def test_align_pairwise(self):
"""Test the Needleman-Wunsch sequence alignment for two protein sequences.
This uses the sequences:
- 'IHAAEEKDWKTAYSYbgFYEAFEGYdsidspkaitslkymllckimlntpedvqalvsgkla',
- 'LHAADEKDFKTAFSYabiggapFYEAFEGYdsvdekvsaltalkymllckvmldlpdevnsllsakl'.
From online servers, the results with a gap open penalty of 5 and gap extend of 1 should be::
https://www.ebi.ac.uk/Tools/psa/emboss_needle/
EMBOSS_001 IHAAEEKDWKTAYSY-B-G---FYEAFEGYDSIDSP-KAITSLKYMLLCKIMLNTPEDVQALVSGKLA
:|||:|||:|||:|| | | ||||||||||:|.. .|:|:||||||||:||:.|::|.:|:|.||
EMBOSS_001 LHAADEKDFKTAFSYABIGGAPFYEAFEGYDSVDEKVSALTALKYMLLCKVMLDLPDEVNSLLSAKL-
http://web.expasy.org/cgi-bin/sim/sim.pl?prot
UserSeq1 IHAAEEKDWKTAYSY-B-G---FYEAFEGYDSIDSP-KAITSLKYMLLCKIMLNTPEDVQALVSGKL
UserSeq2 LHAADEKDFKTAFSYABIGGAPFYEAFEGYDSVDEKVSALTALKYMLLCKVMLDLPDEVNSLLSAKL
*** *** *** ** * * ********** * * * ******** ** * * * * **
"""
# The sequences.
seq1 = 'IHAAEEKDWKTAYSYbgFYEAFEGYdsidspkaitslkymllckimlntpedvqalvsgkla'
seq2 = 'LHAADEKDFKTAFSYabiggapFYEAFEGYdsvdekvsaltalkymllckvmldlpdevnsllsakl'
print(seq1)
print(seq2)
# Perform the alignment.
score, align1, align2, gaps = align_pairwise(seq1,
seq2,
matrix='BLOSUM62',
gap_open_penalty=5.0,
gap_extend_penalty=1.0)
print(score)
print(align1)
print(align2)
print(gaps)
# Check the alignment.
self.assertEqual(
align1,
'IHAAEEKDWKTAYSY-B-G---FYEAFEGYDSIDSP-KAITSLKYMLLCKIMLNTPEDVQALVSGKLA'
)
self.assertEqual(
align2,
'LHAADEKDFKTAFSYABIGGAPFYEAFEGYDSVDEKVSALTALKYMLLCKVMLDLPDEVNSLLSAKL-'
)
# The gap matrix.
real_gaps = zeros((2, 68), int16)
real_gaps[0, 15] = 1
real_gaps[0, 17] = 1
real_gaps[0, 19] = 1
real_gaps[0, 20] = 1
real_gaps[0, 21] = 1
real_gaps[0, 36] = 1
real_gaps[1, 67] = 1
for i in range(2):
for j in range(68):
self.assertEqual(gaps[i, j], real_gaps[i][j])
def test_align_pairwise_PAM250(self):
"""Test the Needleman-Wunsch sequence alignment for two protein sequences using the PAM250 substitution matrix.
This uses the sequences:
- 'IHAAEEKDWKTAYSYbgFYEAFEGYdsidspkaitslkymllckimlntpedvqalvsgkla',
- 'LHAADEKDFKTAFSYabiggapFYEAFEGYdsvdekvsaltalkymllckvmldlpdevnsllsakl'.
From online servers, the results with a gap open penalty of 5 and gap extend of 0.5 should be::
https://www.ebi.ac.uk/Tools/psa/emboss_needle/
EMBOSS_001 IHAAEEKDWKTAYSYb--g---FYEAFEGYdsidspk--aitslkymllckimlntpedvqalvsgkla
:|||:|||.|||:||. | ||||||||||:|. | |:|:||||||||:||:.|::|::|:|:||
EMBOSS_001 LHAADEKDFKTAFSYabiggapFYEAFEGYdsvde-kvsaltalkymllckvmldlpdevnsllsakl-
http://web.expasy.org/cgi-bin/sim/sim.pl?prot
UserSeq1 IHAAEEKDWKTAYSYBG-----FYEAFEGYDSIDSPK--AITSLKYMLLCKIMLNTPEDVQALVSGKL
UserSeq2 LHAADEKDFKTAFSYABIGGAPFYEAFEGYDSVDE-KVSALTALKYMLLCKVMLDLPDEVNSLLSAKL
*** *** *** ** ********** * * * * ******** ** * * * * **
"""
