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NGPhylogeny.fr

Workflow Advanced Setting

PhyML/OneClick

Workflow skeleton

Input data
Fasta format
Multiple Alignment
MAFFT
Multiple alignment program for amino acid or nucleotide sequences
Alignment Curation
BMGE
cleaning aligned sequences
Tree Inference
PhyML
Phylogeny software based on the maximum-likelihood
Tree Rendering
Newick Display
Display a phylogenetic tree as SVG

Configure your workflow

Input data

Choose a file or Paste content
(Fasta format with more than 3 sequences)
Blast runs Files in session

Run mafft with pre-defined input parameters. Specification of these parameters can be found in the help section.

Distance method must be chosen regarding your data

Valid with 6mer distance

1000 for maximum quality

Offset value, which works like gap extension penalty, for group-to-group alignment. For E-INS-i, 0 is recommended to allow large gaps

1.53 default value

Generate reverse complement sequences, as necessary, and align them together with the remaining sequences

Usefull only for amino acids

sliding window size (must be odd; ranges from 1 to alignment length; if set to 1, then entropy-like values are not smoothed; default: 3)

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.

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