Hi Frank,
It seems that you can use the (apparently not used a lot) option from
makeNodeLabel(, method = "md5sum") which creates node labels with the
MD5SUM algorithm using the tip labels descending from each node
(considering the tree as rooted). The result is, for each node, a label
that is
Hi Everyone,
Thank you Jacob, Keith and Emmanuel for your responses. What I am trying to do
is a little different than what the solutions posted here would do. I am not
important a distribution of trees, but rather a single tree with the support
values already included. So imagine something lik
Hi Jake,
What you describe looks very musch like the Lento method implemented in
the function lento() in phangorn. consensusNet(), also in phangorn,
implements something similar: the consensus network.
prop.part(), in ape, is the function behind the two previous ones.
bitsplits() is more eff
To clarify - the idea here is that you are asking which clades appear in
’subordinate’ trees relative to clades that exist in a consensus tree, and then
interrogating the support values of the shared clades which exist in the
’subordinate’ trees? So for example, clade A appears in consensus tree
Frank:
You can import all of the trees into one or more multiPhylo objects,
then use the ape functions prop.part or prop.clades (depending on what
you want to do) to summarize different subsets (e.g., from different
analyses). Here is an example with simulated trees:
x<-rmtree(50,100)
plot(x
Hello,
I have one question
Is there a method to compare the support values (either bootstraps or Pp)
across all shared clades between two or more different trees having identical
taxa? I believe this method would have to first identify the shared clades and
then determine the measure of suppor