# The sequences.
seq1 = 'IHAAEEKDWKTAYSYbgFYEAFEGYdsidspkaitslkymllckimlntpedvqalvsgkla'
seq2 = 'LHAADEKDFKTAFSYabiggapFYEAFEGYdsvdekvsaltalkymllckvmldlpdevnsllsakl'
print(seq1)
print(seq2)
# Perform the alignment.
score, align1, align2, gaps = align_pairwise(seq1, seq2, matrix='PAM250', gap_open_penalty=5.0, gap_extend_penalty=0.5)
print(score)
print(align1)
print(align2)
print(gaps)
# Check the alignment.
self.assertEqual(align1, 'IHAAEEKDWKTAYSYB--G---FYEAFEGYDSIDSPK--AITSLKYMLLCKIMLNTPEDVQALVSGKLA')
self.assertEqual(align2, 'LHAADEKDFKTAFSYABIGGAPFYEAFEGYDSVDE-KVSALTALKYMLLCKVMLDLPDEVNSLLSAKL-')
# The gap matrix.
real_gaps = zeros((2, 69), int16)
real_gaps[0, 16] = 1
real_gaps[0, 17] = 1
real_gaps[0, 19] = 1
real_gaps[0, 20] = 1
real_gaps[0, 21] = 1
real_gaps[0, 37] = 1
real_gaps[0, 38] = 1
real_gaps[1, 35] = 1
real_gaps[1, 68] = 1
for i in range(2):
for j in range(68):
self.assertEqual(gaps[i, j], real_gaps[i][j])
def central_star(sequences, algorithm='NW70', matrix='BLOSUM62', gap_open_penalty=1.0, gap_extend_penalty=1.0, end_gap_open_penalty=0.0, end_gap_extend_penalty=0.0):
"""Align multiple protein sequences to one reference by fusing multiple pairwise alignments.
@param sequences: The list of residue sequences as one letter codes.
@type sequences: list of str
@keyword algorithm: The pairwise sequence alignment algorithm to use.
@type algorithm: str
@keyword matrix: The substitution matrix to use.
@type matrix: str
@keyword gap_open_penalty: The penalty for introducing gaps, as a positive number.
@type gap_open_penalty: float
@keyword gap_extend_penalty: The penalty for extending a gap, as a positive number.
@type gap_extend_penalty: float
@keyword end_gap_open_penalty: The optional penalty for opening a gap at the end of a sequence.
@type end_gap_open_penalty: float
@keyword end_gap_extend_penalty: The optional penalty for extending a gap at the end of a sequence.
@type end_gap_extend_penalty: float
@return: The list of alignment strings and the gap matrix.
@rtype: list of str, numpy rank-2 int array
"""
# Initialise.
N = len(sequences)
scores = zeros((N, N), float64)
# Set up lists of lists for storing all alignment strings.
align1_matrix = []
align2_matrix = []
for i in range(N):
align1_matrix.append([])
align2_matrix.append([])
for j in range(N):
if i == j:
align1_matrix[i].append(sequences[i])
align2_matrix[i].append(sequences[i])
else:
align1_matrix[i].append(None)
align2_matrix[i].append(None)
# Printout.
sys.stdout.write("\nCentral Star multiple sequence alignment.\n\n")
sys.stdout.write("%-30s %s\n" % ("Pairwise algorithm:", algorithm))
sys.stdout.write("%-30s %s\n" % ("Substitution matrix:", matrix))
sys.stdout.write("%-30s %s\n" % ("Gap opening penalty:", gap_open_penalty))
sys.stdout.write("%-30s %s\n" % ("Gap extend penalty:", gap_extend_penalty))
sys.stdout.write("Initial sequences:\n")
for i in range(N):
sys.stdout.write("%3i %s\n" % (i+1, sequences[i]))
# All pairwise alignments.
sys.stdout.write("\nDetermining the scores for all pairwise alignments:\n")
for i in range(N):
for j in range(i+1, N):
# Align the pair.
sys.stdout.write("%-30s " % ("Sequences %i-%i:" % (i+1, j+1)))
score, align1, align2, gaps = align_pairwise(sequences[i], sequences[j], algorithm=algorithm, matrix=matrix, gap_open_penalty=gap_open_penalty, gap_extend_penalty=gap_extend_penalty, end_gap_open_penalty=end_gap_open_penalty, end_gap_extend_penalty=end_gap_extend_penalty, verbosity=0)
sys.stdout.write("%10.1f\n" % score)
