Hello,
I have an alignment which I used to produce ML (with bootstrap) and Bayesian trees. Is there any way I can use a tool that would try to superimpose the bootstrap values of the ML tree on the Bayesian tree? I would just like to have the Bayesian tree with added bootstrap support coming from the PHYML tree.
Thank you,
Adrian
I don't know of any software to do this, but it's possible using the R library ape
Seting up some trees with slightly different topologies and bs values as an example
data(woodmouse)
f <- function(x) nj(dist.dna(x))
tr1 <- tr2 <- f(woodmouse)
tr1$tip.label[c(2,3,9)] <- tr1$tip.label[c(2,9,3)]
tr1$node.labels <- boot.phylo(tr1, woodmouse, f, quiet=TRUE)
tr2$node.labels <- boot.phylo(tr2, woodmouse, f, quiet=TRUE)
Extract the clades from tr1, see if they exist in tr2, and is sowhich node they correspond to
clades <- function(tr) sapply(subtrees(tr), "[[", "tip.label")
A_in_B <- sapply(clades(tr1), function(A) which(sapply(clades(tr2), function(B) setequal(A,B))))
If you are not used to reading R, the apply functions are bit like for-loops, so these is a nested for-loop comparing each clade in tr1 against all clades in tr2 and seeing which match
Use the mapped nodes to create "hybrid" labels:
mapped_nodes <- sapply(A_in_B, function(x)` ` ifelse(length(x)==0, "-", as.character(tr1$node.labels[x])))
tr2$node.labels <- paste(tr2$node.labels, mapped_nodes, sep=" / ")
plot(tr2)
nodelabels(tr2$node.labels)
From their you can save the image or write the tree (with write.tree or write.nexus) and open in your favorite tree drawing program
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version 2.3.6
How does this differ from your earlier question here?
Yes, good question. So there I was asking if it is possible to input into PHYML a Bayesian tree to calculate bootstrap values. That ended up being a bad idea, somehow it either gave me 100 or 0 bootstrap values. So probably not a good approach.
Here I am asking, given 2 different trees, is there any automatic approach that can copy over bootstrap values to another tree so that both values are present on one tree. It is a question more related to graphics. Right now I am doing it manually, seeing if a specific node is present in the ML tree and if yes, I add the BS value and I do it in Adobe Illustrator. Since it is a manual approach, it is prone to errors and time consuming.
while construction of trees with bayesian (BEAST PLATFORM) and maximum likelihood (ON MEGA) I am getting a slight different results with similar models. Is there any scope for publishing both the results and and if not what method I should consider and what changes I should do??