phylogenetic tree

Guy Hoelzer hoelzer at unr.edu
Wed Nov 8 12:47:07 EST 2000


In article <8uc0ke$jme$1 at mercury.hgmp.mrc.ac.uk>, Anders Gorm Pedersen
<gorm at cbs.dtu.dk> wrote:

> Mich Ard wrote:
> 
> > I'm currently making a phylogenetic tree
> > based on the protein sequences, using the
> > programs of clustalW and phylip, and found
> > the output is "unstable", it's always changing
> > depending on the inputing order of these
> > sequences; 
> 
> you should be aware that the apparent instability may in fact merely be
> different graphical representations of the exact same tree. Remember that even
> if you rotate a branch then it's 
> still the same tree topology. 
> 
> I just experimented with using the differently ordered versions of one
distance
> matrix as input to neighbor (of the phylip package). This results in
trees that
> are topologically identical, but that are rendered differently by
drawtree (also
> phylip package). This is mainly due to a different orientation of the entire
> tree, and also due to some branches being rotated.

Anders makes a good point, but it is still possible (even probable) that
the topologies you discovered are truly different.  Every heuristic
algorithm is inherently entry-order sensitive.  If you were using the
maximum parsimony algorithm, and did an exhaustive search, then you would
always get the same tree no matter what your entry-order was.  If you used
a heuristic search algorithm, the order would matter.  Neighbor joining is
a heuristic algorithm, and is therefore always prone to entry-order
sensitivity.  NJ results should always be checked by trying a variety of
entry orders.  The same is true of maximum likelihood analyses.  It is
almost always too computationally intensive to do exhaustive searches in
the context of ML analyses, so heuristic searches are almost always used. 
This makes the result of ML analyses prone to entry-order sensitivity.  As
your question indicates, you are correct to be concerned about this.  It
certainly suggests uncertainty about which tree actually optimizes the
tree picking criterion you chose when you decided which tree estimation
algorithm to use.

-- 
Guy Hoelzer
Department of Biology
University of Nevada Reno
Reno, NV  89557








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