scholarly journals Phylogenetic estimation error can decrease the accuracy of species delimitation: a Bayesian implementation of the general mixed Yule-coalescent model

2012 ◽  
Vol 12 (1) ◽  
pp. 196 ◽  
Author(s):  
Noah M Reid ◽  
Bryan C Carstens
Keyword(s):  
Species Delimitation ◽  
Estimation Error ◽  
Coalescent Model ◽  
Bayesian Implementation ◽  
Phylogenetic Estimation

scholarly journals The BPP program for species tree estimation and species delimitation

2015 ◽  
Vol 61 (5) ◽  
pp. 854-865 ◽  
Author(s):  
Ziheng Yang
Keyword(s):  
Species Delimitation ◽  
Genomic Sequence ◽  
Sequence Data ◽  
Species Tree ◽  
Joint Analysis ◽  
Coalescent Model ◽  
Species Phylogeny ◽  
Multispecies Coalescent ◽  
Tree Estimation ◽  
Nuclear Loci

Abstract This paper provides an overview and a tutorial of the BPP program, which is a Bayesian MCMC program for analyzing multi-locus genomic sequence data under the multispecies coalescent model. An example dataset of five nuclear loci from the East Asian brown frogs is used to illustrate four different analyses, including estimation of species divergence times and population size parameters under the multispecies coalescent model on a fixed species phylogeny (A00), species tree estimation when the assignment and species delimitation are fixed (A01), species delimitation using a fixed guide tree (A10), and joint species delimitation and species-tree estimation or unguided species delimitation (A11). For the joint analysis (A11), two new priors are introduced, which assign uniform probabilities for the different numbers of delimited species, which may be useful when assignment, species delimitation, and species phylogeny are all inferred in one joint analysis. The paper ends with a discussion of the assumptions, the strengths and weaknesses of the BPP analysis.

scholarly journals Uncertain-tree: discriminating among competing approaches to the phylogenetic analysis of phenotype data

2017 ◽  
Vol 284 (1846) ◽  
pp. 20162290 ◽  
Author(s):  
Mark N. Puttick ◽  
Joseph E. O'Reilly ◽  
Alastair R. Tanner ◽  
James F. Fleming ◽  
James Clark ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Accurate Method ◽  
Morphological Data ◽  
Or Groups ◽  
Phenotype Data ◽  
Bayesian Implementation ◽  
Phylogenetic Estimation ◽  
The Impact

Morphological data provide the only means of classifying the majority of life's history, but the choice between competing phylogenetic methods for the analysis of morphology is unclear. Traditionally, parsimony methods have been favoured but recent studies have shown that these approaches are less accurate than the Bayesian implementation of the Mk model. Here we expand on these findings in several ways: we assess the impact of tree shape and maximum-likelihood estimation using the Mk model, as well as analysing data composed of both binary and multistate characters. We find that all methods struggle to correctly resolve deep clades within asymmetric trees, and when analysing small character matrices. The Bayesian Mk model is the most accurate method for estimating topology, but with lower resolution than other methods. Equal weights parsimony is more accurate than implied weights parsimony, and maximum-likelihood estimation using the Mk model is the least accurate method. We conclude that the Bayesian implementation of the Mk model should be the default method for phylogenetic estimation from phenotype datasets, and we explore the implications of our simulations in reanalysing several empirical morphological character matrices. A consequence of our finding is that high levels of resolution or the ability to classify species or groups with much confidence should not be expected when using small datasets. It is now necessary to depart from the traditional parsimony paradigms of constructing character matrices, towards datasets constructed explicitly for Bayesian methods.

scholarly journals A Taxonomic Investigation into the Red Alga Plocamium within New Zealand

2021 ◽  
Author(s):  
◽  
Madeline Wynn Cooper
Keyword(s):  
New Zealand ◽  
Species Delimitation ◽  
Phylogenetic Analyses ◽  
Evolutionary Relationship ◽  
Red Alga ◽  
Morphometric Analyses ◽  
True Diversity ◽  
Candidate Species ◽  
Bayesian Implementation ◽  
Genetic Species

