def test_not_determine_when_wt_mis_generate_mut_site(self):
p = Pe()
p.name = 'TaqI'
p.clean_recognition_sequence = 'tcga'
p.save()
s = Snp('aaaaaat[g/t]gaaaaa')
print(Pe.objects.all().can_determine_snp(s, 1))
def test_not_determine_with_mismatches_in_snp(self):
p = Pe()
p.name = 'TaqI'
p.clean_recognition_sequence = 'tcga'
p.save()
s = Snp('aaaaaat[g/t]gaaaaa')
print(Pe.objects.all().can_determine_snp(s, 1))
def test_determine_with_two_mismatches(self):
p = Pe()
p.name = 'TaqI'
p.clean_recognition_sequence = 'tcga'
p.save()
s = Snp('aaaaaaa[tc/c]aaaaaa')
print(Pe.objects.all().can_determine_snp(s, 2))
def test_determine_with_one_mismatch(self):
p = Pe()
p.name = 'TaqI'
p.clean_recognition_sequence = 'tcga'
p.save()
s = Snp('aaaaaaa[tc/c]gaaaaa')
print(Pe.objects.can_determine_snp(s, 1))
def test_3(self):
p = Pe()
p.name = 'TaqI'
p.clean_recognition_sequence = 'tccy'
p.save()
s = Snp('aaaaaat[c/t]cataaa')
print("{} \n{}".format(self._testMethodName,
Pe.objects.can_determine_snp(s, 1)))
def test_determine_without_mismatches_IUPAC(self):
p = Pe()
p.name = 'TaqI'
p.clean_recognition_sequence = 'tcga'
p.save()
s = Snp('aaaaaatycgaaaaa')
print("{} \n{}".format(self._testMethodName,
Pe.objects.can_determine_snp(s, 0)))
def update_rebase_from_url(url='http://rebase.neb.com/rebase/link_itype2'):
"""
Updates (or creates) REs database from url (NEB Type II format with tabs)
Table Format
============
enzyme name [tab] prototype [tab] recognition sequence with cleavage site
[tab] methylation site and type [tab] commercial source [tab] references
:param url: REs table location (default is 'http://rebase.neb.com/rebase/link_itype2')
:returns: list of new REs and list of updated REs
Example
=======
>> list_of_new_res, list_of_updated_res = update_rebase_from_url()
Downloaded REs Entries: 3725
New REs: 3725
Updated REs: 0
"""
# from fastrflp.models import PrototypeEnzyme as Pe
# from fastrflp.models import RestrictionEnzyme as Re
try:
fh = urllib.request.urlopen(url)
except (ValueError, urllib.error.URLError):
raise fexceps.UpdateRebaseError('Error in URL: %r' % url)
html = fh.read().decode('utf8')
new_pes = []
upd_pes = []
new_res = []
upd_res = []
try:
enzyme_rows = html.splitlines()[10:-1]
except IndexError:
raise fexceps.UpdateRebaseError('Document %r is to short' % url)
for enzyme_row in enzyme_rows:
# enzyme name [tab] prototype [tab] recognition sequence with cleavage site
# [tab] methylation site and type [tab] commercial source [tab] references
try:
re_name, re_prototype, re_recognition_sequence, re_methylation_site, re_suppliers, re_refs \
= tuple(enzyme_row.split('\t'))
except ValueError as err:
if 'unpack' in err:
raise fexceps.UpdateRebaseError('RE table format error (num of columns)')
if re_prototype == '':
re_prototype = re_name
if not Pe.objects.filter(name=re_prototype).exists():
new_pe = Pe(name=re_prototype,
clean_recognition_sequence=clean_re_sequence(re_recognition_sequence),
)
new_pe.save()
new_pe.restrictionenzyme_set.create(name=re_name,
recognition_sequence=re_recognition_sequence,
suppliers=re_suppliers)
new_res.append(re_name)
#new_pe.save()
new_pes.append(re_prototype)
else:
# update PE
existing_pe = Pe.objects.get(name=re_prototype)
if existing_pe.clean_recognition_sequence != clean_re_sequence(re_recognition_sequence):
# existing_pe.prototype = re_prototype
# existing_pe.recognition_sequence = re_recognition_sequence
existing_pe.clean_recognition_sequence = clean_re_sequence(re_recognition_sequence)
# existing_pe.suppliers = re_suppliers
existing_pe.save()
upd_pes.append(re_prototype)
if not existing_pe.restrictionenzyme_set.filter(name=re_name).exists():
existing_pe.restrictionenzyme_set.create(name=re_name,
recognition_sequence=re_recognition_sequence,
suppliers=re_suppliers)
# existing_pe.save()
new_res.append(re_name)
else:
existing_re = Re.objects.get(name=re_name)
if existing_re.recognition_sequence != re_recognition_sequence \
or existing_re.suppliers != re_suppliers:
existing_re.recognition_sequence = re_recognition_sequence
existing_re.suppliers = re_suppliers
existing_re.save()
upd_res.append(re_name)
print('''
Downloaded REs Entries: {}
New PEs: {}\tUpdated PEs: {}
New REs: {}\tUpdated REs: {}
'''.format(len(enzyme_rows),
len(new_pes), len(upd_pes),
len(new_res), len(upd_res)))
return new_pes, upd_pes, new_res, upd_res