tree.merger tool
tree.merger basics
The function tree.merger is meant to merge phylogenetic
information derived from different phylogenies into a single supertree.
Given a backbone (backbone) and a source
(source.tree) trees, tree.merger drops clades
from the latter to attach them on the former according to the
information provided in the dataset object data. Individual
tips to add can be indicated in data as well. Once the
supertree is assembled, tips and nodes ages are calibrated based on
user-specified values.
Input tree and data
The backbone phylogeny serves as the reference to locate
where single tips or entire clades extracted from the
source.tree have to be attached. The backbone
is assumed to be correctly calibrated so that nodes and tips ages
(including the age of the tree root) are left unchanged, unless the user
specifies otherwise. The source.tree is the phylogeny where
the clades to add are extracted from. For each clade attached to the
backbone, the time distances between the most recent common
ancestor of the clade and its descendant nodes are kept fixed, unless
the ages for any of these nodes are indicated by the user. All the new
tips added to the backbone, irrespective of whether they
are attached as a clade or as individual tips, are placed at the maximum
distance from the tree root, unless calibration ages are supplied by the
user. The data object is a dataframe including information
about “what” is attached, where and how. data must be made
of three columns:
bind: the tips or clades to be
attached;
reference: the tips or clades where
bind will be attached;
poly: a logical indicating whether the
bind and reference pair should form a
polytomy.
If different column names are supplied, tree.merger
assumes they are ordered as described and eventually fails if this
requirement is not met. Similarly, with duplicated bind
supplied the function stops and throws an error message. A clade, either
to be bound or to be the reference, must be indicated by collating the
names of the two phylogenetically furthest tips belonging to it,
separated by the “-” symbol. Alternatively, if
backbone$node.label/source.tree$node.label is
not NULL, a
bind/reference clade can be indicated
as “Clade NAMEOFTHECLADE” when appropriate. Similarly, an entire genus
on both the backbone and the source.tree can
be indicated as “Genus NAMEOFTHEGENUS”. Regardless the way it was
attached, any ‘bound’ tip can be used as a reference for another tip
(individually or as an element for clade identification, i.e. in the
“species1-species2” form). The order with which clades and tips to
attach are supplied does not matter.
Tips and nodes are calibrated within tree.merger by
means of the function scaleTree.
To this aim, named vectors of tips and nodes ages, meant as time
distance from the youngest tips within the phylogeny, must be supplied.
As for the data object, the nodes to be calibrated should
be identified by collating the names of the two phylogenetically
furthest tips it subtends to, separated by a “-”.
Attaching individual tips to the backbone tree
If only individual tips are attached the source.tree can
be left unspecified. Tips set to be attached to the same
reference with poly=FALSE are
considered to represent a polytomy. Tips set as bind
which are already on the backbone tree are removed from the latter and
placed according to the reference. In the example
below, tips “genusE_1a” and “genusE_1b” are set to be attached to the
same reference “genusE_1”, creating a polytomy. The species “genusC_4”
and “genusC_5”, are both set to be bound to the entire “Genus genusC”
(including “genusC_1”, “genusC_2”, and “genusC_3”), but only the latter
is explicitly indicated to create a polytomous clade (“poly=TRUE”). Once
“genusC_5” is attached, the most recent common ancestor (MRCA) of the
entire genusC changes with respect to the MRCA on the
backbone, hence the reference for “genusC_6” is identified
by selecting the two phylogenetically furthest tips within the ‘new’
genusC, that is “genusC_1-genusC_5”. “genusB_3” belonging to the
backbone is indicated to be moved, and “genusH_1” is added to the tree
root thus changing the total height of the tree.
