrcaott40117ott197961, mrcaott197961ott817762, mrcaott197961ott529863,
mrcaott197961ott766348, mrcaott766348ott766350, mrcaott436201ott436206,
mrcaott436201ott436203, mrcaott436201ott814202, mrcaott87589ott256106,
mrcaott256106ott460583, mrcaott460583ott514367, mrcaott460583ott613178,
Amphibolis ott460577, mrcaott91974ott351467, Posidoniaceae ott460581, Posidonia
(genus in kingdom Archaeplastida) ott91949, mrcaott91976ott928713, Amborellales
ott927960, Amborellaceae ott295910, Amborella ott303952, Lycopodiopsida
ott144795, mrcaott3661ott18736, Selaginellales ott144821, Selaginellaceae
ott144818, Selaginella ott144816, mrcaott10602ott10604, mrcaott10604ott10608,
mrcaott10604ott78166, mrcaott10604ott10618, mrcaott101177ott144813,
mrcaott532022ott583202, mrcaott532022ott799880, mrcaott541ott1066,
Bryophyta ott246594, mrcaott1066ott204205, Bryophytina ott471195, Bryopsida
ott821346, mrcaott1066ott86152, mrcaott1066ott1769, mrcaott1769ott7813,
mrcaott7813ott148635, mrcaott7813ott86148, mrcaott7813ott454749,
mrcaott7813ott86154, mrcaott7813ott31044, mrcaott31044ott844044,
mrcaott31044ott1060862, Physcomitrella ott821349, Chlorophyta ott979501,
mrcaott185ott42071, mrcaott185ott1426, mrcaott1426ott1544, mrcaott1544ott8659,
mrcaott1544ott15345, mrcaott1544ott9282, mrcaott9389ott818260,
mrcaott9389ott23557, mrcaott23557ott527099plot(tr)
Let’s get rid of those OTT IDs from the tree, I don’t like that. There’s a helper function for that
tr$tip.label <- strip_ott_ids(tr$tip.label, remove_underscores = TRUE)ggtree(tr) +
geom_tree() +
geom_tiplab(size=3,
fontface='italic') +
theme_tree() +
xlim(0, 15)
Cool! I took the above species list and uploaded to timetree (see Species_timetree.svg)
plot(ggdraw()+cowplot::draw_image('./data/species_timetree.svg'))Warning: Package `magick` is required to draw images. Image not drawn.
Timetree also lets you export the tree timed with MYA
tree <- read.tree('./data/timetree_species.nwk')tree$tip.label <- str_replace_all(tree$tip.label, '_', ' ')
p <- ggplot(tree) +
geom_tree() +
theme_tree2() +
scale_x_continuous(labels = abs) +
geom_tiplab(size=3, fontface='italic')
revts(p) + xlim(-1200, 300)Scale for 'x' is already present. Adding another scale for 'x', which will
replace the existing scale.
sessionInfo()R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)
Matrix products: default
locale:
[1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252
[3] LC_MONETARY=English_Australia.1252 LC_NUMERIC=C
[5] LC_TIME=English_Australia.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4
[5] readr_2.0.2 tidyr_1.1.4 tibble_3.1.5 tidyverse_1.3.1
[9] ggplot2_3.3.5 cowplot_1.1.1 ggtree_3.0.4 rotl_3.0.12
[13] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] nlme_3.1-152 fs_1.5.0 lubridate_1.8.0 progress_1.2.2
[5] httr_1.4.2 rprojroot_2.0.2 tools_4.1.0 backports_1.2.1
[9] bslib_0.3.1 utf8_1.2.2 R6_2.5.1 DBI_1.1.1
[13] lazyeval_0.2.2 colorspace_2.0-2 withr_2.4.2 tidyselect_1.1.1
[17] prettyunits_1.1.1 curl_4.3.2 compiler_4.1.0 git2r_0.28.0
[21] cli_3.0.1 rvest_1.0.2 xml2_1.3.2 labeling_0.4.2
[25] sass_0.4.0 scales_1.1.1 digest_0.6.28 yulab.utils_0.0.4
[29] rmarkdown_2.11 rentrez_1.2.3 pkgconfig_2.0.3 htmltools_0.5.2
[33] highr_0.9 dbplyr_2.1.1 fastmap_1.1.0 rlang_0.4.12
[37] readxl_1.3.1 rstudioapi_0.13 farver_2.1.0 gridGraphics_0.5-1
[41] jquerylib_0.1.4 generics_0.1.1 jsonlite_1.7.2 magrittr_2.0.1
[45] ggplotify_0.1.0 patchwork_1.1.1 Rcpp_1.0.7 munsell_0.5.0
[49] fansi_0.5.0 ape_5.5 lifecycle_1.0.1 stringi_1.7.5
[53] whisker_0.4 yaml_2.2.1 grid_4.1.0 parallel_4.1.0
[57] promises_1.2.0.1 crayon_1.4.1 rncl_0.8.4 lattice_0.20-44
[61] haven_2.4.3 hms_1.1.1 knitr_1.36 pillar_1.6.4
[65] reprex_2.0.1 XML_3.99-0.8 glue_1.4.2 evaluate_0.14
[69] ggfun_0.0.5 modelr_0.1.8 vctrs_0.3.8 treeio_1.16.2
[73] tzdb_0.1.2 httpuv_1.6.3 cellranger_1.1.0 gtable_0.3.0
[77] assertthat_0.2.1 xfun_0.27 broom_0.7.9 tidytree_0.3.7
[81] later_1.3.0 aplot_0.1.2 ellipsis_0.3.2