scholarly journals An Examination of the Monophyly of Morning Glory Taxa Using Bayesian Phylogenetic Inference

2002 ◽  
Vol 51 (5) ◽  
pp. 740-753 ◽  
Author(s):  
Richard E. Miller ◽  
Thomas R. Buckley ◽  
Paul S. Manos
Keyword(s):  
Phylogenetic Inference ◽  
Morning Glory ◽  
Bayesian Phylogenetic Inference

MrBayes sMC3

2016 ◽  
Vol 32 (2) ◽  
pp. 246-265 ◽  
Author(s):  
Lídia Kuan ◽  
Frederico Pratas ◽  
Leonel Sousa ◽  
Pedro Tomás
Keyword(s):  
Dna Sequences ◽  
Software Package ◽  
State Of The Art ◽  
Phylogenetic Inference ◽  
Iterative Approach ◽  
Computational Power ◽  
Data Transfers ◽  
Bayesian Phylogenetic Inference ◽  
Level Parallelism ◽  
Number Of Iterations

MrBayes is a popular software package for Bayesian phylogenetic inference, which uses an iterative approach to derive an evolutionary tree for a collection of species whose DNA sequences are known. Computationally, MrBayes is characterized by a large number of iterations, each composed of a set of tasks that isolated are not very time-consuming, but are globally computationally demanding. To accelerate the latest MrBayes 3.2, this paper presents MrBayes sMC3, which relies on the computational power of an heterogeneous CPU+GPU platform. For this, MrBayes sMC3 exploits both task and data-level parallelism while minimizing the overheads associated with kernel launches and CPU-GPU data transfers. Experimental results indicate that the proposed parallel approach, together with the proposed set of optimizations, allow for an application acceleration of up to 10× regarding the original MrBayes, and up to 3× regarding the Beagle Library. Furthermore, by analyzing the convergence rate of MrBayes sMC3 with that of the state-of-the-art approaches, a significant reduction in execution time is observed.

scholarly journals Stepwise Bayesian Phylogenetic Inference

2020 ◽  
Author(s):  
Sebastian Höhna ◽  
Allison Y. Hsiang
Keyword(s):  
Single Point ◽  
Gene Tree ◽  
Computational Cost ◽  
Phylogenetic Inference ◽  
Point Estimate ◽  
Sufficient Information ◽  
Analysis Pipeline ◽  
Stepwise Approach ◽  
Joint Approach ◽  
Bayesian Phylogenetic Inference

AbstractThe ideal approach to Bayesian phylogenetic inference is to estimate all parameters of interest jointly in a single hierarchical model. However, this is often not feasible in practice due to the high computational cost that would be incurred. Instead, phylogenetic pipelines generally consist of chained analyses, whereby a single point estimate from a given analysis is used as input for the next analysis in the chain (e.g., a single multiple sequence alignment is used to estimate a gene tree). In this framework, uncertainty is not propagated from step to step in the chain, which can lead to inaccurate or spuriously certain results. Here, we formally develop and test the stepwise approach to Bayesian inference, which uses importance sampling to generate observations for the next step of an analysis pipeline from the posterior produced in the previous step. We show that this approach is identical to the joint approach given sufficient information in the data and in the importance sample. This is demonstrated using both a toy example and an analysis pipeline for inferring divergence times using a relaxed clock model. The stepwise approach presented here not only accounts for uncertainty between analysis steps, but also allows for greater flexibility in program choice (and hence model availability) and can be more computationally efficient than the traditional joint approach when multiple models are being tested.

scholarly journals Two C++ Libraries for Counting Trees on a Phylogenetic Terrace

2017 ◽  
Author(s):  
R. Biczok ◽  
P. Bozsoky ◽  
P. Eisenmann ◽  
J. Ernst ◽  
T. Ribizel ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Phylogenetic Tree ◽  
Phylogenetic Inference ◽  
Source Codes ◽  
Likelihood Score ◽  
Order Of Magnitude ◽  
Tree Topologies ◽  
Tree Space ◽  
Bayesian Phylogenetic Inference ◽  
Counting Trees

