def compute_primers():
# Get the part names.
sequence_name = request.form['sequence_name']
sequence = request.form['sequence'].replace('\n','')
backbone = request.form['backbone']
# Validation checks
if not validate_sequence_characters(sequence):
return error('Sequence contains non-ATGC letters')
if not validate_sequence_length(sequence):
return error('Sequence length has to be at least 100 n.t.')
else:
# Create a SeqRecord object.
part = SeqRecord(Seq(sequence.upper(), alphabet=generic_dna),
name=sequence_name, id=sequence_name)
backbone_part = plasmids[backbone]
p = PrimerDesigner()
p.set_sequences([part, backbone_part])
p.construct_graph()
nodes = p.nodes(data=True)
edges = p.edges(data=True)
protocol = p.pcr_protocol()
return render_template('primers.html',
nodes=nodes,
edges=edges,
protocol=protocol)
def compute_mutagenesis_primers(self):
"""
Using the sequence fragments to be assembled together, computes for
each step the primers that are to be used to assemble the mutated
fragments.
"""
for step, frags in self.fragments.items():
# Run the standard PrimerDesigner protocol.
p = PrimerDesigner()
p.set_sequences(frags)
# Ensure to set the filename attribute.
p.filename = 'step{step}'.format(step=step)
p.construct_graph()
p.compute_assembly_primers()
p.compute_junction_sequencing_primers()
p.compute_pcr_protocol()
self.primer_designers[step] = p
if __name__ == '__main__':
master_cloning_primers = list()
for f in os.listdir(os.getcwd()):
if '.fasta' in f:
print(f)
for k, v in segmaps.items():
if k in f:
segment = v
backbone = plasmids['pDZ-{0}-split2'.format(segment)]
print(backbone)
p = PrimerDesigner()
p.read_sequences(f)
p.add_sequences(backbone)
p.construct_graph()
protocol = p.pcr_protocol()
f = f.replace('.fasta', '')
pd.DataFrame(protocol).to_csv('{0}_pcr_protocol.csv'.format(f))
for n, d in p.nodes(data=True):
"""Grab out the cloning primers."""
primer_data = dict()
for drxn in ['fw', 're']:
primer_data['part'] = n
primer_data['{0}_cloning_primer'.format(drxn)] =\
str(d['{0}_cloning_primer'.format(drxn)].seq)
master_cloning_primers.append(primer_data)
pd.DataFrame(master_cloning_primers).to_csv('all_primers.csv')