Re: Bayesian analysis for morphological data!!!

[Jean-Michel Benoit <s.aegyptiacus@wanadoo.fr>]

Er, all that seems a lot complicated to me. I suppose a comparison between
trees based on this "new" method and trees based on the "old" method is
available somewhere so as to give one a more precise idea?
Cheers,
Jean-Michel

----- Original Message -----
From: "David Marjanovic" <david.marjanovic@gmx.at>
To: <dinosaur@usc.edu>
Sent: Wednesday, December 14, 2005 6:50 PM
Subject: Bayesian analysis for morphological data!!!


> At last someone explains how to do that!
>
> John J. Wiens, James W. Fetzner, Jr., Christopher L. Parkinson & Tod W.
> Reeder: Hylid Frog Phylogeny and Sampling Strategies for Speciose Clades,
> Systematic Biology 54(5), 778 -- 807 (October 2005)
>
> >From page 781:
>
> "Morphological data [in addition to several genes] were coded as binary
> and multistate characters and were analyzed using parsimony and Bayesian
> methods. Multistate characters involving quantitative variation along a
> single axis (length or extent of ossification of a structure, number of a
> meristic character) were ordered. Given that the states of these
> characters were delimited based on the assumption that similarity in trait
> values is informative, we believe it is only logical to use this
> assumption in ordering the states. The alternative is to assume that
> similarity in quantitative trait values is not informative, in which case
> many taxa would have to be given a unique state for these characters
> (because most taxa will not be identical), the states would be unordered,
> and these characters would therefore be largely uninformative."
>
> Meristic characters appear to be the number of something (like sacral
> vertebrae). Not ordering these would mean that you can go from, say, 1
> sacral vertebra to 10 in one step (and back in another one).
>
> p. 781f:
>
> "Bayesian analyses were performed using MrBayes version 3.0b4 [...].
> Analyses of the morphological data used two replicate searches of 10.0 x
> 10^6 generations each, sampling every 1,000 generations, with four chains
> and default priors (i.e., equal state frequencies; uniform shape
> parameter; all topologies equally likely a priori; branch lengths
> unconstrained:exponential). [...] The phylogeny was estimated from the
> majority-rule consensus of post-burn-in trees pooled from the two
> replicates. [...]
>   Bayesian analysis of the morphological data was performed using the
> maximum likelihood model for discrete morphological character data (Markov
> _k_ or Mk) developed by Lewis (2001). The data were modeled under the
> assumption that only characters that varied among taxa were included
> (i.e., coding = variable; see Lewis (2001)). Analyses were performed both
> including and excluding a parameter for variation in rates of change among
> characters (using the gamma distribution; Yang, 1993, 1994). We then
> compared the fit of these models to our data using the Bayes factor
> (following Nylander et al., 2004). The Bayes factor (B10) represents the
> ratio of the model likelihoods of the two models under consideration.
> Values of [...] [2 ln B10] were calculated (i.e., two times the difference
> between the harmonic means of the log-likelihoods (post burn-in) of the
> two models) and values > 10 were considered to be very strong evidence
> favoring one model over the other (Kass and Raftery, 1995). The harmonic
> mean of the log-likelihoods was calculated using the _sump_ command in
> MrBayes, based on the pooled likelihood scores of the post-burn-in trees
> from the two replicate searches for each model. These analyses strongly
> favored the Mk + Gamma model (Mk-v of Lewis (2001), lnL = -3,723.62) over
> the Mk model (lnL = -3,850.67), with a Bayes factor of 254.10. Only
> results from the former analysis are presented."
>
> Er, yeah. Erm. I don't quite get all of this, but it looks like a very
> promising approach for the future, and maybe for the present. Note that
> the Gamma parameter does not require input on which characters evolve
> faster than which others.
>
> p. 786:
>
> "_Results_
>
> _Morphological Data_
>
>   Parsimony and Bayesian analyses gave similar results for most analyses
> in this study, and differences generally involved branches only weakly
> supported by one or both methods. Given that we expect model-based methods
> to provide phylogenetic estimates that are as accurate or more accurate
> than those from parsimony (e.g., all data sets show demonstrably poor fit
> to the simple model of character change assumed by equally weighted
> parsimony), and in order to conserve space and paper, we present and
> describe trees from the Bayesian analyses only (for all types of data).
> However, we indicate congruent support from parsimony bootstrapping on all
> trees, and describe many parsimony results in the text."
>
> As an aside, the (fully resolved!!!) morphological tree is, to the
> authors' own surprise, thoroughly weird. The traditional classification
> (morphology-based) is much more similar to the molecular tree and to the
> combined tree (which the authors prefer). I guess the reason is the
> unfavorable ratio of taxa (79) to morphological + life history +
> chromosomal characters (144). Compare the theropod analysis in The
> Dinosauria -- 75 taxa, 638 characters (and a few impressive plesiomorphies
> nevertheless). Way to go. -- Besides, the number of 144 characters is IMHO
> artificially inflated. Consider characters 35 and 36: "Tympanic annulus:
> (0) absent, (1) present", "Tympanic annulus: (0) separate from crista
> parotica, (1) fused to crista parotica". Why not fuse these into an
> unordered multistate character? "Tympanic annulus: (0) absent, (1)
> separate from crista parotica, (2) fused to it"? There are several more
> such pairs, like 137 and 138 or 25 and 26 (...which might also be
> correlated with 24). The authors themselves only identify probable
> correlation among characters that are probably adaptations for climbing
> and convergence of a specialized tadpole type (coded as several
> characters) between an ingroup and an outgroup taxon.
>
> I won't bore you with the outcome, except to mention that most
> leptodactylids aren't leptodactylids. And next I'll read
>
> Paul O. Lewis: A Likelihood Approach to Estimating Phylogeny from Discrete
> Morphological Character Data, Systematic Biology 50(6), November 2001
>
> Oh, and the main message of Wiens et al.: Don't be afraid of missing data.
> :-)
>
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