Hola Juan.
If your heights (distances) above the root are a vector h in the order
of the node indices of the tree (in tree$edge) it would be as easy as:
tree$edge.length<-rep(NA,nrow(tree$edge))
for(i in 1:nrow(tree$edge))
tree$edge.length[i]<-h[tree$edge[i,2]]-h[tree$edge[i,1]]
If it
Hi all
This is a simple question:
I have a set of ultrametric trees with information on their
topology but without branch lengths. On a separate file, I have
the distances of each node and leaf to the root. Can someone
instruct me on how to to compute the branch
One way would be to label the root to make it a leaf, and apply NJ.
Neighbor-joining reconstructs the original branch lengths (and topology) given
tree-distances between the leaves.
Cécile
On Nov 30, 2016, at 10:30 AM, Juan Antonio Balbuena
mailto:j.a.balbu...@uv.es>> wrote:
Hi all
This is a
Dear all,
I am analysing phylogenetic signal using Blomberg's K. For several of my traits
(univariate, continuous), the signal strongly deviates both from random and
from the Brownian Motion.
I am unsure how to interpret this. Can you give me some advice what this could
mean?
Thanks a lot!
Dear Florian,
What do you mean, exactly? Do you mean the K statistics is, say, about
0.5, and that the randomizaton test for phylogenetic signal (Blomberg et
al. 2003), which is based on the MSE not K, is significant, indicating that
you do have some degree of signal (more than zero)?
Cheers,
Te
Hi Liam
Thank you very much for your input. I am working with host and parasite trees.
The host tree topology looks like:
TREE HOST =
H4,H5)H3,H6)H2,((H9,(H11,H12)H10)H8,(H14,((H17,H18)H16,H19)H15)H13)H7)H1,(H21,H22)H20)H0;
and the heights above the root are given as
[RANKS represents the