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dato
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bind
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reference
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poly
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genusE_1a
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genusE_1
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FALSE
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genusC_3a
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genusC_3
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FALSE
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genusB_1a
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genusB_1
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FALSE
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genusC_4
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Genus genusC
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TRUE
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genusF_1
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Clade DC
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FALSE
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genusG_1
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genusF_1-genusB_2
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TRUE
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genusH_1
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genusE_1a-genusC_3
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FALSE
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genusC_5
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Genus genusC
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FALSE
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genusC_6
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genusC_5-genusC_1
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FALSE
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genusB_3
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genusB_2-genusB_1
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FALSE
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genusE_1b
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genusE_1
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FALSE
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tree.merger(backbone=tree.back,data=dato,plot=FALSE)
#> Warning in tree.merger(backbone = tree.back, data = dato, plot = FALSE): genusB_3 removed from the backbone tree
#> Warning in doTryCatch(return(expr), name, parentenv, handler): Root age not indicated: the tree root arbitrarily set at
#> 3.32
As no tip.ages are supplied to tree.merger,
all the new tips are placed at the maximum distance from the tree root.
Since no age for the root of the merged tree is indicated, the function
places it arbitrarly and produces a warning to inform the user about its
position with respect to the youngest tip on the phylogeny.
To calibrate the the ages of either tips or nodes within the merged
tree, the arguments tip.ages and node.ages
must be indicated.
ages.tip
#> genusH_1 genusE_1a genusE_1 genusE_1b genusF_1 genusC_5 genusC_3a genusG_1
#> 1.0 2.0 1.7 1.5 0.8 1.5 0.3 1.2
#> genusB_1a
#> 0.2
ages.node
#> genusB_1-genusF_1 genusE_1a-genusE_1b genusH_1-genusB_1
#> 2.2 2.9 3.5
tree.merger(backbone=tree.back,data=dato,tip.ages=ages.tip,node.ages = ages.node,plot=FALSE)
#> Warning in tree.merger(backbone = tree.back, data = dato, tip.ages = ages.tip, : genusB_3 removed from the backbone tree
Attaching clades to the backbone tree
When a clade is attached, the node subtending to it on
source.tree is identified as the MRCA of the tip pair, the
“Genus”, or the “Clade” indicated in bind. In the
example below, “Genus genusA” from the source is added as sister to
“genusA_1” within the backbone. Then, “genusL_1” is bound to the newly
created clade made of all the tips belonging to the “genusA”, located by
the two phylogenetically furthest tips within it.
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dato.clade
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bind
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reference
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poly
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Genus genusA
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genusA_1
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FALSE
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genusG_1-genusF_2
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Clade DC
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FALSE
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Clade HI
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Genus genusB
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FALSE
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genusL_1
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genusA_1-genusA_4
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FALSE
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tree.merger(backbone=tree.back,data=dato.clade,source.tree=tree.source,plot=FALSE)
Guided examples
### load the RRphylo example dataset including Cetaceans tree
data("DataCetaceans")
DataCetaceans$treecet->treecet # phylogenetic tree
treecet$node.label[(131-Ntip(treecet))]<-"Crown Mysticeti" # assigning node labels
### Select two clades and some species to be removed
tips(treecet,131)->crown.Mysticetes
tips(treecet,193)->Delphininae
c("Aetiocetus_weltoni","Saghacetus_osiris",
"Zygorhiza_kochii","Ambulocetus_natans",
"Kentriodon_pernix","Kentriodon_schneideri","Kentriodon_obscurus",
