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#This software is a free software. Thus, it is licensed under GNU General Public License.
#Python implementation to Smith-Waterman Algorithm for Homework 1 of Bioinformatics class.
#Forrest Bao, Sept. 26 <http://fsbao.net> <forrest.bao aT gmail.com>
# zeros() was origianlly from NumPy.
# This version is implemented by alevchuk 2011-04-10
def zeros(shape):
retval = []
for x in range(shape[0]):
retval.append([])
for y in range(shape[1]):
retval[-1].append(0)
return retval
match_award = 10
mismatch_penalty = -5
gap_penalty = -5 # both for opening and extanding
def match_score(alpha, beta, gap_symbol = "-"):
if alpha == beta:
return match_award
elif alpha == gap_symbol or beta == gap_symbol:
return gap_penalty
else:
return mismatch_penalty
def finalize(align1, align2, gap_symbol = "-"):
align1 = align1[::-1] #reverse sequence 1
align2 = align2[::-1] #reverse sequence 2
i,j = 0,0
#calcuate identity, score and aligned sequeces
symbol = ''
for i in range(0,len(align1)):
# if two AAs are the same, then output the letter
if align1[i] == align2[i]:
symbol = symbol + align1[i]
# if they are not identical and none of them is gap
elif align1[i] != align2[i] and align1[i] != gap_symbol and align2[i] != gap_symbol:
symbol += ' '
found = 0
#if one of them is a gap, output a space
elif align1[i] == gap_symbol or align2[i] == gap_symbol:
symbol += ' '
return align1, align2
def needle(seq1, seq2, gap_symbol = "-"):
m, n = len(seq1), len(seq2) # length of two sequences
# Generate DP table and traceback path pointer matrix
score = zeros((m+1, n+1)) # the DP table
# Calculate DP table
for i in range(0, m + 1):
score[i][0] = gap_penalty * i
for j in range(0, n + 1):
score[0][j] = gap_penalty * j
for i in range(1, m + 1):
for j in range(1, n + 1):
match = score[i - 1][j - 1] + match_score(seq1[i-1], seq2[j-1])
delete = score[i - 1][j] + gap_penalty
insert = score[i][j - 1] + gap_penalty
score[i][j] = max(match, delete, insert)
# Traceback and compute the alignment
align1, align2 = '', ''
i,j = m,n # start from the bottom right cell
while i > 0 and j > 0: # end toching the top or the left edge
score_current = score[i][j]
score_diagonal = score[i-1][j-1]
score_up = score[i][j-1]
score_left = score[i-1][j]
if score_current == score_diagonal + match_score(seq1[i-1], seq2[j-1]):
align1 += seq1[i-1]
align2 += seq2[j-1]
i -= 1
j -= 1
elif score_current == score_left + gap_penalty:
align1 += seq1[i-1]
align2 += gap_symbol
i -= 1
elif score_current == score_up + gap_penalty:
align1 += gap_symbol
align2 += seq2[j-1]
j -= 1
# Finish tracing up to the top left cell
while i > 0:
align1 += seq1[i-1]
align2 += gap_symbol
i -= 1
while j > 0:
align1 += gap_symbol
align2 += seq2[j-1]
j -= 1
return finalize(align1, align2) |