Wednesday, March 1, 2017

Error bars on divergence times on a phylogeny plotted in R

Today a colleague at Universidad de los Andes (where I'm currently on sabbatical, BTW) asked me how to add error bars for divergence times to the nodes of a plotted phylogeny in R.

Well, as is the case with many things, I bet that there is a ton of different ways to do this; however, the following is one very simple technique.

In the following, I have a "phylo" object tree; and I also have a matrix (CI) containing the times before the present for the lower & upper confidence limits on each estimated divergence time corresponding to the nodes of my tree. Note that these CIs have been simulated to be intentionally assymetric - as such confidence intervals often are:

library(phytools)
## here are the data:
tree
## 
## Phylogenetic tree with 26 tips and 25 internal nodes.
## 
## Tip labels:
##  Z, Y, X, W, V, U, ...
## 
## Rooted; includes branch lengths.
CI
##    lower (MYBP) upper (MYBP)
## 27    111.80101    92.599420
## 28     90.13474    64.370663
## 29     48.45811    28.394226
## 30     42.77937    22.359999
## 31     83.01736    61.962733
## 32     41.48123    18.614973
## 33     26.10956     0.000000
## 34     95.60433    75.950823
## 35     88.41807    68.551308
## 36     93.32274    69.118385
## 37     84.96369    66.249093
## 38     29.45826     6.303606
## 39     72.61971    54.372320
## 40     73.15644    45.563312
## 41     65.70458    37.262456
## 42     35.86271    18.184414
## 43     34.17755    12.586219
## 44     47.11305    26.530968
## 45     50.74606    24.070106
## 46     41.64973    23.878326
## 47     58.47533    35.912961
## 48     13.19029     0.000000
## 49     35.42824    11.007959
## 50     27.73721     6.913533
## 51     15.31440     0.000000

Now let's plot it:

plotTree(tree,xlim=c(110,-5),direction="leftwards",
    mar=c(4.1,1.1,1.1,1.1),ftype="i")
abline(v=seq(0,120,by=10),lty="dashed",
    col=make.transparent("grey",0.5))
axis(1,at=seq(0,120,by=20))
obj<-get("last_plot.phylo",envir=.PlotPhyloEnv)
for(i in 1:tree$Nnode+Ntip(tree))
    lines(x=c(CI[i-Ntip(tree),1],CI[i-Ntip(tree),2]),
        y=rep(obj$yy[i],2),lwd=11,lend=0,
        col=make.transparent("blue",0.4))
points(obj$xx[1:tree$Nnode+Ntip(tree)],
    obj$yy[1:tree$Nnode+Ntip(tree)],pch=19,col="blue",
    cex=1.8)

plot of chunk unnamed-chunk-2

(I added a few embellishments, but it should be straightforward to pick these out.)

I like it.

As with most such plots, it will tend to look better if expored as a PDF.

Note that because my CIs are in time for the present, I decide to plot my tree "leftwards", but then flip my x axis to run from higher to lesser values using the argument value xlim=c(110,-5).

Note also that in the example above I have assumed that the order of the rows of CI matches the order of the node indices in the tree.

These were simulated data, obviously. The code used to simulate these values was as follows:

tree<-pbtree(n=26,tip.label=LETTERS[26:1],scale=100)
h<-sapply(1:tree$Nnode+Ntip(tree),nodeheight,tree=tree)
CI<-cbind(h-runif(n=length(h),min=10,max=20),h+runif(n=length(h),
    min=5,max=10))
CI[CI>max(nodeHeights(tree))]<-max(nodeHeights(tree))
CI<-max(nodeHeights(tree))-CI
rownames(CI)<-1:tree$Nnode+Ntip(tree)
colnames(CI)<-paste(c("lower","upper"),"(MYBP)")

2 comments:

  1. Dear Liam,

    How can I get the matrix of CI from a posterior distribution of trees (empirical data)?
    Thanks,
    Aparna

    ReplyDelete

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