2017
DOI: 10.1016/j.jtbi.2016.11.005
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Species tree estimation using Neighbor Joining

Abstract: Recent theoretical work has demonstrated that Neighbor Joining applied to concatenated DNA sequences is a statistically consistent method of species tree reconstruction. This brief note compares the accuracy of this approach to other popular statistically consistent species tree reconstruction algorithms including ASTRAL-II Neighbor Joining using average gene-tree internode distances (NJst) and SVD-Quartets+PAUP*, as well as concatenation using maximum likelihood (RaxML). We find that the faster Neighbor Joini… Show more

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Cited by 23 publications
(19 citation statements)
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“…These included three multispecies coalescent methods34,35: the Bayesian SNAPP36 (with a subset of 48,922 unlinked SNPs in 12 individuals representing the eco-morphological groups), the algebraic method SVDquartets37,38, which allows for site-specific rate variation and is robust to gene-flow between sister taxa39, and the summary method ASTRAL40,41, using the 2543 local ML trees that were described above as input. We also built a whole genome Neighbour-Joining (NJ) tree using the Dasarathy et al algorithm, which has been shown to be a statistically consistent and accurate species tree estimator under ILS42,43. The above methods have also been applied to datasets where the individuals that are genetically intermediate between eco-morphological groups ( C. trimaculatus , A. stuartgranti , and A. steveni ) have been removed, thus likely reducing the extent of violation of the multispecies coalescent model.…”
Section: Resultsmentioning
confidence: 99%
“…These included three multispecies coalescent methods34,35: the Bayesian SNAPP36 (with a subset of 48,922 unlinked SNPs in 12 individuals representing the eco-morphological groups), the algebraic method SVDquartets37,38, which allows for site-specific rate variation and is robust to gene-flow between sister taxa39, and the summary method ASTRAL40,41, using the 2543 local ML trees that were described above as input. We also built a whole genome Neighbour-Joining (NJ) tree using the Dasarathy et al algorithm, which has been shown to be a statistically consistent and accurate species tree estimator under ILS42,43. The above methods have also been applied to datasets where the individuals that are genetically intermediate between eco-morphological groups ( C. trimaculatus , A. stuartgranti , and A. steveni ) have been removed, thus likely reducing the extent of violation of the multispecies coalescent model.…”
Section: Resultsmentioning
confidence: 99%
“…These included three multispecies coalescent methods 36,37 : the Bayesian SNAPP 38 (with a subset of 48,922 unlinked SNPs in 12 individuals representing the eco-morphological groups), the algebraic method SVDquartets 39,40 , which allows for site-specific rate variation and is robust gene-flow between sister taxa 41 , and the summary method ASTRAL 42,43 , using the 2543 local ML trees that were described above as input. We also built whole genome Neighbour-Joining (NJ) tree using the Dasarathy et al algorithm, which has been shown to be a statistically consistent and accurate species tree estimator under ILS 44,45 It is also clear that the mtDNA phylogeny is an outlier, being substantially different from all the whole-genome phylogenies and also from the majority of the local ML trees (Fig. 2b,c and…”
Section: Phylogenetic Framework Relationshipsmentioning
confidence: 99%
“…Summary coalescent-based methods have, however, been criticized for placing unrealistic confidence in gene tree estimation, and concerns have been raised regarding their performance when the accuracy of inferred gene trees varies (Springer and Gatesy 2016). In some circumstances, such as poor phylogenetic signal or low ILS and high gene tree estimation error, concatenation can provide as good or even better species-tree estimates Liu et al 2015a;Rusinko and McPartlon 2017;Molloy and Warnow 2018). Full coalescent methods on the other hand, can overcome these problems by simultaneously estimating gene and species trees and taking into account their uncertainty under a Bayesian framework (Knowles et al 2012).…”
mentioning
confidence: 99%