Phyloseminar
http://phyloseminar.org/
phyloseminar -- a free online seminar about phylogeneticsphyloseminarhttps://feedburner.google.com
Barbara Holland: Developing a statistically powerful measure for quartet tree inference using phylogenetic and Markov invariants, 2017-06-22 14:00 PDT
http://phyloseminar.org/
<p>Recently there has been renewed interest in phylogenetic inference methods based on phylogenetic invariants, alongside the related Markov invariants. Broadly speaking, both these approaches give rise to polynomial functions of sequence site patterns that, in expectation value, either vanish for particular evolutionary trees (in the case of phylogenetic invariants) or have well understood transformation properties (in the case of Markov invariants).</p>
<p>While both approaches have been valued for their intrinsic mathematical interest, it is not clear how they relate to each other, and to what extent they can be used as practical tools for inference of phylogenetic trees. By focusing on the special case of binary sequence data and quartets of taxa, we are able to view these two different polynomial-based approaches within a common framework.</p>
<p>We present three desirable statistical properties that we argue any invariant-based phylogenetic method should satisfy: (1) sensible behaviour under reordering of input sequences; (2) stability as the taxa evolve independently according to a Markov process; and (3) explicit dependence on the assumption of a continuous-time process. Motivated by these statistical properties, we develop and explore several new phylogenetic inference methods. In particular, we develop a statistically bias-corrected version of the Markov invariants approach which satisfies all three properties. We also extend previous work by showing that the phylogenetic in- variants can be implemented in such a way as to satisfy property (3). A simulation study shows that, in comparison to other methods, our new proposed approach based on bias-corrected Markov invariants is extremely powerful for phylogenetic inference.</p>2017-06-05T14:00:00-07:0069holland
Laura Kubatko: Using invariants for coalescent-based phylogenetic inference, 2017-05-31 10:00 PDT
http://phyloseminar.org/
<p>The advent of rapid and inexpensive sequencing technologies has necessitated the development of computationally efficient methods for analyzing sequence data for many genes simultaneously in a phylogenetic framework. The coalescent process is the most commonly used model for linking the underlying genealogies of individual genes with the global species-level phylogeny, but inference under the coalescent model is computationally daunting in the typical inference frameworks (e.g., the likelihood and Bayesian frameworks) due to the dimensionality of the space of both gene trees and species trees. By viewing the data arising under the phylogenetic coalescent model as a collection of site patterns, the algebraic structure associated with the probability distribution on the site patterns can be used to develop computationally efficient methods for inference via phylogenetic invariants.</p>
<p>In this talk, I will discuss three problems that can be addressed using invariants. First, I will describe how identifiability results for four-taxon species trees based on site pattern probabilities can be used to build a quartet-based inference algorithm for trees of arbitrary size. Second, methods for rooting phylogenetic species trees inferred under the coalescent model will be discussed. Finally, the use of invariants to detect species that arose via hybridization will be described. The methods presented will be demonstrated on several phylogenomic-scale datasets. Because the methods are derived in a fully model-based framework (i.e., the coalescent process is used to model the relationship between gene trees and the species tree, and standard nucleotide substitution models (GTR+I+G and all submodels) are used for sequence-level evolution), these methods are promising approaches for computationally efficient, model-based inference for the large-scale sequence data available today.</p>2017-04-26T10:00:00-07:0068kubatko
Marta Casanellas Rius: Phylogenetic invariants: what are they and why should we care, 2017-04-26 10:00 PDT
http://phyloseminar.org/
<p>It has been now thirty years since the introduction of phylogenetic invariants by Lake, Cavender, and Felsenstein. However, the use of phylogenetic invariants as a method of phylogenetic reconstruction has been in a dormant state for about 20 years; quoting J. Felsenstein in his 2004 book "invariants are worth attention, not for what they do for us now, but what they might lead to in the future".</p>
<p>During the last decade many efforts have been made by mathematicians to completely understand the structure and use of phylogenetic invariants. This has led to the characterization of different types of invariants for many different models: from the most simple Jukes-Cantor model to the general Markov model, and even mixtures of them and the coalescent. Most importantly, this has produced new and efficient methods of phylogenetic reconstruction for complex models. The use of invariants has also been used in model selection and has been crucial in proving the identifiability of parameters for certain models.</p>
<p>In this talk we shall introduce phylogenetic invariants, explain the main ideas that underlie the methods of phylogenetic reconstruction based on invariants and discuss the advantages and drawbacks of them.</p>2017-03-28T10:00:00-07:0067casanellas
W. Ford Doolittle: Darwinizing Gaia, 2017-03-28 10:00 PDT
http://phyloseminar.org/
<p>Talks in this series have largely focused on population genetic and phylogenetic methods for reconstructing micro- and macroevolutionary patterns consequent from microevolutionary processes. When natural selection is invoked, it is generally assumed to operate through the differential reproduction of favored variants among populations of physical entities, be they genes, cells, organisms or (rarely) species. The Gaia hypothesis of James Lovelock, co-developed and vigorously promoted by Lynn Margulis in the 1970s, has been very popular with the lay public. But most mainstream Darwinists scorned and still do not accept the notion. They cannot imagine global biospheric stability being selected for at any of the above levels, and do not see the Earth's biosphere as part of a population of comparable global entities engaged in reproductive competition. Most philosophers of biology would similarly argue that any global homeostatic systems (if they exist) can be only "fortuitous byproducts" of lower-level selection. I will suggest that we look at the biogeochemical cycles and other homeostatic processes that might confer stability-- rather than the individual organisms or "species" (mostly microbial) that implement them-- as the relevant units of selection. By thus focusing our attentions on the "song", not the "singers," a Darwinized Gaia might be developed. Our understanding of evolution by natural selection would however need to be stretched to accommodate differential persistence, and our definition of reproduction would need to be reworked.</p>2017-03-03T10:00:00-08:0066doolittle
Tim Vaughan: Joint Bayesian inference of bacterial ancestral recombination graphs, 2017-02-23 12:00 PST
http://phyloseminar.org/
<p>Homologous recombination is a central feature of bacterial evolution,
yet confounds traditional phylogenetic methods. In this seminar I
will present a novel approach to inferring bacterial evolution based
on the ClonalOrigin model (Didelot et al., Genetics, 2010). This
method permits joint Bayesian inference of the entire bacterial
recombination graph and associated model parameters. The method is
implemented in the BEAST 2 phylogenetic inference package. It can be
easily combined with a variety of substitution models accounting for
site-to-site clock rate heterogeneity as well as parametric and
non-parametric models of effective population size dynamics. I will
also present work on summarizing posterior distributions over the
space of tree-based recombination graphs which, together with the
joint inference method, aims to bridge the technological gap between
recombination-aware phylogenetic inference and traditional methods.</p>2017-01-23T11:30:00-08:0065vaughan