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It is only the "best" tree based on classifier performance.
Computing phylogenies requires two main components for more than three genomes: scoring a given tree, and searching for the best tree based on their scores.
This hypothesis is supported by the fact that selecting the best tree based on the quartet support produced improved topological accuracy compared to selecting the best tree based on the pseudo-likelihood score, and that the quartet support optimization criterion is statistically consistent under the multi-species coalescent model [ 25].
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These results are congruent with the two best trees based on inversion medians that we recently inferred from streptophyte gene order data using Mesostigma as outgroup [ 8].
The overall topology of the best Bayesian tree based on the lower-scored SATé alignment was quite different from the one produced by the best-scored alignment, and all of the reference lineages, except for the Orbiliomycetes, were scattered over more than one clade each (Figure S1).
The best ML tree based on RY coding of the nuclear partition is similar to the ML tree using standard nucleotide coding.
BiSSE and GeoSSE model assumptions were satisfied through the use of the best rooted tree based on the dated ITS and multi-gene phylogenies: i) rooted phylogenetic tree with branch lengths; ii) contemporaneous terminal taxa and; iii) ultrametric tree [ 81].
PAUP* was then used to search for the maximum likelihood (ML) tree, based on the best fit model and parameter estimates given by ModelTest (Table 1) and using a heuristic search with tree bisection reconnection (TBR).
When we applied the divergence time of approximately 0.5 Mya for the C. cuvieri lineage to the NPRS ultrametric tree based on the best ML tree derived from the concatenated sequence data set, the divergence time between superclades A and B was estimated to be about 0.4 Mya (Table 4).
a Phylogram and radial tree layout of the ML tree based on a best-fit model (SYM + G).
Figure 1 Simplified phylogenetic tree based on the best-scoring maximum likelihood phylogram of Chung et al. ([2014]).
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