Last updated: 2021-05-23
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Knit directory: wildlife-bacteria/
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library(ggtree)
library(treeio)
library(tidyverse)
library(ggtreeExtra)
library(ggstar)
library(readr)
library(ggrepel)
library(ape)
library(phangorn)Tutorial here Tutorial here here here here blog post
Load data
toi_tree <- read.iqtree("data/dada2_tois/IQTREE/all_tois_aln.fasta.treefile") # load IQTREE output
metadata_tree <- read_csv("data/dada2_tois/IQTREE/all_tois_aln.csv")Make tree
toi_tree = ggtree(toi_tree, branch.length='none', layout='circular')
toi_tree1 = toi_tree %<+% metadata_tree
toi_tree2 = toi_tree1 +
aes(color = Family)
ggsave("tree_toi.pdf", plot = toi_tree2, path = "output/plots", width = 20, height = 20, units = "cm")
# bootstrap
bsp = tree@phylo$node.label
# Add node info
toi_tree3 = toi_tree2 + geom_text(aes(label = label), hjust = 1, vjust = -0.4, size = 3) + geom_nodelab(aes(label = FALSE))Add note support information
ggtree(toi_tree, layout = 'circular') + geom_label_repel(aes(label=UFboot, fill=UFboot)) +
theme(legend.position = c(.1, .8)) + scale_fill_viridis_c()toi_tree2 %>% gheatmap(metadata_tree, offset=8, width=0.6, colnames=FALSE) %>% scale_x_ggtree() pp + theme(legend.position=“right”)
To identify node numbers
toi_tree2n = toi_tree2 + geom_text(aes(label=node), hjust=-.3)Load data
bor_iqtree <- read.iqtree("data/taxa_trees/Borrelia/IQTREE_root/borrelia16sv34_trim_43.fasta.treefile") # load IQTREE output
# newtick tree
bor_ntree <- read.tree("data/taxa_trees/Borrelia/IQTREE_root/tree.newick") # load newick tree
# Metadata
library(readr)
metadata <- read_csv("data/taxa_trees/Borrelia/IQTREE_root/metadata.csv",
col_types = cols(X6 = col_skip(), X7 = col_skip(), X8 = col_skip(), X9 = col_skip(), X10 = col_skip()))ggtree(bor_tree) + geom_label_repel(aes(label=UFboot, fill=UFboot)) +
theme(legend.position = c(.1, .8)) + scale_fill_viridis_c()Edit labels
genus <- c(metadata$Genus)
species <- c(metadata$Species)
acc <- c(metadata$Accession)
d <- data.frame(label =bor_iqtree@phylo$tip.label, genus = genus,
species = species, acc = acc)Make tree with new labels
bor_ntree2 = ggtree(bor_iqtree) %<+% d + geom_tiplab(aes(label=paste0('italic(', genus, ')~bolditalic(', species, ')~', acc)), parse=T) + geom_point2(aes(subset=(node==46)), shape=23, size=5, fill='black') + geom_hilight(mapping=aes(subset = node %in% c(46))) + scale_fill_manual(values=c("darkgreen"))Save
ggsave("bor_ntree2.pdf", plot = bor_ntree2, path = "output/plots", width = 70, height = 40, units = "cm")Load data
# load IQTREE output
bart_tree <- read.iqtree("data/taxa_trees/Bartonella/IQTREE_root/bartonella_clustalw_57seq_533bp.fasta.treefile")# simple load with branch support and tip labels
ggtree(bart_tree) + geom_text(aes(label = label))
#Identify node numbers
ggtree(bart_tree) + geom_text(aes(label=node), hjust=-.3)bart_tree\(root.edge <- 80 ggtree(b) + geom_tiplab() + geom_rootedge() ggtree(bart_tree) + geom_tiplab() + geom_rootedge() ggtree(bart_tree) + geom_tiplab() + geom_rootedge(rootedge = 80) bart_tree\)root.edge <- 80 ggtree(tree2) + geom_tiplab() + geom_rootedge()
read.nexus parsing standard NEXUS file (re-exported from ape)
plot_bartree = ggtree(bart_tree) + geom_label_repel(aes(label=UFboot, fill=SH_aLRT)) +
theme(legend.position = c(.1, .8)) + scale_fill_viridis_c()
plot_bartree = plot_bartree + geom_point2(aes(subset=(node==68)), shape=23, size=5, fill='red')#zoom in on clade
viewClade(p, MRCA(p, "DQ538396", "GU168959"))Old data
#To load data
load("data/taxa_of_interest.RData")
# Load tree
tree <- read.iqtree("data/dada2_tois/IQTREE/ASV_taxa_of_interest_aln.fasta.treefile") # load IQTREE output
# tree <- read.tree("data/dada2_tois/IQTREE/ASV_taxa_of_interest.newick") # load newick tree
# Add metadata
library(readr)
metadata_tree <- read_csv("data/dada2_tois/taxa_of_interest3.csv")Plot tree
pg = ggtree(tree, branch.length='none', layout='circular')
pg2 = pg %<+% metadata_tree
pg3 = pg2 +
aes(color = Family)
pg3 = pg2 +
geom_tippoint(mapping=aes(color=Family)
pg4 = pg3 +
aes(color = "Family") +
geom_fruit(data=taxa_of_interest,
geom=geom_bar,
mapping = aes(y=OTU, size="Abundance"))
pg4 = pg3 +
geom_fruit(
data=taxa_of_interest,
geom=geom_boxplot,
mapping = aes(
y=OTU,
fill=species
))
pg4 = pg3 +
geom_fruit(
data=taxa_of_interest,
geom=geom_bar,
mapping = aes(
x=OTU,
y=Abundance))pg = ggtree(tree, branch.length='none', layout='circular')
t1 = pg %<+% taxa_of_interest
t2 = t1 +
aes(color = Family)
t3 <- t1 +
geom_star(
mapping=aes(fill=Family, size=Abundance, starshape=SampleCategory),
starstroke=1
) +
scale_size_continuous(
range=c(1, 3),
guide=guide_legend(
keywidth=0.5,
keyheight=0.5,
override.aes=list(starshape=15),
order=2)
) +
scale_starshape_manual(
values=c(15, 13, 1),
guide=guide_legend(
keywidth=1,
keyheight=1,
order=1
)
)
t4 = t3 + geom_hilight(node=306, fill="pink", alpha=.6)
sessionInfo()