tree_generator.py

# -*- coding: utf-8 -*-
"""
Created on Tue Jan 29 14:59:19 2019

@author: Amaury Leroy
"""

import numpy as np
from Bio.SeqRecord import SeqRecord
from Bio.Cluster import treecluster
import alignementseq
from scipy.cluster.hierarchy import average, dendrogram

#seqs = [SeqRecord('TAACCCCAAAAGAACCAGA'), SeqRecord('TTCTGTAGTAGAGATGGAATTAAGAAAAAACCATCAACTATAACCCCAAAAGAACCAGA'), SeqRecord('TTCTGTAGTAGAGATGGAATTAAGAAAAAACCATCAACTATAACCCCAAAAGAACCAGA'),SeqRecord('GTAGTAGAGATGGAATTAAGAAAAAACCATCAACTATAACCCCAAGAGAACCAGA'), SeqRecord('GAGCCGGATGAGAAGAAACTCTCATGTCCGGTTCTGTAGTAGAGATGGAATTAAGAAAAAACCATCAACTATAACCCCAAGAGAACCAGA'), SeqRecord('TTTTCATTCGCGAGGAGCCGGATGAGAAGAAACTCTCATGTCCGGTTCTGTAGTAGAGATGGAATTAAGAAAAAACCATCAACTATAACCCCAAGAGAACCAGA')]

#Arguments : une liste de séquences, une fonction d'alignement
score_gap = -8
def tree_build(seqs, align):
    len_seqs= [len(seq) for seq in seqs]
    M = np.zeros((len(seqs),len(seqs))) 
    for i in range (len(seqs)):
        for j in range (i):
            M[i][j], a, b = align(seqs[i], seqs[j])
            M[i][j] = 1-abs(M[i][j]/(max(len_seqs)*(11-score_gap)))
#    print(type(M), M)
#    tree = treecluster(None, distancematrix=M, method = 'a', dist = 'e',)
    tree= average(M)
    return tree


#tree = tree_build(seqs, alignementseq.align2steps)
#print(tree)
#dn = dendrogram(tree)