ML scores

Andrew Roger aroger at is.dal.ca
Tue Oct 3 13:50:56 EST 2000


My perspective below:

Nicole Dubilier wrote:
> Hi!
> I'm a bit worried about bringing down the wrath of the entire ML
> community on me for asking such a stupid question, but here goes:
> what is the absolute worth of a log likelihood value for a final tree? I
> understand that for a given data set I can try to improve ln log by
> comparing runs with different e.g. transition/transversion ratios but
> once I have found the best ln log value for my data set, how do I know
> if this is a good value? For example, with my data sets I have -ln log
> values around 12000 and this seems "bad" to me because in published
> trees I have looked at -ln log values are usually around 2000 to 4000.

likelihood scores of different trees with different datasets (using
different models etc) are not comparable directly like this.  Your
likelihood score for your best tree is the probability of your data
being produced by that tree, given the model of evolution you specified,
with the particular parameters you have estimated.  Other published
likelihoods are based on the probability of their data being produced by
their tree with their model of evolution given their optimized
parameters.  They are just not directly comparable in any useful way I
can think of.  The "goodness" of your tree can be evaluated in a number
of other ways however -- you can bootstrap resample to test how strongly
the data support individual branches or you can perform a variety of
other analyses to detect "phylogenetic signal" in your data. 
Alternatively you may want to compare the likelihood of the best tree to
the likelihood of some other tree (ie other published topologies) using
a variety of tests ranging from parametric bootstrapping to corrected
Kishino-Hasegawa tests (e.g. see an excellent web site: http://www.zoo.cam.ac.uk/zoostaff/goldman/tests/index.html)

Hope this helps?

Andrew Roger

> thanks very much, Nicole
> Dr. Nicole Dubilier
> Dept. of Molecular Ecology
> Max-Planck Institute for Marine Microbiology
> Celsiusstr. 1, D-28359 Bremen, Germany
> Tel.: +49 421 2028-932, Fax: +49 421 2028-580
> ndubilie at mpi-bremen.de
> ---


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