<p>The red alga Plocamium is a cosmopolitan genus, known for its distinct branching pattern and rich chemical composition. Recent studies indicate morphological-based species delimitation approaches have failed to accurately discern diversity, distributions, and evolutionary relationship between species worldwide. Currently there are seven recognized species within New Zealand based on traditional morphological approaches and no molecular based work focused on discerning true diversity of New Zealand species in this genus. This thesis is the first to use molecular-assisted alpha taxonomy to investigate Plocamium within New Zealand. Phylogenetic analyses (Maximum Likelihood and Bayesian Inference) based on COI, rbcL, LSU and combined LSU/COI markers, three molecular species delimitation methods (Automatic Barcode Gap Discovery, General Mixed Yule Coalescent, and Bayesian implementation of the Poisson Tree Processes), and morphometric analyses of various characters (width of main axis (WMA), width of lowest basal ramuli (WLBR), length of lowest basal ramuli (LLBR), number of alternating series of ramuli (NASR), average number of ramuli per alternating series (ANRAS), curvature of basal ramuli (CBR) and serrations present or absent from basal ramuli (SERBR) were used to address this topic. The species delimitation methods revealed at least eleven (A-K) putative genetic species (with some incongruences) within the New Zealand specimens included in the study. Morphometric analyses indicated morphology reflects genetic diversity when multiple measures of multiple characters are used, however this is not the case when considering single characters. Phylogenetic analyses revealed possible monophyly of New Zealand candidate species C-K, and possible relationships to Australian, Chilean, and Taiwanese species. However these backbone relationships were poorly supported. The results of this study indicate that Plocamium diversity within New Zealand has been underestimated and provide the first steps in discovering the true species diversity of Plocamium within New Zealand.</p>

scholarly journals Identifying model violations under the multispecies coalescent model using P2C2M.SNAPP

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8271
Author(s):  
Drew J. Duckett ◽  
Tara A. Pelletier ◽  
Bryan C. Carstens
Keyword(s):  
Posterior Distribution ◽  
Incomplete Lineage Sorting ◽  
R Package ◽  
Predictive Distribution ◽  
Species Trees ◽  
Lineage Sorting ◽  
Posterior Predictive Distribution ◽  
Coalescent Model ◽  
Multispecies Coalescent ◽  
Phylogenetic Estimation

Phylogenetic estimation under the multispecies coalescent model (MSCM) assumes all incongruence among loci is caused by incomplete lineage sorting. Therefore, applying the MSCM to datasets that contain incongruence that is caused by other processes, such as gene flow, can lead to biased phylogeny estimates. To identify possible bias when using the MSCM, we present P2C2M.SNAPP. P2C2M.SNAPP is an R package that identifies model violations using posterior predictive simulation. P2C2M.SNAPP uses the posterior distribution of species trees output by the software package SNAPP to simulate posterior predictive datasets under the MSCM, and then uses summary statistics to compare either the empirical data or the posterior distribution to the posterior predictive distribution to identify model violations. In simulation testing, P2C2M.SNAPP correctly classified up to 83% of datasets (depending on the summary statistic used) as to whether or not they violated the MSCM model. P2C2M.SNAPP represents a user-friendly way for researchers to perform posterior predictive model checks when using the popular SNAPP phylogenetic estimation program. It is freely available as an R package, along with additional program details and tutorials.

scholarly journals A Simulation Study to Examine the Information Content in Phylogenomic Data Sets under the Multispecies Coalescent Model

2020 ◽  
Vol 37 (11) ◽  
pp. 3211-3224
Author(s):  
Jun Huang ◽  
Tomáš Flouri ◽  
Ziheng Yang
Keyword(s):  
Information Content ◽  
Mutation Rate ◽  
Species Delimitation ◽  
Species Tree ◽  
Data Sets ◽  
Site Mutation ◽  
Coalescent Model ◽  
Inference Problems ◽  
Multispecies Coalescent ◽  
Tree Estimation