"Eurhinodelphis_cristatus","Eurhinodelphis_bossi")->extinct
plot(treecet,show.tip.label = FALSE,no.margin=TRUE)
nodelabels(frame="n",col="blue",font=2,node=c(131,193),text=c("crown\nMysticetes","Delphininae"))
tiplabels(frame="circle",bg="red",cex=.3,text=rep("",length(c(crown.Mysticetes,Delphininae,extinct))),
tip=which(treecet$tip.label%in%c(crown.Mysticetes,Delphininae,extinct)))
### Create the backbone and source trees
drop.tip(treecet,c(crown.Mysticetes[-which(tips(treecet,131)%in%
c("Caperea_marginata","Eubalaena_australis"))],
Delphininae[-which(tips(treecet,193)=="Tursiops_aduncus")],extinct))->backtree
keep.tip(treecet,c(crown.Mysticetes,Delphininae,extinct))->sourcetree
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dato
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bind
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reference
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poly
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Clade Crown Mysticeti
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Fucaia_buelli-Aetiocetus_weltoni
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FALSE
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Aetiocetus_weltoni
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Aetiocetus_cotylalveus
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FALSE
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Saghacetus_osiris
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Fucaia_buelli-Tursiops_truncatus
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FALSE
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Zygorhiza_kochii
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Saghacetus_osiris-Fucaia_buelli
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FALSE
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Ambulocetus_natans
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Dalanistes_ahmedi-Fucaia_buelli
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FALSE
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Genus Kentriodon
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Phocoena_phocoena-Delphinus_delphis
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FALSE
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Sousa_chinensis-Delphinus_delphis
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Sotalia_fluviatilis
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FALSE
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Kogia_sima
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Kogia_breviceps
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FALSE
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Eurhinodelphis_cristatus
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Eurhinodelphis_longirostris
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FALSE
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Grampus_griseus
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Globicephala_melas-Pseudorca_crassidens
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FALSE
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Eurhinodelphis_bossi
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Eurhinodelphis_longirostris
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FALSE
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### Merge the backbone and the source trees according to dato without calibrating tip and node ages
tree.merger(backbone = backtree,data=dato,source.tree = sourcetree,plot=FALSE)
#> Warning in tree.merger(backbone = backtree, data = dato, source.tree = sourcetree, : Kogia_sima, Grampus_griseus removed from the backbone tree
#> Warning in tree.merger(backbone = backtree, data = dato, source.tree = sourcetree, : Eubalaena_australis, Caperea_marginata, Tursiops_aduncus already on the source tree: removed from the backbone tree
#> Warning in doTryCatch(return(expr), name, parentenv, handler): Root age not indicated: the tree root arbitrarily set at
#> 45.06
### Set tips and nodes calibration ages
c(Aetiocetus_weltoni=28.0,
Saghacetus_osiris=33.9,
Zygorhiza_kochii=34.0,
Ambulocetus_natans=40.4,
Kentriodon_pernix=15.9,
Kentriodon_schneideri=11.61,
Kentriodon_obscurus=13.65,
Eurhinodelphis_bossi=13.65,
Eurhinodelphis_cristatus=5.33)->tipages
c("Ambulocetus_natans-Fucaia_buelli"=52.6,
"Balaena_mysticetus-Caperea_marginata"=21.5)->nodeages
### Merge the backbone and the source trees and calibrate tips and nodes ages
tree.merger(backbone = backtree,data=dato,source.tree = sourcetree,
tip.ages=tipages,node.ages=nodeages,plot=FALSE)
#> Warning in tree.merger(backbone = backtree, data = dato, source.tree = sourcetree, : Kogia_sima, Grampus_griseus removed from the backbone tree
#> Warning in tree.merger(backbone = backtree, data = dato, source.tree = sourcetree, : Eubalaena_australis, Caperea_marginata, Tursiops_aduncus already on the source tree: removed from the backbone tree
scaleTree tool
The function scaleTree is a useful tool to deal with
phylogenetic age calibration written around Gene Hunt’s scalePhylo
function (https://naturalhistory.si.edu/staff/gene-hunt). It
rescales branches and leaves of the tree according to species and/or
nodes calibration ages (meant as distance from the youngest tip within
the tree).
If only species ages are supplied (argument tip.ages),
the function changes leaves length, leaving node ages and internal
branch lengths unaltered. When node ages are supplied (argument
node.ages), the function shifts nodes position along their
own branches while keeping other nodes and species positions
unchanged.
