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NGPhylogeny.fr

PhyML 3.1

phylip/fasta format

Empirical: frequencies are estimated by counting the occurences in the alignment. ML/Model:frequencies are estimated using ML for nucleotides or defined by the proteic substitution model.

Must be a positive integer, 'e' if you want PhyML to estimate it

Empirical: frequencies are estimated by counting the occurences in the alignment. ML/Model:frequencies are estimated using ML for nucleotides or defined by the proteic substitution model.

Empirical: frequencies are estimated by counting the occurences in the alignment. ML/Model:frequencies are estimated using ML for nucleotides or defined by the proteic substitution model.

Empirical: frequencies are estimated by counting the occurences in the alignment. ML/Model:frequencies are estimated using ML for nucleotides or defined by the proteic substitution model.

Can be a fixed value in the [0,1] range or 'e' to get the maximum likelihood estimate, 0 to ignore this parameter

1 means no gamma model

'e' if you want PhyML to estimate it

Use aLRT or aBayes to save computing time

Must be a positive integer

0 to random seed

newick format


References

  • Guindon, S. and Dufayard, J. F. and Lefort, V. and Anisimova, M. and Hordijk, W. and Gascuel, O.(2010). New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0 . Systematic Biology doi