Text 459, 79 rader
Skriven 2004-10-21 13:18:00 av Michael Ragland (1:278/230)
Ärende: Re: Can You Please Help M
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in article cl65sm$atf$1@darwin.ediacara.org, Michael Ragland at
ragland66@webtv.net wrote on 10/20/04 10:05 AM: 

You write, "Use of computer simulations in this regard should be treated
cautiously. It is very difficult to avoid assuming some (if not all) of
the same aspects of the evolutionary process in the generation of the
data and in the likelihood model assumed in the analysis. This results
in a circularity that can easily mislead inferences in favor of the
maximum likelihood method. There is no question that ML can be misled by
LBA, like any other topology estimation method constrained to yield
pictures of bifurcating trees if the assumed evolutionary model is
incorrect, which is ALWAYS true in practice." Am I to take it from this
last statement you consider using computer simulation to generate
sequence data for protein families, and studying the influence of among
site rate variation on the performance of phylogenetic reconstruction as
useless? 

Guy Hoelzer:
No. I am actually a big fan of modeling evolution with computer
simulations. However, I think the the way that it has been used to
compare the efficacy of alternative phylogenetic estimation methods has
often biased the results in favor of methods that assume relatively
detailed evolutionary models. When you simulate evolution to generate
the test data sets, you must assume a particular model of evolution. The
analytical methods also assume various evolutionary models. It shouldn't
be surprising that "the winner" is generally the method which assumes
the same (or most similar) evolutionary model as the one under which the
data were generated. Because methods like maximum parsimony or neighbor
joining assume generic and vague evolutionary models, the models assumed
for the generation of data usually don't resemble those models very
well. On the other hand, the models assumed by maximum likelihood or
Bayesian methods are designed to reflect the particular way we think
evolution works in some detail, so those are very much like the ones
assumed in the generation of the data. I don't see this approach as a
fair playing field, so I take the resulting inferences with a big grain
or two of salt. I far prefer to use real biological data for such
comparisons. Of course, the problem there is that we usually don't know
the Truth about the underlying phylogenetic tree, but there are
exceptions. A classic example is the experimental evolution work by
Hillis and colleagues on the virus T7. These authors created an
evolutionary tree in the lab with this fast evolving virus, so we can
check the data analysis against the Truth without having imposed our own
model of the evolutionary process in the generation of the data. 

MR:
It states, "Three different tree topologies were used to explore the
effect of long branch attraction with data that incorporated
substitution bias and different degrees of among site rate variation."
Does the "substitution bias" constitute assuming some (if not all) of
the same aspects of the evolutionary process in the generation of the
data and in the likelihood model assumed in the analysis? 

Guy Hoelzer:
Particular patterns of substitution bias are often assumed in maximum
likelihood analyses of phylogenetic data. The circularity that concerns
me is not equally problematical in all such studies, so you really have
to read each one very carefully to assess the extent of the problem. 

Cheers, 
Guy

MR:
Not much to add. Thanks for the info. I agree using real biological data
but as you concede in most situations one is severely constrained. 

"It's uncertain whether intelligence has any long term survival value.
Bacteria do quite well with it."

Stephen Hawking
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