Abstract We use computer simulation to examine the information content in multilocus data sets for inference under the multispecies coalescent model. Inference problems considered include estimation of evolutionary parameters (such as species divergence times, population sizes, and cross-species introgression probabilities), species tree estimation, and species delimitation based on Bayesian comparison of delimitation models. We found that the number of loci is the most influential factor for almost all inference problems examined. Although the number of sequences per species does not appear to be important to species tree estimation, it is very influential to species delimitation. Increasing the number of sites and the per-site mutation rate both increase the mutation rate for the whole locus and these have the same effect on estimation of parameters, but the sequence length has a greater effect than the per-site mutation rate for species tree estimation. We discuss the computational costs when the data size increases and provide guidelines concerning the subsampling of genomic data to enable the application of full-likelihood methods of inference.

scholarly journals A Taxonomic Investigation into the Red Alga Plocamium within New Zealand

2021 ◽  
Author(s):  
◽  
Madeline Wynn Cooper
Keyword(s):  
New Zealand ◽  
Species Delimitation ◽  
Phylogenetic Analyses ◽  
Evolutionary Relationship ◽  
Red Alga ◽  
Morphometric Analyses ◽  
True Diversity ◽  
Candidate Species ◽  
Bayesian Implementation ◽  
Genetic Species

<p>The red alga Plocamium is a cosmopolitan genus, known for its distinct branching pattern and rich chemical composition. Recent studies indicate morphological-based species delimitation approaches have failed to accurately discern diversity, distributions, and evolutionary relationship between species worldwide. Currently there are seven recognized species within New Zealand based on traditional morphological approaches and no molecular based work focused on discerning true diversity of New Zealand species in this genus. This thesis is the first to use molecular-assisted alpha taxonomy to investigate Plocamium within New Zealand. Phylogenetic analyses (Maximum Likelihood and Bayesian Inference) based on COI, rbcL, LSU and combined LSU/COI markers, three molecular species delimitation methods (Automatic Barcode Gap Discovery, General Mixed Yule Coalescent, and Bayesian implementation of the Poisson Tree Processes), and morphometric analyses of various characters (width of main axis (WMA), width of lowest basal ramuli (WLBR), length of lowest basal ramuli (LLBR), number of alternating series of ramuli (NASR), average number of ramuli per alternating series (ANRAS), curvature of basal ramuli (CBR) and serrations present or absent from basal ramuli (SERBR) were used to address this topic. The species delimitation methods revealed at least eleven (A-K) putative genetic species (with some incongruences) within the New Zealand specimens included in the study. Morphometric analyses indicated morphology reflects genetic diversity when multiple measures of multiple characters are used, however this is not the case when considering single characters. Phylogenetic analyses revealed possible monophyly of New Zealand candidate species C-K, and possible relationships to Australian, Chilean, and Taiwanese species. However these backbone relationships were poorly supported. The results of this study indicate that Plocamium diversity within New Zealand has been underestimated and provide the first steps in discovering the true species diversity of Plocamium within New Zealand.</p>

scholarly journals Sampling Error Does Not Invalidate the Yule-Coalescent Model for Species Delimitation. A Response to Lohse (2009)

2009 ◽  
Vol 58 (4) ◽  
pp. 442-444 ◽  
Author(s):  
Anna Papadopoulou ◽  
Michael T. Monaghan ◽  
Timothy G. Barraclough ◽  
Alfried P. Vogler
Keyword(s):  
Species Delimitation ◽  
Sampling Error ◽  
Coalescent Model

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

Influence of Channel Estimation Error on MIMO Multiplexing Using Precoding in Downlink OFDM Radio Access

2009 ◽  
Vol E92-B (5) ◽  
pp. 1553-1562
Author(s):  
Takashi ISOGAI ◽  
Mamoru SAWAHASHI ◽  
Hidekazu TAOKA ◽  
Kenichi HIGUCHI
Keyword(s):  
Channel Estimation ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Radio Access
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