Hastings ratio of the LOCAL proposal used in Bayesian phylogenetics.
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Algorithms↗
Biomedical subjects
Paul O Lewis
Publications and source records attributed to Paul O Lewis.
Unearthing the molecular phylodiversity of desert soil green algae (Chlorophyta).
Deserts are not usually considered biodiversity hotspots, but desert microbiotic crust communities exhibit a rich diversity of both eukaryotic and prokaryotic life forms. Like many communities dominated by microscopic organisms, they defy characterization by traditional species-counting approaches to assessing biodiversity. Here we use exclusive molecular phylodiversity (E) to quantify the amount of evolutionary divergence unique to desert-dwelling green algae (Chlorophyta) in microbiotic crust communities. Given a phylogenetic tree with branch lengths expressed in units of expected substitutions per site, E is the total length of all tree segments representing exclusively desert lineages. Using MCMC to integrate over tree topologies and branch lengths provides 95% Bayesian credible intervals for phylodiversity measures. We found substantial exclusive molecular phylodiversity based on 18S rDNA data, showing that desert lineages are distantly related to their nearest aquatic relatives. Our results challenge conventional wisdom, which holds that there was a single origin of terrestrial green plants and that green algae are merely incidental visitors rather than indigenous components of desert communities. We identify examples of lineage diversification within deserts and at least 12 separate transitions from aquatic to terrestrial life apart from the most celebrated transition leading to the embryophyte land plants. [Bayesian phylogenetics; biodiversity; exclusive molecular phylodiversity; microbiotic crusts.].
Biodiversity↗
Polytomies and Bayesian phylogenetic inference.
Bayesian phylogenetic analyses are now very popular in systematics and molecular evolution because they allow the use of much more realistic models than currently possible with maximum likelihood methods. There are, however, a growing number of examples in which large Bayesian posterior clade probabilities are associated with very short branch lengths and low values for non-Bayesian measures of support such as nonparametric bootstrapping. For the four-taxon case when the true tree is the star phylogeny, Bayesian analyses become increasingly unpredictable in their preference for one of the three possible resolved tree topologies as data set size increases. This leads to the prediction that hard (or near-hard) polytomies in nature will cause unpredictable behavior in Bayesian analyses, with arbitrary resolutions of the polytomy receiving very high posterior probabilities in some cases. We present a simple solution to this problem involving a reversible-jump Markov chain Monte Carlo (MCMC) algorithm that allows exploration of all of tree space, including unresolved tree topologies with one or more polytomies. The reversible-jump MCMC approach allows prior distributions to place some weight on less-resolved tree topologies, which eliminates misleadingly high posteriors associated with arbitrary resolutions of hard polytomies. Fortunately, assigning some prior probability to polytomous tree topologies does not appear to come with a significant cost in terms of the ability to assess the level of support for edges that do exist in the true tree. Methods are discussed for applying arbitrary prior distributions to tree topologies of varying resolution, and an empirical example showing evidence of polytomies is analyzed and discussed.
Bayes Theorem↗
NCL: a C++ class library for interpreting data files in NEXUS format.
UNLABELLED: The NEXUS Class Library (NCL) is a collection of C++ classes designed to simplify interpreting data files written in the NEXUS format used by many computer programs for phylogenetic analyses. The NEXUS format allows different programs to share the same data files, even though none of the programs can interpret all of the data stored therein. Because users are not required to reformat the data file for each program, use of the NEXUS format prevents cut-and-paste errors as well as the proliferation of copies of the original data file. The purpose of making the NCL available is to encourage the use of the NEXUS format by making it relatively easy for programmers to add the ability to interpret NEXUS files in newly developed software. AVAILABILITY: The NCL is freely available under the GNU General Public License from http://hydrodictyon.eeb.uconn.edu/ncl/ SUPPLEMENTARY INFORMATION: Documentation for the NCL (general information and source code documentation) is available in HTML format at http://hydrodictyon.eeb.uconn.edu/ncl/
Databases, Bibliographic↗
Phylogeny estimation: traditional and Bayesian approaches.
The construction of evolutionary trees is now a standard part of exploratory sequence analysis. Bayesian methods for estimating trees have recently been proposed as a faster method of incorporating the power of complex statistical models into the process. Researchers who rely on comparative analyses need to understand the theoretical and practical motivations that underlie these new techniques, and how they differ from previous methods. The ability of the new approaches to address previously intractable questions is making phylogenetic analysis an essential tool in an increasing number of areas of genetic research.
Bayes Theorem↗
A Bayesian approach to inferring population structure from dominant markers.
Molecular markers derived from polymerase chain reaction (PCR) amplification of genomic DNA are an important part of the toolkit of evolutionary geneticists. Random amplified polymorphic DNA markers (RAPDs), amplified fragment length polymorphisms (AFLPs) and intersimple sequence repeat (ISSR) polymorphisms allow analysis of species for which previous DNA sequence information is lacking, but dominance makes it impossible to apply standard techniques to calculate F-statistics. We describe a Bayesian method that allows direct estimates of FST from dominant markers. In contrast to existing alternatives, we do not assume previous knowledge of the degree of within-population inbreeding. In particular, we do not assume that genotypes within populations are in Hardy-Weinberg proportions. Our estimate of FST incorporates uncertainty about the magnitude of within-population inbreeding. Simulations show that samples from even a relatively small number of loci and populations produce reliable estimates of FST. Moreover, some information about the degree of within-population inbreeding (FIS) is available from data sets with a large number of loci and populations. We illustrate the method with a reanalysis of RAPD data from 14 populations of a North American orchid, Platanthera leucophaea.
Bayes Theorem↗
Genetic algorithms and parallel processing in maximum-likelihood phylogeny inference.
We investigated the usefulness of a parallel genetic algorithm for phylogenetic inference under the maximum-likelihood (ML) optimality criterion. Parallelization was accomplished by assigning each "individual" in the genetic algorithm "population" to a separate processor so that the number of processors used was equal to the size of the evolving population (plus one additional processor for the control of operations). The genetic algorithm incorporated branch-length and topological mutation, recombination, selection on the ML score, and (in some cases) migration and recombination among subpopulations. We tested this parallel genetic algorithm with large (228 taxa) data sets of both empirically observed DNA sequence data (for angiosperms) as well as simulated DNA sequence data. For both observed and simulated data, search-time improvement was nearly linear with respect to the number of processors, so the parallelization strategy appears to be highly effective at improving computation time for large phylogenetic problems using the genetic algorithm. We also explored various ways of optimizing and tuning the parameters of the genetic algorithm. Under the conditions of our analyses, we did not find the best-known solution using the genetic algorithm approach before terminating each run. We discuss some possible limitations of the current implementation of this genetic algorithm as well as of avenues for its future improvement.
Algorithms↗