AbstractMotivationThe presence of terraces in phylogenetic tree space, that is, a potentially large number of distinct tree topologies that have exactly the same analytical likelihood score, was first described by Sanderson et al, (2011). However, popular software tools for maximum likelihood and Bayesian phylogenetic inference do not yet routinely report, if inferred phylogenies reside on a terrace, or not. We believe, this is due to the unavailability of an efficient library implementation to (i) determine if a tree resides on a terrace, (ii) calculate how many trees reside on a terrace, and (iii) enumerate all trees on a terrace.ResultsIn our bioinformatics programming practical we developed two efficient and independent C++ implementations of the SUPERB algorithm by Constantinescu and Sankoff (1995) for counting and enumerating the trees on a terrace. Both implementations yield exactly the same results and are more than one order of magnitude faster and require one order of magnitude less memory than a previous 3rd party python implementation.AvailabilityThe source codes are available under GNU GPL at https://github.com/[email protected]

A new autumn flowering Crocus (Iridaceae) from SW Turkey: C. terzioghluii

Phytotaxa ◽  
2019 ◽  
Vol 420 (3) ◽  
pp. 224-232
Author(s):  
ALMILA CIFTCI ◽  
DOERTE HARPKE ◽  
OSMAN EROL
Keyword(s):  
New Species ◽  
Phylogenetic Inference ◽  
Nuclear Rdna ◽  
Metaphase Chromosomes ◽  
Rdna Its ◽  
Sw Turkey ◽  
Close Relationship ◽  
Autumn Flowering ◽  
Bayesian Phylogenetic Inference ◽  
A New Species

Crocus terzioghluii (Iridaceae) is described as a new species endemic to southwestern Anatolia, Turkey. It is related to Crocus babadagensis and differs from this species in having corm tunics with well-developed rings, and prominent stripes on outer segments, as well as in leaf number and flowering time. The corms and tunics of both species are illustrated. A phylogenetic tree obtained by Bayesian phylogenetic inference of the combined sequences of the nuclear rDNA ITS and ETS regions confirms the affiliation of C. terzioghluii to C. ser. Biflori and its close relationship to C. babadagensis. A microphotograph of the metaphase chromosomes (2n = 2x = 8) along with the idiogram and a leaf cross section of the new species are given.

scholarly journals Adaptive Tree Proposals for Bayesian Phylogenetic Inference

2021 ◽  
Author(s):  
X Meyer
Keyword(s):  
Posterior Distribution ◽  
Computational Cost ◽  
Phylogenetic Inference ◽  
Mixing Efficiency ◽  
Sample Tree ◽  
Practical Challenge ◽  
Consistent Performance ◽  
Performance Gains ◽  
Bayesian Phylogenetic Inference ◽  
Novel Design

Abstract Bayesian inference of phylogeny with MCMC plays a key role in the study of evolution. Yet, this method still suffers from a practical challenge identified more than two decades ago: designing tree topology proposals that efficiently sample tree spaces. In this article, I introduce the concept of adaptive tree proposals for unrooted topologies, that is tree proposals adapting to the posterior distribution as it is estimated. I use this concept to elaborate two adaptive variants of existing proposals and an adaptive proposal based on a novel design philosophy in which the structure of the proposal is informed by the posterior distribution of trees. I investigate the performance of these proposals by first presenting a metric that captures the performance of each proposal within a mixture of proposals. Using this metric, I compare the performance of the adaptive proposals to the performance of standard and parsimony-guided proposals on 11 empirical datasets. Using adaptive proposals led to consistent performance gains and resulted in up to 18-fold increases in mixing efficiency and 6-fold increases in convergence rate without increasing the computational cost of these analyses.

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