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 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.

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

An Average-Passage Empirical Closure Model for Centrifugal Compressors

2004 ◽  
Author(s):  
Limin Gao ◽  
Guang Xi ◽  
Shangjin Wang
Keyword(s):  
Experimental Data ◽  
Empirical Model ◽  
Stokes Equations ◽  
Computational Cost ◽  
Axial Flow ◽  
Equation System ◽  
Computational Grids ◽  
Navier Stokes ◽  
Sufficient Information ◽  
Centrifugal Compressors

Applying the novel time- and passage-averaging operators, a reduced average-passage equation system is derived to remove the bodyforce and the blockage factor in Adamczyk’s average-passage equations. Like the Reynolds-averaged Navier-Stokes equations the average-passage flow model does not contain sufficient information to determine its solution. Based on the rich throughflow analysis for axial-flow turbomachinery and numerous studies for centrifugal compressors, a semi-empirical model of the deterministic stress is developed for centrifugal compressors in the present study. Finally, the empirical model coupled with the interface approach is applied to predict the time-averaged flow field in a tested centrifugal compressor stage and the results are compared with experimental data. Using the same computational grids, the computational cost with the empirical model is slightly more than that with the mixing plane model, and a good agreement was obtained between the numerical results and experimental data.

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.

Modeling of a Rotaxane-based Molecular Device

2002 ◽  
Vol 741 ◽  
Author(s):  
Xiange Zheng ◽  
Karl Sohlberg
Keyword(s):  
Single Point ◽  
Computational Cost ◽  
Geometry Optimization ◽  
Potential Energy Function ◽  
Computational Procedure ◽  
Structural Features ◽  
Full Geometry Optimization ◽  
Point Energy ◽  
Semi Empirical ◽  
Relationship Of

ABSTRACTA computational procedure is presented for investigating photo-induced switchable rotaxanes and demonstrated for a known system. This procedure starts with the generation of more than 104 chemically reasonable rotaxane conformations based on an empirical intramolecular potential energy function. Single-point energy calculations at the semi-empirical (AM1) level are carried out for each structure in the singlet (ground), triplet, and anionic doublet states. The structural features are assigned and then correlated with energy for each state. What emerges is a profile of the structure-energy relationship that captures the salient features of the system that endow it with device-like character. Full geometry optimization of a subset of co-conformations (∼1%) demonstrates that the procedure based on single-point calculations is sufficient to obtain a profile of the relationship of structural features to energy that is consistent with experiments, at greatly reduced computational cost.

scholarly journals Is it Possible to Find a Good Point Estimate of a Calibrated Radiocarbon Date?

Radiocarbon ◽  
2007 ◽  
Vol 49 (2) ◽  
pp. 393-401 ◽  
Author(s):  
Adam Michczyński
Keyword(s):  
Computer Simulation ◽  
Confidence Intervals ◽  
Single Point ◽  
Radiocarbon Date ◽  
Point Estimate ◽  
Local Mode ◽  
True Value ◽  
Point Estimates ◽  
Good Point ◽  
Accepted Practice

The result from probabilistic calibration of a radiocarbon date is given in the form of a probability density function. Consequently, reporting a 68% or 95% confidence interval has became a commonly accepted practice. However, many users of 14C dates still try to present the results of calibration as a single point. This manner of presentation is often applied during the construction of age-depth models due to its convenience and simplicity. In this paper, the author tests whether it is possible to find a good point estimate of a calibrated 14C date. The idea of the tests is to compare, using computer simulation, the true value of the calendar age with the age calculated based on the probabilistic calibration of the 14C date and the method of finding the point estimate. The test is carried out for the following point estimates: mode, median, average, the central point of the confidence intervals, and the local mode inside the confidence intervals. The results show that none of these may be considered as a good estimate.

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