# Store the score and alignment strings.
scores[i, j] = scores[j, i] = score
align1_matrix[i][j] = align1_matrix[j][i] = align1
align2_matrix[i][j] = align2_matrix[j][i] = align2
# The central sequence.
sys.stdout.write("\nDetermining the central sequence:\n")
sum_scores = scores.sum(0)
Sc_sum_score = 1e100
Sc_index = 0
for i in range(N):
if sum_scores[i] < Sc_sum_score:
Sc_sum_score = sum_scores[i]
Sc_index = i
sys.stdout.write("%-30s %10.1f\n" % (("Sum of scores, sequence %i:" % (i+1)), sum_scores[i]))
sys.stdout.write("%-30s %i\n" % ("Central sequence:", Sc_index+1))
# Partition the sequences.
Sc = sequences[Sc_index]
Si = []
for i in range(N):
if i != Sc_index:
Si.append(sequences[i])
# Optimal alignments.
sys.stdout.write("\nDetermining the iterative optimal alignments:\n")
Sc_prime = Sc
string_lists = []
for i in range(N-1):
# Update the string lists.
string_lists.append([])
# Perform the pairwise alignment between Sc' and Si, replacing all '-' with 'X'.
score, Sc_prime, Si_prime, gaps = align_pairwise(Sc_prime.replace('-', 'X'), Si[i].replace('-', 'X'), algorithm=algorithm, matrix=matrix, gap_open_penalty=gap_open_penalty, gap_extend_penalty=gap_extend_penalty, end_gap_open_penalty=end_gap_open_penalty, end_gap_extend_penalty=end_gap_extend_penalty, verbosity=0)
sys.stdout.write("\n%-30s %s\n" % ("Sequence Sc':", Sc_prime.replace('X', '-')))
sys.stdout.write("%-30s %s\n" % (("Sequence S%i':" % (i+1)), Si_prime.replace('X', '-')))
# Store the Si alignment.
for j in range(len(Sc_prime)):
string_lists[i].append(Si_prime[j])
# Add spaces to the lists for all previous alignments.
else:
# Find gaps in the central sequence.
for j in range(len(Sc_prime)):
if Sc_prime[j] == '-':
# Pad the previous alignments.
for k in range(0, i):
string_lists[k].insert(j, '-')
# Rebuild the alignment lists and create a gap matrix.
strings = []
M = len(Sc_prime)
strings.append(Sc_prime)
for i in range(N-1):
strings.append(''.join(string_lists[i]))
for i in range(N):
strings[i] = strings[i].replace('X', '-')
# Restore the original sequence ordering.
string = strings.pop(0)
strings.insert(Sc_index, string)
# Create the gap matrix.
gaps = zeros((N, M), int16)
for i in range(N):
for j in range(M):
if strings[i][j] == '-':
gaps[i, j] = 1
# Final printout.
sys.stdout.write("\nFinal MSA:\n")
for i in range(N):
sys.stdout.write("%3i %s\n" % (i+1, strings[i]))
# Return the results.
return strings, gaps
def central_star(sequences,
algorithm='NW70',
matrix='BLOSUM62',
gap_open_penalty=1.0,
gap_extend_penalty=1.0,
end_gap_open_penalty=0.0,
end_gap_extend_penalty=0.0):
"""Align multiple protein sequences to one reference by fusing multiple pairwise alignments.
@param sequences: The list of residue sequences as one letter codes.
@type sequences: list of str
@keyword algorithm: The pairwise sequence alignment algorithm to use.
@type algorithm: str
@keyword matrix: The substitution matrix to use.
@type matrix: str
@keyword gap_open_penalty: The penalty for introducing gaps, as a positive number.
@type gap_open_penalty: float
@keyword gap_extend_penalty: The penalty for extending a gap, as a positive number.
@type gap_extend_penalty: float
@keyword end_gap_open_penalty: The optional penalty for opening a gap at the end of a sequence.
@type end_gap_open_penalty: float
@keyword end_gap_extend_penalty: The optional penalty for extending a gap at the end of a sequence.
@type end_gap_extend_penalty: float
@return: The list of alignment strings and the gap matrix.
