Annotating both bootstrap (UFboot + SH-aLRT) nodes and species nodes

[Michelle Demers]

Greetings ggtree community,

I am trying to build a tree using output from IQtree2 where I have two legends: one legend for grouping my organisms by species, and a second legend to annotate nodes based on ultrafast bootstrap values + SH-aLRT values. I want only 2 categories for the bootstrap legend: high confidence (UFBoot >= 90 && SH-aLRT >= 80) and low confidence (UFBoot < 90 && SH-aLRT < 80). I have attached a tree ("desired_tree) that I am trying to model this one after. 

Just as a note, the Newick tree is not direct output from IQtree2.  I first load my tree file output into Archaeopteryx to root it at the midpoint, then output it as Newick for processing in R.

Here is my code, but it does not work properly. I think it may be incorrectly annotating the  nodes by bootstrap confidence, and I am having difficulty making two separate legends with colours. I have modelled this code from the answer you gave for the question "Annotating nodes wit bootstrap cutoff" but I can't get it to work the way I want it to. 

Can you help?

library(ggtree)

library(ggplot2)

library(tidyverse)

library(treeio)

tree <- read.newick("scabrum_midpoint_rooted.treefile") 

 #Extract node label

 bootsv <-data.frame(tree[["node.label"]])

 ntip <- length(tree[["tip.label"]])

 nnode <- tree[["Nnode"]]

 SHaLRT <- data.frame(lapply(bootsv, function(x) as.numeric(sub("/.*", "",x))))

 UFBoot <-data.frame(lapply(bootsv, function(x) as.numeric(sub(".*/", "",x))))

 support <- cbind(SHaLRT, UFBoot)

 colnames(support) <- c("SHaLRT", "UFBoot")

 row.names(support) <- c((ntip + 1) : (ntip + nnode))

 #Remove values below SH-aLRT80 <80 and UFB <90

 support <- support[which(support$SHaLRT >=80 & support$UFBoot >=90),]

 #cut data

 support$UFBoot <- cut(as.numeric(support$UFBoot), breaks = 90,right = F,include.lowest = TRUE)

 #Put the results back into the tree.

 tree[["node.label"]] <- support$UFBoot

 #make a color list

 col = c("blue", "orange", "yellow", "green", "purple", "pink")

 names(col) = c(1, 2, 3, 4, 5)

 #plot the tree with bootstrap cutoffs

 tree2 <- ggtree(tree) +

   geom_point2(aes(subset = !isTip,colour = label), size=2.2)+

   geom_tiplab(size = 2.6, align=TRUE, linesize=0.25)+

   ggplot2::xlim(0, 0.4) +

   #geom_text(aes(label=node)) +

   scale_colour_manual("High bootstrap Confidence", #legend name

                       values = col, #legend color

                       labels = c("High confidence", "low confidence"))

#add labelling for forma species

tipcategories <- read.csv("tree_metadata.csv", header = TRUE, stringsAsFactors = FALSE, col.names = c("isolate", "fsp"),)

dd = as.data.frame(tipcategories)

tree2 %<+% dd +

  theme(legend.position = c(0.1, 0.9)) + 

  geom_tippoint(aes(colour = factor(fsp))) +

  guides(colour=guide_legend(title="Forma specialis")) 

Thank you!

Michelle

PhD candidate | The University of Sydney

[Yu, Guangchuang]

I would recommend you to use the tidytree package to extract information from node labels and create a variable to store the category of high and low confidence. Then convert the object to a treedata object and visualize it with ggtree. 

