ML_TREE

Calculating the maximum likelihood tree from a multiple sequence alignment is easy, and only requires nexus files containing the taxa and sequences.

Currently, there is only support for DNA, but SNP, Bimarkers, and other data types are in the works.

                        from PhyNetPy.tools import ML_TREE
                        from PhyNetPy.GTR import *

                        filenames = ["file1.nex", "file2.nex"] 
                        log_output = "out.txt"
                        tree_output = "ml_tree.tree"
                        

                        # Default, with substitution model JC() and number of iterations = 3000
                        likelihoods_1 = ML_TREE(filenames, tree_output, log_output)

                        # num_iter keyword set
                        likelihoods_2 = ML_TREE(filenames, tree_output, log_output, num_iter=5000)

                        # submodel keyword set
                        likelihoods_3 = ML_TREE(filenames, tree_output, log_output, submodel=K2P(.4, .6))


                

Here is a sample nexus file:

                        #NEXUS

                        BEGIN TAXA;

                        DIMENSIONS NTAX=4;

                        TAXLABELS
                        seq_1
                        seq_2
                        seq_3
                        seq_4
                        ;

                        END;

                        BEGIN CHARACTERS;
                        DIMENSIONS NCHAR=5;
                        FORMAT DATATYPE=DNA MISSING=? GAP=- MATCHCHAR=. ;
                        MATRIX

                        seq_1 GACCC

                        seq_2 GACCG

                        seq_3 CACCT

                        seq_4 CACCC
                        ;

                        END;