PMC0
10.1093%2Fbioinformatics%2Fbtq706
methods
The phangorn package interacts with several other R-packages, especially with the ape package (Paradis et al., >>2004<<). From ape, phangorn inherits the tree format (class phylo which has become a standard), which allows use of the excellent plotting facilities within ape.
The speed and accuracy of phylogenetic reconstruction by ML are comparable to PhyML (Guindon and Gascuel, >>2003<<) using nearest neighbor interchange (NNI) rearrangements (see Supplementary Materials).
1) a phylogenetic tree based on the data of Rokas et al., >>2003<< using a GTR + Γ(4) + I model (Kelchner and Thomas, 2007):
1) a phylogenetic tree based on the data of Rokas et al., 2003 using a GTR + Γ(4) + I model (Kelchner and Thomas, >>2007<<): Fig. 1.
phylogenetic tree with bootstrap support on the edges for the data of Rokas et al., >>2003<<.
For nucleotide data all models implemented in ModelTest (Posada, >>2008<<) are available (e.g. “JC” or “GTR”). Moreover any reversible model can be specified by the user for different character states.
For amino acids, the main common rate matrices are provided, e.g. WAG (Whelan and Goldman, >>2001<<) or LG (Le and Gascuel, 2008).
For amino acids, the main common rate matrices are provided, e.g. WAG (Whelan and Goldman, 2001) or LG (Le and Gascuel, >>2008<<). Additionally rate matrices can also be estimated. For instance Mathews et al., 2010 used the function optim.pml to infer a phytochrome amino acid transition matrix. There are several methods implemented to compare different ML models
For instance Mathews et al., >>2010<< used the function optim.pml to infer a phytochrome amino acid transition matrix.
phangorn also contains mixture models (Pagel and Meade, >>2004<<) and partition models.
These spectra can be visualized using a Lento plot (Lento et al., >>1995<<) to present the supporting and conflicting signals for the splits of a dataset (Fig.
Splits can easily be exported to SpectroNet (Huber et al., >>2002<<) or Splitsgraph (Huson and Bryant, 2006) and visualized as a network.
Splits can easily be exported to SpectroNet (Huber et al., 2002) or Splitsgraph (Huson and Bryant, >>2006<<) and visualized as a network.
Lento plot of the edge weights from sequence spectrum for the data of Rokas et al., >>2003<<. On the x-axis the splits or edges are represented by the dots overlying the graph.
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