Hi Nick & al.

Actually, Nick's method should work too.

If the distance matrix is a patristic distance matrix based on the ML tree, then neighbor-joining ought to recover the exact topology and branch lengths of your ML tree. This is on p. 166 of Felsenstein (2004): "Neighbor-joining, like the least squares methods, is guaranteed to recover the true tree if the distance matrix happens to be an exact reflection of a tree."

Maria, are you sure that your distance matrix came from the branch lengths in your ML tree; and, furthermore, are you sure that NJ did not give you the correct tree? Keep in mind that NJ will return an unrooted tree and that the branches might be rotated around any node (thus, your plotted tree may seem quite different from the ML tree).

- Liam

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On 5/12/2011 5:28 PM, mgavil2 wrote:
Hi Nick,

I tried nj, but the topology I obtain from that is totally different.
I am not sure if it has anything to do with the fact that the tree was
created based on maximum likelihood?
Thanks though!

Meche



On Thu, May 12, 2011 at 4:23 PM, Nick Matzke<mat...@berkeley.edu>  wrote:
The APE command NJ (neighbor-joining) will form a tree from a distance
matrix, so that's one option.  You could do it and then see if you get the
same topology from NJ as from your topology tree.  The branch lengths will
reflect whatever distances were calculated from the data (which might be one
of several corrected or uncorrected distances, depending on the input
sequence/character data).

Cheers,
Nick

On 5/12/11 2:18 PM, mgavil2 wrote:

All,
I have a tree topology (tree_name.tre), and a distance matrix, based
on that tree topology. However I cant not seem to find the nexus file
from which the matrix was generated.  Is there a way to use that
distance matrix to incorporate branch lengths into my topology?
I have looked into all the threads of questions posted in the list,
but still can not find an answer. my final objective is just to
generate a tree with branch lengths proportional to the distances on
the matrix (reviewers requirement for a publication).

Any suggestions would be greatly appreciated!

Thanks.

Maria Mercedes


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