如何在R中以NEWICK格式附加集群（树）节点的引导值

Question

I want to make a tree (cluster) using Interactive Tree of Life web-based tool (iTOL). As an input file (or string) this tool uses Newick format which is a way of representing graph-theoretical trees with edge lengths using parentheses and commas. Beside that, additional information might be supported such as bootstrapped values of cluster's nodes.

For example, here I created dataset for a cluster analysis using clusterGeneration package:

library(clusterGeneration)
set.seed(1)    
tmp1 <- genRandomClust(numClust=3, sepVal=0.3, numNonNoisy=5,
        numNoisy=3, numOutlier=5, numReplicate=2, fileName="chk1")
data <- tmp1$datList[[2]]

Afterwards I performed cluster analysis and assessed support for the cluster's nodes by bootstrap using pvclust package:

set.seed(2)    
y <- pvclust(data=data,method.hclust="average",method.dist="correlation",nboot=100)
plot(y)  

Here is the cluster and bootstrapped values:

In order to make a Newick file , I used ape package:

library(ape)
yy<-as.phylo(y$hclust)
write.tree(yy,digits=2)

write.tree function will print tree in a Newick format:

((x2:0.45,x6:0.45):0.043,((x7:0.26,(x4:0.14,(x1:0.14,x3:0.14):0.0064):0.12):0.22,(x5:0.28,x8:0.28):0.2):0.011);

Those numbers represent branch lengths (cluster's edge lengths). Following instructions from iTOL help page ("Uploading and working with your own trees" section) I manually added bootstrapped values into my Newick file (bolded values below):

((x2:0.45,x6:0.45) 74 :0.043,((x7:0.26,(x4:0.14,(x1:0.14,x3:0.14) 55 :0.0064) 68 :0.12) 100 :0.22,(x5:0.28,x8:0.28) 100 :0.2) 63 :0.011);

It works fine when I upload the string into iTOL. However, I have a huge cluster and doing it by hand seems tedious...

QUESTION: What would be a code that can perform it instead of manual typing?

Bootstrap values can be obtained by:

(round(y$edges,2)*100)[,1:2]

Branch lengths used to form Newick file can be obtained by:

yy$edge.length

I tried to figure out how write.tree function works after debugging it. However, I noticed that it internally calls function .write.tree2 and I couldn't understand how to efficiently change the original code and obtain bootstrapped values in appropriate position in a Newick file.

Any suggestion are welcome.

Answer 1

Here is one solution for you: objects of class phylo have an available slot called node.label that, appropriately, gives you the label of a node. You can use it to store your bootstrap values. There will be written in your Newick File at the appropriate place as you can see in the code of .write.tree2 :

> .write.tree2
function (phy, digits = 10, tree.prefix = "") 
{
    brl <- !is.null(phy$edge.length)
    nodelab <- !is.null(phy$node.label)

...

    if (is.null(phy$root.edge)) {
        cp(")")
        if (nodelab) 
            cp(phy$node.label[1])
        cp(";")
    }
    else {
        cp(")")
        if (nodelab) 
            cp(phy$node.label[1])
        cp(":")
        cp(sprintf(f.d, phy$root.edge))
        cp(";")
    }

...

The real difficulty is to find the proper order of the nodes. I searched and searched but couldn't find a way to find the right order a posteriori .... so that means we will have to get that information during the transformation from an object of class hclust to an object of class phylo .

And luckily, if you look into the function as.phylo.hclust , there is a vector containing the nodes index in their correct order vis-à-vis the previous hclust object:

> as.phylo.hclust
function (x, ...) 
{
    N <- dim(x$merge)[1]
    edge <- matrix(0L, 2 * N, 2)
    edge.length <- numeric(2 * N)
    node <- integer(N)              #<-This one
...

Which means we can make our own as.phylo.hclust with a nodenames parameter as long as it is in the same order as the nodes in the hclust object (which is the case in your example since pvclust keeps a coherent order internally, ie the order of the nodes in the hclust is the same as in the table in which you picked the bootstraps):

# NB: in the following function definition I only modified the commented lines
as.phylo.hclust.with.nodenames <- function (x, nodenames, ...) #We add a nodenames argument
{
    N <- dim(x$merge)[1]
    edge <- matrix(0L, 2 * N, 2)
    edge.length <- numeric(2 * N)
    node <- integer(N)
    node[N] <- N + 2L
    cur.nod <- N + 3L
    j <- 1L
    for (i in N:1) {
        edge[j:(j + 1), 1] <- node[i]
        for (l in 1:2) {
            k <- j + l - 1L
            y <- x$merge[i, l]
            if (y > 0) {
                edge[k, 2] <- node[y] <- cur.nod
                cur.nod <- cur.nod + 1L
                edge.length[k] <- x$height[i] - x$height[y]
            }
            else {
                edge[k, 2] <- -y
                edge.length[k] <- x$height[i]
            }
        }
        j <- j + 2L
    }
    if (is.null(x$labels)) 
        x$labels <- as.character(1:(N + 1))
    node.lab <- nodenames[order(node)] #Here we define our node labels
    obj <- list(edge = edge, edge.length = edge.length/2, tip.label = x$labels, 
        Nnode = N, node.label = node.lab) #And you put them in the final object
    class(obj) <- "phylo"
    reorder(obj)
}

In the end, here is how you would use this new function in your case study:

bootstraps <- (round(y$edges,2)*100)[,1:2]
yy<-as.phylo.hclust.with.nodenames(y$hclust, nodenames=bootstraps[,2])
write.tree(yy,tree.names=TRUE,digits=2)
[1] "((x5:0.27,x8:0.27)100:0.24,((x7:0.25,(x4:0.14,(x1:0.13,x3:0.13)61:0.014)99:0.11)100:0.23,(x2:0.46,x6:0.46)56:0.022)61:0.027)100;"
#See the bootstraps    ^^^ here for instance
plot(yy,show.node.label=TRUE) #To show that the order is correct
plot(y) #To compare with (here I used the yellow value)