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. 2019 Jul 24;11(8):679. doi: 10.3390/v11080679

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© 2019 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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Ancestral geographical reconstructions based on phylogenetic trees obtained by the Bayesian method (Beast program) (A) and ML methods, F81 algorithms, (PastView program) (B) from the complete coding sequence of the S segment. The red arrows point the nodes in disagreement between Bayesian and ML methods. Tree-like representations of transitions were computed with BEAST (C), PastView (D), and PastML (E) programs. For (C) and (D), transition maps are summarized with PastView program and numbers indicate the counts of identical transitions having the same ancestor. For (E), transition map is done by PastML program and circle diameters are proportional to the number of tips of the initial tree contained in each cluster. Consensus transitions between the three programs are highlighted in blue, red, and green.

Ancestral geographical reconstructions based on phylogenetic trees obtained by the Bayesian method (Beast program) (A) and ML methods, F81 algorithms, (PastView program) (B) from the complete coding sequence of the S segment. The red arrows point the nodes in disagreement between Bayesian and ML methods. Tree-like representations of transitions were computed with BEAST (C), PastView (D), and PastML (E) programs. For (C) and (D), transition maps are summarized with PastView program and numbers indicate the counts of identical transitions having the same ancestor. For (E), transition map is done by PastML program and circle diameters are proportional to the number of tips of the initial tree contained in each cluster. Consensus transitions between the three programs are highlighted in blue, red, and green.