#> t9 t73 t11 t43 t78 t46 t52 t26
#> 1.250 1.205 0.000 2.430 3.150 1.050 0.000 1.550
scaleTree(tree,tip.ages=sp.ages)->treeS1
#>
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#> 98 152 123 85 118 127 164 143
#> 10.7 0.7 1.2 12.6 5.1 5.8 18.8 12.8
scaleTree(tree,node.ages=nod.ages)->treeS2
#>
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treeS2->treeS1
It may happen that species and/or node ages to be calibrated are
older than the age of their ancestors. In such cases, after moving the
species (node) to its target age, the function reassembles the phylogeny
above it by assigning the same branch length (set through the argument
min.branch) to the all the branches along the species
(node) path, so that the tree is well-conformed and ancestor-descendants
relationships remain unchanged. In this way changes to the original tree
topology only pertain to the path along the “calibrated” species.
c(sp.ages,nod.ages)
#> t1 96
#> 20.5 15.6
# scaleTree(tree,tip.ages = sp.ages,node.ages = nod.ages,min.branch = 1)->treeS
#>
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Guided examples
# load the RRphylo example dataset including Felids tree
data("DataFelids")
DataFelids$treefel->tree
# get species and nodes ages
# (meant as distance from the youngest species, that is the Recent in this case)
max(nodeHeights(tree))->H
H-dist.nodes(tree)[(Ntip(tree)+1),(Ntip(tree)+1):(Ntip(tree)+Nnode(tree))]->age.nodes
H-diag(vcv(tree))->age.tips
# apply Pagel's lambda transformation to change node ages only
rescaleRR(tree,lambda=0.8)->tree1
# apply scaleTree to the transformed phylogeny, by setting
# the original ages at nodes as node.ages
scaleTree(tree1,node.ages=age.nodes)->treeS1
#>
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# change leaf length of 10 sampled species
tree->tree2
set.seed(14)
sample(tree2$tip.label,10)->sam.sp
age.tips[sam.sp]->age.sam
age.sam[which(age.sam>0.1)]<-age.sam[which(age.sam>0.1)]-1.5
age.sam[which(age.sam<0.1)]<-age.sam[which(age.sam<0.1)]+0.2
tree2$edge.length[match(match(sam.sp,tree$tip.label),tree$edge[,2])]<-age.sam
# apply scaleTree to the transformed phylogeny, by setting
# the original ages at sampled tips as tip.ages
scaleTree(tree2,tip.ages=age.tips[sam.sp])->treeS2
#>
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# apply Pagel's kappa transformation to change both species and node ages,
# including the age at the tree root
rescaleRR(tree,kappa=0.5)->tree3
# apply scaleTree to the transformed phylogeny, by setting
# the original ages at nodes as node.ages
scaleTree(tree1,tip.ages = age.tips,node.ages=age.nodes)->treeS3
#>
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cutPhylo tool
The function cutPhylo is meant to cut the phylogentic
tree to remove all the tips and nodes younger than a reference
(user-specified) age, which can also coincide with a specific node. When
an entire clade is cut, the user can choose (by the argument
keep.lineage) to keep its branch length as a tip of the new
tree, or remove it completely.
cutPhylo(tree,age=5,keep.lineage = TRUE)
cutPhylo(tree,age=5,keep.lineage = FALSE)
cutPhylo(tree,node=129,keep.lineage = TRUE)
cutPhylo(tree,node=129,keep.lineage = FALSE)
fix.poly tool
The function fix.poly randomly resolves polytomies
either at specified nodes or througout the tree (Castiglione et
al. 2020). This latter feature works like ape’s multi2di.
However, contrary to the latter, polytomies are resolved to non-zero
length branches, to provide credible partition of the evolutionary time
among the nodes descending from the dichotomized node. This could be
useful to gain realistic evolutionary rate estimates at applying
RRphylo. Under the type = collapse
specification the user is expected to indicate which node/s
must be transformed into a multichotomus clade.
