Phylogenetic tree manipulation

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.

dato
bind reference poly
genusE_1a genusE_1 FALSE
genusC_3a genusC_3 FALSE
genusB_1a genusB_1 FALSE
genusC_4 Genus genusC TRUE
genusF_1 Clade DC FALSE
genusG_1 genusF_1-genusB_2 TRUE
genusH_1 genusE_1a-genusC_3 FALSE
genusC_5 Genus genusC FALSE
genusC_6 genusC_5-genusC_1 FALSE
genusB_3 genusB_2-genusB_1 FALSE
genusE_1b genusE_1 FALSE
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.

dato.clade
bind reference poly
Genus genusA genusA_1 FALSE
genusG_1-genusF_2 Clade DC FALSE
Clade HI Genus genusB FALSE
genusL_1 genusA_1-genusA_4 FALSE
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
dato
bind reference poly
Clade Crown Mysticeti Fucaia_buelli-Aetiocetus_weltoni FALSE
Aetiocetus_weltoni Aetiocetus_cotylalveus FALSE
Saghacetus_osiris Fucaia_buelli-Tursiops_truncatus FALSE
Zygorhiza_kochii Saghacetus_osiris-Fucaia_buelli FALSE
Ambulocetus_natans Dalanistes_ahmedi-Fucaia_buelli FALSE
Genus Kentriodon Phocoena_phocoena-Delphinus_delphis FALSE
Sousa_chinensis-Delphinus_delphis Sotalia_fluviatilis FALSE
Kogia_sima Kogia_breviceps FALSE
Eurhinodelphis_cristatus Eurhinodelphis_longirostris FALSE
Grampus_griseus Globicephala_melas-Pseudorca_crassidens FALSE
Eurhinodelphis_bossi Eurhinodelphis_longirostris FALSE
### 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.