BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.

Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally.

Computational Performance and Statistical Accuracy of *BEAST and Comparisons with Other Methods.

Under the multispecies coalescent model of molecular evolution, gene trees have independent evolutionary histories within a shared species tree. In comparison, supermatrix concatenation methods assume that gene trees share a single common genealogical history, thereby equating gene coalescence with species divergence. The multispecies coalescent is supported by previous studies which found that its predicted distributions fit empirical data, and that concatenation is not a consistent estimator of the species tree.

Evaluating a multigene environmental DNA approach for biodiversity assessment.

Background: There is an increasing demand for rapid biodiversity assessment tools that have a broad taxonomic coverage. Here we evaluate a suite of environmental DNA (eDNA) markers coupled with next generation sequencing (NGS) that span the tree of life, comparing them with traditional biodiversity monitoring tools within ten 20×20 meter plots along a 700 meter elevational gradient.

Results: From six eDNA datasets (one from each of 16S, 18S, ITS, trnL and two from COI) we identified sequences from 109 NCBI taxonomy-defined phyla or equivalent, ranging from 31 to 60 for a given eDNA marker.

Calibrated birth-death phylogenetic time-tree priors for bayesian inference.

Here we introduce a general class of multiple calibration birth-death tree priors for use in Bayesian phylogenetic inference. All tree priors in this class separate ancestral node heights into a set of "calibrated nodes" and "uncalibrated nodes" such that the marginal distribution of the calibrated nodes is user-specified whereas the density ratio of the birth-death prior is retained for trees with equal values for the calibrated nodes. We describe two formulations, one in which the calibration information informs the prior on ranked tree topologies, through the (conditional) prior, and the other which factorizes the prior on divergence times and ranked topologies, thus allowing uniform, or any arbitrary prior distribution on ranked topologies.

BEAST 2: a software platform for Bayesian evolutionary analysis.

We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility.

Looking for trees in the forest: summary tree from posterior samples.

Background: Bayesian phylogenetic analysis generates a set of trees which are often condensed into a single tree representing the whole set. Many methods exist for selecting a representative topology for a set of unrooted trees, few exist for assigning branch lengths to a fixed topology, and even fewer for simultaneously setting the topology and branch lengths. However, there is very little research into locating a good representative for a set of rooted time trees like the ones obtained from a BEAST analysis.

Simulating gene trees under the multispecies coalescent and time-dependent migration.

Background: The multispecies coalescent model has become popular in recent years as a framework to infer a species phylogeny from multilocus genetic data collected from multiple individuals. The model assumes that speciation occurs at a specific point in time, after which the two sub-species evolve in total isolation. However in reality speciation may occur over an extended period of time, during which sister lineages remain in partial contact.

The pipid root.

The estimation of phylogenetic relationships is an essential component of understanding evolution. Accurate phylogenetic estimation is difficult, however, when internodes are short and old, when genealogical discordance is common due to large ancestral effective population sizes or ancestral population structure, and when homoplasy is prevalent. Inference of divergence times is also hampered by unknown and uneven rates of evolution, the incomplete fossil record, uncertainty in relationships between fossil and extant lineages, and uncertainty in the age of fossils.

Sequence diversity under the multispecies coalescent with Yule process and constant population size.

The study of sequence diversity under phylogenetic models is now classic. Theoretical studies of diversity under the Kingman coalescent appeared shortly after the introduction of the coalescent. In this paper we revisit this topic under the multispecies coalescent, an extension of the single population model to multiple populations.

Calibrated tree priors for relaxed phylogenetics and divergence time estimation.

The use of fossil evidence to calibrate divergence time estimation has a long history. More recently, Bayesian Markov chain Monte Carlo has become the dominant method of divergence time estimation, and fossil evidence has been reinterpreted as the specification of prior distributions on the divergence times of calibration nodes. These so-called "soft calibrations" have become widely used but the statistical properties of calibrated tree priors in a Bayesian setting hashave not been carefully investigated.

Calibrating divergence times on species trees versus gene trees: implications for speciation history of Aphelocoma jays.

Estimates of the timing of divergence are central to testing the underlying causes of speciation. Relaxed molecular clocks and fossil calibration have improved these estimates; however, these advances are implemented in the context of gene trees, which can overestimate divergence times. Here we couple recent innovations for dating speciation events with the analytical power of species trees, where multilocus data are considered in a coalescent context.

Bayesian inference of species trees from multilocus data.

Until recently, it has been common practice for a phylogenetic analysis to use a single gene sequence from a single individual organism as a proxy for an entire species. With technological advances, it is now becoming more common to collect data sets containing multiple gene loci and multiple individuals per species. These data sets often reveal the need to directly model intraspecies polymorphism and incomplete lineage sorting in phylogenetic estimation procedures.

Bayesian inference of population size history from multiple loci.

Background: Effective population size (Ne) is related to genetic variability and is a basic parameter in many models of population genetics. A number of methods for inferring current and past population sizes from genetic data have been developed since JFC Kingman introduced the n-coalescent in 1982. Here we present the Extended Bayesian Skyline Plot, a non-parametric Bayesian Markov chain Monte Carlo algorithm that extends a previous coalescent-based method in several ways, including the ability to analyze multiple loci.

The perils of plenty: what are we going to do with all these genes?

This new century's biology promises more of everything--more genes, more organisms, more species and, in short, more data. The flood of data challenges us to find better and quicker ways to summarize and analyse. Here, we present preliminary results and proofs of concept from three of our research projects that are motivated by our search for solutions to the perils of plenty.