### load the RRphylo example dataset including Cetaceans tree
data("DataCetaceans")
DataCetaceans$treecet->treecet
### Resolve all the polytomies within Cetaceans phylogeny
fix.poly(treecet,type="resolve")->treecet.fixed
#>
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## Set branch colors
unlist(sapply(names(which(table(treecet$edge[,1])>2)),function(x)
c(x,getDescendants(treecet,as.numeric(x)))))->tocolo
unlist(sapply(names(which(table(treecet$edge[,1])>2)),function(x)
c(getMRCA(treecet.fixed,tips(treecet,x)),
getDescendants(treecet.fixed,as.numeric(getMRCA(treecet.fixed,tips(treecet,x)))))))->tocolo2
colo<-rep("gray60",nrow(treecet$edge))
names(colo)<-treecet$edge[,2]
colo2<-rep("gray60",nrow(treecet.fixed$edge))
names(colo2)<-treecet.fixed$edge[,2]
colo[match(tocolo,names(colo))]<-"red"
colo2[match(tocolo2,names(colo2))]<-"red"
par(mfrow=c(1,2))
plot(treecet,no.margin=TRUE,show.tip.label=FALSE,edge.color = colo,edge.width=1.3)
plot(treecet.fixed,no.margin=TRUE,show.tip.label=FALSE,edge.color = colo2,edge.width=1.3)
### Resolve the polytomies pertaining the genus Kentriodon
fix.poly(treecet,type="resolve",node=221)->treecet.fixed2
#>
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## Set branch colors
c(221,getDescendants(treecet,as.numeric(221)))->tocolo
c(getMRCA(treecet.fixed2,tips(treecet,221)),
getDescendants(treecet.fixed2,as.numeric(getMRCA(treecet.fixed2,tips(treecet,221)))))->tocolo2
colo<-rep("gray60",nrow(treecet$edge))
names(colo)<-treecet$edge[,2]
colo2<-rep("gray60",nrow(treecet.fixed2$edge))
names(colo2)<-treecet.fixed2$edge[,2]
colo[match(tocolo,names(colo))]<-"red"
colo2[match(tocolo2,names(colo2))]<-"red"
par(mfrow=c(1,2))
plot(treecet,no.margin=TRUE,show.tip.label=FALSE,edge.color = colo,edge.width=1.3)
plot(treecet.fixed2,no.margin=TRUE,show.tip.label=FALSE,edge.color = colo2,edge.width=1.3)
### Collapse Delphinidae into a polytomous clade
fix.poly(treecet,type="collapse",node=179)->treecet.collapsed
#>
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# Set branch colors
c(179,getDescendants(treecet,as.numeric(179)))->tocolo
c(getMRCA(treecet.collapsed,tips(treecet,179)),
getDescendants(treecet.collapsed,as.numeric(getMRCA(treecet.collapsed,tips(treecet,179)))))->tocolo2
colo<-rep("gray60",nrow(treecet$edge))
names(colo)<-treecet$edge[,2]
colo2<-rep("gray60",nrow(treecet.collapsed$edge))
names(colo2)<-treecet.collapsed$edge[,2]
colo[match(tocolo,names(colo))]<-"red"
colo2[match(tocolo2,names(colo2))]<-"red"
par(mfrow=c(1,2))
plot(treecet,no.margin=TRUE,show.tip.label=FALSE,edge.color = colo,edge.width=1.3)
plot(treecet.collapsed,no.margin=TRUE,show.tip.label=FALSE,edge.color = colo2,edge.width=1.3)
References
Castiglione, S., Serio, C., Piccolo, M., Mondanaro, A., Melchionna,
M., Di Febbraro, M., Sansalone, G., Wroe, S.,& Raia, P. (2020). The
influence of domestication, insularity and sociality on the tempo and
mode of brain size evolution in mammals. Biological Journal of the
Linnean Society, 132: 221-231.