--
1. G Yu*. Using ggtree to visualize data on tree-like structures. Current Protocols in Bioinformatics. 2020, 69:e96. https://doi.org/10.1002/cpbi.96
2. LG Wang, TTY Lam, S Xu, Z Dai, L Zhou, T Feng, P Guo, CW Dunn, BR Jones, T Bradley, H Zhu, Y Guan, Y Jiang, G Yu*. treeio: an R package for phylogenetic tree input and output with richly annotated and associated data. Molecular Biology and Evolution. 2020, 37(2):599-603. http://dx.doi.org/10.1093/molbev/msz240
3. G Yu*, TTY Lam, H Zhu, Y Guan*. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Molecular Biology and Evolution, 2018, 35(2):3041-3043. https://doi.org/10.1093/molbev/msy194
4. G Yu, DK Smith, H Zhu, Y Guan, TTY 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. https://doi.org/10.1111/2041-210X.12628
5. Book: https://yulab-smu.top/treedata-book/
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--

--~--~---------~--~----~------------~-------~--~----~

Guangchuang Yu PhD

Professor, Director

Department of Bioinformatics
School of Basic Medical Sciences

Southern Medical University

Guangzhou, China

www: https://yulab-smu.top

-~----------~----~----~----~------~----~------~--~---

[George Pacheco]

Hello Guangchuang,

Would you be so kind as to quickly demonstrate how to do that? Basically, I have the same issue myself as I would like to have categorized bootstraps and not only above a certain number.

Thanks a lot in advance, George. 

 basePhylo_annot +
  geom_point2(aes(label = label, subset = !is.na(as.numeric(label)) & as.numeric(label) > 85), shape = 21, size = 1.65, fill = "#155211", colour = "#155211", alpha = .85, stroke = .075, show.legend = FALSE) +
  geom_tippoint(aes(fill = BioStatus, subset = !is.na(BioStatus)), size = 1.65, stroke = .075, colour = "#000000", alpha = 1, shape = 21, na.rm = TRUE) +
  geom_strip("PigeonIsland_05-GBS", "Trincomalee_01-GBS", barsize = 3.5, color = "#d9d9d9", label = "Group A", fontsize = 6, offset = .75, offset.text = 1.5) +
  geom_strip("Abadeh_04-GBS", "Torshavn_02-GBS", barsize = 3.5, color = "#bdbdbd", label = "Group B", fontsize = 6, offset = .75, offset.text = 1.5) +
  geom_strip("TelAviv_07-GBS", "Isfahan_03-GBS", barsize = 3.5, color = "#969696", label = "Group C", fontsize = 6, offset = .75, offset.text = 7) +
  geom_strip("Barcelona_15-GBS", "Monterrey_05-GBS", barsize = 3.5, color = "#636363", label = "Group D", fontsize = 6, offset = .75, offset.text = 9) +
  geom_strip("Berlin_04-GBS", "London_05-GBS", barsize = 3.5, color = "#252525", label = "Group E", fontsize = 6, offset = .75, offset.text = 1.5) +
  scale_fill_manual(values = c("#44AA99", "#F0E442", "#E69F00", "#56B4E9", "#ff0000"), labels = gsub("_", " ", levels(Data_annot$BioStatus)), na.translate = FALSE) +
  theme(panel.spacing = margin(t = 0, b = 0, r = 0, l = 0),
        panel.border = element_blank(),
        plot.margin = margin(t = 0, b = 0, r = 0, l = 0),
        legend.position = c(.11, .875),
        legend.spacing.y = unit(.4, "cm"),
        legend.key.height = unit(.45, "cm"),
        legend.margin = margin(t = 0, b = 0, r = 0, l = 0),
        legend.box.margin = margin(t = 5, b = -20, r = 0, l = 30)) +
  guides(colour = guide_legend(title = "Species", title.theme = element_text(size = 14, face = "bold"),
                               label.theme = element_text(size = 10, face = "italic"), override.aes = list(size = .8, starshape = NA), order = 1),
         fill = guide_legend(title = "Biological Status", title.theme = element_text(size = 14, face = "bold"),
                             label.theme = element_text(size = 10),
                             override.aes = list(starshape = 21, size = 2.85, alpha = .9, starstroke = .0015), order = 2))