@rtype: list of str, numpy rank-2 int array
"""
# Initialise.
N = len(sequences)
scores = zeros((N, N), float64)
# Set up lists of lists for storing all alignment strings.
align1_matrix = []
align2_matrix = []
for i in range(N):
align1_matrix.append([])
align2_matrix.append([])
for j in range(N):
if i == j:
align1_matrix[i].append(sequences[i])
align2_matrix[i].append(sequences[i])
else:
align1_matrix[i].append(None)
align2_matrix[i].append(None)
# Printout.
sys.stdout.write("\nCentral Star multiple sequence alignment.\n\n")
sys.stdout.write("%-30s %s\n" % ("Pairwise algorithm:", algorithm))
sys.stdout.write("%-30s %s\n" % ("Substitution matrix:", matrix))
sys.stdout.write("%-30s %s\n" % ("Gap opening penalty:", gap_open_penalty))
sys.stdout.write("%-30s %s\n" %
("Gap extend penalty:", gap_extend_penalty))
sys.stdout.write("Initial sequences:\n")
for i in range(N):
sys.stdout.write("%3i %s\n" % (i + 1, sequences[i]))
# All pairwise alignments.
sys.stdout.write("\nDetermining the scores for all pairwise alignments:\n")
for i in range(N):
for j in range(i + 1, N):
# Align the pair.
sys.stdout.write("%-30s " % ("Sequences %i-%i:" % (i + 1, j + 1)))
score, align1, align2, gaps = align_pairwise(
sequences[i],
sequences[j],
algorithm=algorithm,
matrix=matrix,
gap_open_penalty=gap_open_penalty,
gap_extend_penalty=gap_extend_penalty,
end_gap_open_penalty=end_gap_open_penalty,
end_gap_extend_penalty=end_gap_extend_penalty,
verbosity=0)
sys.stdout.write("%10.1f\n" % score)
# Store the score and alignment strings.
scores[i, j] = scores[j, i] = score
align1_matrix[i][j] = align1_matrix[j][i] = align1
align2_matrix[i][j] = align2_matrix[j][i] = align2
# The central sequence.
sys.stdout.write("\nDetermining the central sequence:\n")
sum_scores = scores.sum(0)
Sc_sum_score = 1e100
Sc_index = 0
for i in range(N):
if sum_scores[i] < Sc_sum_score:
Sc_sum_score = sum_scores[i]
Sc_index = i
sys.stdout.write("%-30s %10.1f\n" % (("Sum of scores, sequence %i:" %
(i + 1)), sum_scores[i]))
sys.stdout.write("%-30s %i\n" % ("Central sequence:", Sc_index + 1))
# Partition the sequences.
Sc = sequences[Sc_index]
Si = []
for i in range(N):
if i != Sc_index:
Si.append(sequences[i])
# Optimal alignments.
sys.stdout.write("\nDetermining the iterative optimal alignments:\n")
Sc_prime = Sc
string_lists = []
for i in range(N - 1):
# Update the string lists.
string_lists.append([])
# Perform the pairwise alignment between Sc' and Si, replacing all '-' with 'X'.
score, Sc_prime, Si_prime, gaps = align_pairwise(
Sc_prime.replace('-', 'X'),
Si[i].replace('-', 'X'),
algorithm=algorithm,
matrix=matrix,
gap_open_penalty=gap_open_penalty,
gap_extend_penalty=gap_extend_penalty,
end_gap_open_penalty=end_gap_open_penalty,
end_gap_extend_penalty=end_gap_extend_penalty,
verbosity=0)
sys.stdout.write("\n%-30s %s\n" %
("Sequence Sc':", Sc_prime.replace('X', '-')))
sys.stdout.write("%-30s %s\n" %
(("Sequence S%i':" %
(i + 1)), Si_prime.replace('X', '-')))
# Store the Si alignment.
for j in range(len(Sc_prime)):
string_lists[i].append(Si_prime[j])
# Add spaces to the lists for all previous alignments.
else:
# Find gaps in the central sequence.
for j in range(len(Sc_prime)):
if Sc_prime[j] == '-':
# Pad the previous alignments.
for k in range(0, i):
string_lists[k].insert(j, '-')
# Rebuild the alignment lists and create a gap matrix.
strings = []
M = len(Sc_prime)
strings.append(Sc_prime)
for i in range(N - 1):
strings.append(''.join(string_lists[i]))
for i in range(N):
strings[i] = strings[i].replace('X', '-')
# Restore the original sequence ordering.
string = strings.pop(0)
strings.insert(Sc_index, string)
# Create the gap matrix.
gaps = zeros((N, M), int16)
for i in range(N):
for j in range(M):
if strings[i][j] == '-':
gaps[i, j] = 1
# Final printout.
sys.stdout.write("\nFinal MSA:\n")
for i in range(N):
sys.stdout.write("%3i %s\n" % (i + 1, strings[i]))
# Return the results.
return strings, gaps
