Plotting a legend outside the plot area using add.color.bar (& in general)

Recently I received the following question:

“I am using the add.color.bar function to add a colorbar to an existing plot.
Do you know if it is possible to move the added colorbar to the outside of the plot domain? Do you think I would need to modify code in the actual function?”

Evidently, this can be done using par(xpd=TRUE). For instance:

library(phytools)
tree

## 
## Phylogenetic tree with 26 tips and 25 internal nodes.
## 
## Tip labels:
##  A, B, C, D, E, F, ...
## 
## Rooted; includes branch lengths.

x

##           A           B           C           D           E           F 
##  3.09148522  1.54096027  2.91508379  2.00469068  1.15813551  0.29543463 
##           G           H           I           J           K           L 
##  0.27951056  0.60805259 -2.52405841 -3.50891295 -3.34674083 -0.97428407 
##           M           N           O           P           Q           R 
## -1.25336677 -1.40812351 -0.51371266 -2.92582374 -2.24608676 -0.53203275 
##           S           T           U           V           W           X 
## -0.59487179  0.30811419 -0.08364322  0.16895725  0.70189973 -3.64724619 
##           Y           Z 
## -3.65517946 -4.30271550

obj<-contMap(tree,x,plot=FALSE)
plot(obj,legend=FALSE,mar=c(5.1,2.1,2.1,2.1))
par(xpd=TRUE)
add.color.bar(leg=3,cols=obj$cols,title="trait value",lims=obj$lims,
    digits=3,prompt=FALSE,x=0,y=-3)

We can easily see that this is outside of our plotting domain by adding axis labels to the plot as follows:

plot(obj,legend=FALSE,mar=c(6.1,2.1,2.1,2.1))
par(xpd=TRUE)
add.color.bar(leg=3,cols=obj$cols,title="trait value",lims=obj$lims,
    digits=3,prompt=FALSE,x=0,y=-4)
axis(1)

You get the general idea.

Evolution 2017 meeting slides

At the recent 'Evolution' meeting in Portland Oregon (the joint meeting of ASN, SSB, and SSE), I presented a talk entitled:

Some additional new plotting methods for phylogenies & comparative data.

The intention was to basically give a rapid-fire survey of the majority (but not all) of the phylogenetic plotting methods available in phytools, along with some comment about the purpose of different methods.

This I did; however, unfortunately, some colors were burnt out on the slide projector, so for those wondering what the plots were supposed to look like, and for those unable to attend at all, I have now posted the PDF online. The direct link is here, but the full presentation is also embedded below. Enjoy!

Fix to read.newick for cases in which some but not all nodes are labeled

It was recently reported that there can be a mismatch between the number of nodes & the length of the node label vector in an object class "phylo" produced by the function read.newick in phytools. This appears to be a bug that is produced when some nodes have labels, but the node with the largest-valued index does not have a label. I just pushed a fix to GitHub & it appears to work. Here's a demo using the case submitted on R-sig-phylo:

library(phytools)

## Loading required package: ape

## Loading required package: maps

packageVersion("phytools")

## [1] '0.6.17'

tree<-read.newick(text='((((((a))A),(((b),(b1)))B)))C;')
tree$edge.length<-rep(1,nrow(tree$edge))
plotTree.singletons(tree)
nodelabels(tree$node.label)

That's it.

Generating a set of random resolutions of all the nodes in a tree with multifurcations

Today, an R-sig-phylo list member asked:

“I am using the ape package to randomly resolve polytomies using 'multi2di' and wondering if there is a way to use this function to get a single output tree file that contains multiple different randomly resolved trees using some number of resamplings?”

This can be done using the phytools function resolveNode, which returns all possible resolutions of a given node. We just iterate over all the nodes of the tree pick a random resolution each time.

Here's a function to do that:

resolveRandom<-function(tree){
    while(!is.binary(tree)){
        nodes<-1:tree$Nnode+Ntip(tree)
        Nchildren<-function(node,tree) length(Children(tree,node))
        nchilds<-sapply(nodes,Nchildren,tree=tree)
        node<-nodes[which(nchilds>2)[1]]
        tree<-sample(resolveNode(tree,node),1)[[1]]
    }
    tree
}

Here's a quick demo:

library(phytools)
library(phangorn)
tree<-read.tree(text="(((A1,A2),(B1,B2,B3),C,D),E,F);")
plotTree(tree,type="cladogram",nodes="centered")

## now some random resolutions
plotTree(resolveRandom(tree),type="cladogram",nodes="centered")

plotTree(resolveRandom(tree),type="cladogram",nodes="centered")

plotTree(resolveRandom(tree),type="cladogram",nodes="centered")

plotTree(resolveRandom(tree),type="cladogram",nodes="centered")

We can also generate a set of resolutions using replicate:

trees<-replicate(36,resolveRandom(tree),simplify=FALSE)
class(trees)<-"multiPhylo"
par(mfrow=c(6,6))
plotTree(trees,type="cladogram",nodes="centered")

That's it.