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align.py
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align.py
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import numpy as np
import pandas as pd
def align_global(seqi, seqii, match, mismatch, open_gap, gap):
ni = len(seqi)
nii = len(seqii)
# initialization of NW matrix
M = np.zeros((ni + 1, nii + 1))
M[0, 1] += open_gap
M[1, 0] += open_gap
M[1:, 0] = np.linspace(-2, -2 + (ni - 1) * gap, ni)
M[0, 1:] = np.linspace(-2, -2 + (nii - 1) * gap, nii)
# Compute the NeeW matrix
for i in range(1, ni + 1):
for j in range(1, nii + 1):
diag = M[i - 1, j - 1]
ver = M[i - 1, j]
hor = M[i, j - 1]
diag += match if (seqi[i - 1] == seqii[j - 1]) else mismatch
ver += open_gap if (i == 1) else gap
hor += open_gap if (j == 1) else gap
M[i, j] = max([diag, ver, hor])
# Find the optimal alignment
al_seqi = []
al_seqii = []
al_seqi.append(seqi[-1])
al_seqii.append(seqii[-1])
i = ni - 1
j = nii - 1
while i > 0 and j > 0:
diag = M[i - 1, j - 1]
ver = M[i - 1, j]
hor = M[i, j - 1]
if diag >= ver and diag >= hor:
i -= 1
j -= 1
al_seqi.append(seqi[i])
al_seqii.append(seqii[j])
elif hor > diag and hor > ver:
j -= 1
al_seqii.append(seqii[j])
al_seqi.append('-')
elif ver > diag and ver > hor:
i -= 1
al_seqi.append(seqi[i])
al_seqii.append('-')
al_seqi = ''.join(al_seqi)[::-1]
al_seqii = ''.join(al_seqii)[::-1]
return [al_seqi, al_seqii]
def align_local(seqi, seqii, match, mismatch, open_gap, gap):
ni = len(seqi)
nii = len(seqii)
# Initialize the Smith-Waterman matrix
M = np.zeros((ni + 1, nii + 1))
# Compute the Smith-Waterman matrix
for i in range(1, ni + 1):
for j in range(1, nii + 1):
diag = M[i - 1, j - 1]
ver = M[i - 1, j]
hor = M[i, j - 1]
diag += match if (seqi[i - 1] == seqii[j - 1]) else mismatch
ver += open_gap if (i == 1) else gap
hor += open_gap if (j == 1) else gap
M[i, j] = max([diag, ver, hor, 0])
# Find the optimal local alignment
i, j = np.unravel_index(M.argmax(), M.shape)
al_seqi = []
al_seqii = []
while i > 0 and j > 0 and M[i, j] > 0:
diag = M[i - 1, j - 1]
ver = M[i - 1, j]
hor = M[i, j - 1]
if diag >= ver and diag >= hor:
i -= 1
j -= 1
al_seqi.append(seqi[i])
al_seqii.append(seqii[j])
elif hor > diag and hor > ver:
j -= 1
al_seqii.append(seqii[j])
al_seqi.append('-')
elif ver > diag and ver > hor:
i -= 1
al_seqi.append(seqi[i])
al_seqii.append('-')
al_seqi = ''.join(al_seqi)[::-1]
al_seqii = ''.join(al_seqii)[::-1]
return [al_seqi, al_seqii]
def align(seqi, seqii, alignment_type = 'global', match = 2, mismatch = -1, open_gap = -2, gap = -1):
seqi = np.array(list(seqi))
seqii = np.array(list(seqii))
# substitution matrix
# matrix = [[2, -6, -6, -6], [-6, 2, -6, -6],
# [-6, -6, 2, -6], [-6, -6, -6, 2]]
if alignment_type == 'local':
return align_local(seqi, seqii, match, mismatch, open_gap, gap)
elif alignment_type == 'global':
return align_global(seqi, seqii, match, mismatch, open_gap, gap)
else:
raise ValueError('Invalid alignment type: {}'.format(alignment_type))
# seq1 = 'CACACAGTGACTAGCTAGCTACGATC'
# seq2 = 'CACACAGTCGACTAGCTAGCACGATC'
seq1 = 'ACTACTAGATTACTTACGGATCAGGTACTTTAGAGGCTTGCAACCA'
seq2 = 'TACTCACGGATGAGGTACTTTAGAGGC'
seq3 = 'ACTACTAGATTACGGATCGTACTTTAGAGGCTAGCAACCA'
print(*align(seq1, seq2, 'local'), sep='\n')