def source_specific_proteins_with_ptm_mutations():
source_models = mutation_sources()
source_models['merged'] = None
proteins_with_ptm_muts = {}
kinases = {}
kinase_groups = {}
for name, model in tqdm(source_models.items()):
query = (
db.session.query(distinct(Protein.id))
.filter(Protein.has_ptm_mutations_in_dataset(model) == True)
)
proteins_with_ptm_muts[name] = query.count()
kinases[name] = (
db.session.query(distinct(models.Kinase.id))
.join(Protein)
.filter(Protein.has_ptm_mutations_in_dataset(model) == True)
).count()
kinase_groups[name] = (
db.session.query(distinct(models.KinaseGroup.id))
.join(models.Kinase)
.join(Protein)
.filter(Protein.has_ptm_mutations_in_dataset(model) == True)
).count()
return {
'Proteins with PTM muts': proteins_with_ptm_muts,
'Kinases with PTM muts': kinases,
'Kinase groups with PTM muts': kinase_groups
}
def test_select_preferred_isoform(self):
proteins_data = [
('NM_001', 'MA', False),
('NM_002', 'MAA', True),
('NM_003', 'MAAA', True), # we want this one:
# canonical according to uniprot, then longest, then oldest in refseq
('NM_004', 'MAAA', True),
('NM_005', 'MAAAA', False)
]
preferred_refseq = 'NM_003'
gene = Gene(name='Gene X')
for refseq, seq, is_uniprot_canonical in proteins_data:
protein = Protein(refseq=refseq, sequence=seq, gene=gene)
if is_uniprot_canonical:
protein_references = ProteinReferences(
uniprot_entries=[UniprotEntry(isoform=1, reviewed=True)])
protein.external_references = protein_references
db.session.add(gene)
isoform = select_preferred_isoform(gene)
assert isoform
assert isoform.refseq == preferred_refseq
def test_edge_cases_mapping(self):
gene_t = Gene(
name='T',
isoforms=[
# 123456789
Protein(refseq='NM_01', sequence='AXAXAYAYA'),
# C-terminal part was trimmed
Protein(refseq='NM_02', sequence='AXAXA'),
# N-terminal part was trimmed
Protein(refseq='NM_03', sequence='AYAYA'),
])
db.session.add(gene_t)
db.session.commit()
mapper = SiteMapper(create_key_model_dict(Protein, 'refseq'),
lambda s: f'{s.position}{s.residue}')
# all sites in NM_01, the idea is to test
sites = DataFrame.from_dict(data={
'site at N-terminus edge': ('T', 'NM_01', 1, '^AX', 'A', 2),
'site at C-terminus edge': ('T', 'NM_01', 9, 'YA$', 'A', 2),
},
orient='index')
sites.columns = [
'gene', 'refseq', 'position', 'sequence', 'residue',
'left_sequence_offset'
]
mapped_sites = mapper.map_sites_by_sequence(sites)
assert len(mapped_sites) == 4
def test_sites(self):
p = Protein(**test_protein_data())
sites = [
Site(position=3, residue='R', type='phosphorylation'),
Site(position=4, residue='T', type='methylation')
]
db.session.add(p)
p.sites = sites
response = self.client.get('/protein/sites/NM_000123')
assert response.status_code == 200
assert response.content_type == 'application/json'
assert len(response.json) == 2
phospo_site_repr = None
for site_repr in response.json:
if site_repr['type'] == 'phosphorylation':
phospo_site_repr = site_repr
assert phospo_site_repr
def test_has_sites_in_range(self):
mutation_position = 100
sites_result = {
(93, 107): True,
(92, 108): False,
(100,): True,
tuple(): False,
(90,): False,
(110,): False,
(94, 95, 96, 97, 98, 99): True,
(101, 102, 103, 104, 105, 106): True,
(93,): True,
(107,): True
}
for sites_positions, expected_result in sites_result.items():
protein = Protein(
sites=[
Site(position=pos)
for pos in sites_positions
]
)
result = protein.has_sites_in_range(mutation_position - 7, mutation_position + 7)
assert result == expected_result
def test_mutation(self):
p = Protein(**test_protein_data())
p.mutations = create_test_mutations()
db.session.add(p)
queries = {
'/protein/mutation/NM_000123/1/K': 1,
'/protein/mutation/NM_000123/1/K?filters=Mutation.sources:in:MC3':
