print
# Create a vocabulary and encode the sequences.
v = Vocabulary()
aEncoded = v.encodeSequence(a)
bEncoded = v.encodeSequence(b)
print 'Encoded A:', aEncoded
print 'Encoded B:', bEncoded
print
# Create a scoring and align the sequences using global aligner.
scoring = SimpleScoring(2, -1)
aligner = GlobalSequenceAligner(scoring, -2)
score, alignments = aligner.align(aEncoded, bEncoded, backtrace=True)
# Create sequence profiles out of alignments.
profiles = [Profile.fromSequenceAlignment(a) for a in alignments]
for encoded in profiles:
profile = v.decodeProfile(encoded)
print profile
print
# Create a soft scoring and align the first profile against sequence A.
scoring = SoftScoring(scoring)
aligner = GlobalProfileAligner(scoring, -2)
score, alignments = aligner.align(profiles[0], Profile.fromSequence(aEncoded),
backtrace=True)
for encoded in alignments:
alignment = v.decodeProfileAlignment(encoded)
print alignment
# Create a vocabulary and encode the sequences.
v = Vocabulary()
aEncoded = v.encodeSequence(a)
bEncoded = v.encodeSequence(b)
print 'Encoded A:', aEncoded
print 'Encoded B:', bEncoded
print
# Create a scoring and align the sequences using global aligner.
scoring = SimpleScoring(2, -1)
aligner = GlobalSequenceAligner(scoring, -2)
score, alignments = aligner.align(aEncoded, bEncoded, backtrace=True)
# Create sequence profiles out of alignments.
profiles = [Profile.fromSequenceAlignment(a) for a in alignments]
for encoded in profiles:
profile = v.decodeProfile(encoded)
print profile
print
# Create a soft scoring and align the first profile against sequence A.
scoring = SoftScoring(scoring)
aligner = GlobalProfileAligner(scoring, -2)
score, alignments = aligner.align(profiles[0],
Profile.fromSequence(aEncoded),
backtrace=True)
for encoded in alignments:
alignment = v.decodeProfileAlignment(encoded)
print alignment
