def main():
parser = argparse.ArgumentParser()
help_backtrack = "Backtrack and output an optimal alignment along with the cost"
parser.add_argument('-b',
'--backtrack',
help=help_backtrack,
action='store_true')
help_seqs = "Path to FASTA file containing the three sequences"
parser.add_argument('sequences', help=help_seqs)
help_substmatrix = "Path to a file containing the score matrix"
parser.add_argument("substmatrix", help=help_substmatrix)
help_gapcost = 'Value for the linear gapcost'
parser.add_argument('gapcost', type=int, help=help_gapcost)
args = parser.parse_args()
sequences_names_tuples = prj3.read_input_fasta(args.sequences)
seqs = [tup[1] for tup in sequences_names_tuples]
alphabet, substmatrix = prj2.read_input_score(args.substmatrix)
gapcost = args.gapcost
backtrack = args.backtrack
print(
prj3.sp_exact_3(seqs[0], seqs[1], seqs[2], substmatrix, gapcost,
alphabet, backtrack))
def main():
parser = argparse.ArgumentParser()
help_seqs = "Path to FASTA file containing the sequences"
parser.add_argument('sequences', help=help_seqs)
help_substmatrix = "Path to a file containing the score matrix"
parser.add_argument("substmatrix", help=help_substmatrix)
args = parser.parse_args()
sequences_names_tuples = read_input_fasta(args.sequences)
alphabet, substmatrix = prj2.read_input_score(args.substmatrix)
run_tests(sequences_names_tuples, substmatrix, alphabet, 5)
def main():
parser = argparse.ArgumentParser()
help_seqs = "Path to FASTA file containing the three sequences"
parser.add_argument('sequences', help=help_seqs)
help_substmatrix = "Path to a file containing the score matrix"
parser.add_argument("substmatrix", help=help_substmatrix)
help_gapcost = 'Value for the linear gapcost'
parser.add_argument('gapcost', type=int, help=help_gapcost)
args = parser.parse_args()
sequences_names_tuples = prj3.read_input_fasta(args.sequences)
alphabet, substmatrix = prj2.read_input_score(args.substmatrix)
gapcost = args.gapcost
prj3.sp_approx_2(sequences_names_tuples, alphabet, substmatrix, gapcost)
def main():
parser = argparse.ArgumentParser()
input_seq1 = "Path to FASTA file containing the first sequence"
parser.add_argument("seq1", help=input_seq1)
input_seq2 = "Path to FASTA file containing the second sequence"
parser.add_argument("seq2", help=input_seq2)
input_scoreMatrix = "Path to a file containing the score matrix"
parser.add_argument("scoreMatrix", help=input_scoreMatrix)
input_alpha = "alpha value to be used in affine cost function"
parser.add_argument("alpha", help=input_alpha, type=int)
input_beta = "beta value to be used in affine cost function"
parser.add_argument("beta", help=input_beta, type=int)
input_backtrack = "returns an optimal alignment along with the cost"
parser.add_argument('-b',
'--backtrack',
help=input_backtrack,
action='store_true')
args = parser.parse_args()
seq1 = p2.read_input_fasta(args.seq1)
seq2 = p2.read_input_fasta(args.seq2)
alphabet, scoreMatrix = p2.read_input_score(args.scoreMatrix)
alphaCost = args.alpha
betaCost = args.beta
bool_backtrack = args.backtrack
p2.alpha = alphaCost
p2.beta = betaCost
p2.mSub = scoreMatrix
p2.alph = alphabet
cost, alignment = p2.optimal_cost(seq1, seq2, min, bool_backtrack)
print('cost: %i' % cost)
if bool_backtrack:
print('>seq1')
print(alignment[0])
print()
print('>seq2')
print(alignment[1])