1,
'/protein/mutation/NM_000123/2/K': 1,
}
for query, expected_results_cnt in queries.items():
response = self.client.get(query)
assert len(response.json) == expected_results_cnt
response = self.client.get(
'/protein/mutation/NM_000123/2/K?filters=Mutation.sources:in:MC3')
assert 'Warning: There is a mutation, but it does not satisfy given filters' in response.json
response = self.client.get('/protein/mutation/NM_000123/2/K')
mut = response.json.pop()
assert mut['ref'] == 'A'
assert mut['pos'] == 2
assert mut['alt'] == 'K'
assert mut['protein'] == 'NM_000123'
def create_test_models():
protein = Protein(refseq='NM_0001',
gene=Gene(name='SOMEGENE'),
sequence='ABCD')
mutation = Mutation(protein=protein, position=1, alt='E')
protein.gene.preferred_isoform = protein
MC3Mutation(mutation=mutation,
cancer=Cancer(code='CAN'),
samples='Sample A,Sample B',
count=2)
InheritedMutation(mutation=mutation,
clin_data=[
ClinicalData(disease=Disease(name='Some disease'),
sig_code=5),
ClinicalData(disease=Disease(name='Other disease'),
sig_code=2)
])
protein_kinase = Protein(refseq='NM_0002',
gene=Gene(name='OTHERGENE'),
sequence='ABCD')
kinase = Kinase(name='Kinase name', protein=protein_kinase)
site = Site(protein=protein,
position=1,
residue='A',
kinases={kinase},
pmid={1, 2},
types={SiteType(name='glycosylation')})
protein.sites = [site]
return locals()
def test_mapping(self):
gene_a = Gene(
name='A',
isoforms=[
# the full isoform of gene A
Protein(refseq='NM_01', sequence='AAAAAAAAAXAA'),
# a trimmed isoform of gene A
Protein(refseq='NM_02', sequence='AAAXAA'),
])
gene_b = Gene(name='B',
isoforms=[
Protein(refseq='NM_03', sequence='BBBBBBBBBYBB'),
Protein(refseq='NM_04', sequence='BBBYBB'),
])
db.session.add_all([gene_a, gene_b])
# whoops, NM_03 has be accidentally removed (!)
db.session.delete(Protein.query.filter_by(refseq='NM_03').one())
db.session.commit()
mapper = SiteMapper(create_key_model_dict(Protein, 'refseq'),
lambda s: f'{s.position}{s.residue}')
sites = DataFrame.from_dict(data={
'good site A': ('A', 'NM_01', 10, 'AXA', 'X', 1),
'lost isoform': ('B', 'NM_03', 10, 'BYB', 'Y', 1)
},
orient='index')
sites.columns = [
'gene', 'refseq', 'position', 'sequence', 'residue',
'left_sequence_offset'
]
mapped_sites = mapper.map_sites_by_sequence(sites)
sites_by_isoform = group_by_isoform(mapped_sites)
# one from NM_01 (defined), from NM_02 (mapped), from NM_04 (mapped)
assert len(mapped_sites) == 3
assert set(sites_by_isoform) == {'NM_01', 'NM_02', 'NM_04'}
assert sites_by_isoform['NM_01'].residue == sites_by_isoform[
'NM_02'].residue == 'X'
assert sites_by_isoform['NM_01'].position == 10
assert sites_by_isoform['NM_02'].position == 4
assert sites_by_isoform['NM_04'].residue == 'Y'
assert sites_by_isoform['NM_04'].position == 4
# will the mapping to NM_02 still work if we remove 'gene' column?
sites.drop(columns=['gene'], inplace=True)
mapped_sites = mapper.map_sites_by_sequence(sites)
sites_by_isoform = group_by_isoform(mapped_sites)
assert len(mapped_sites) == 2
assert set(sites_by_isoform) == {'NM_01', 'NM_02'}
def test_known_mutations(self):
p = Protein(**test_protein_data())
p.mutations = create_test_mutations()
db.session.add(p)
response = self.client.get('/protein/known_mutations/NM_000123')
muts = response.json
assert len(muts) == 4
def test_train_model(self):
phosphorylation = SiteType(name='phosphorylation')
# non-phosphorylated serine residues are needed to generate negative sites
p = Protein(refseq='NM_007',
sequence='--------SLPA-----------SVIT-------')
g = Gene(isoforms=[p], preferred_isoform=p)
db.session.add(g)
# phosphorylated, with sites
p = Protein(refseq='NM_001',
sequence='--------SPAK-----------SPAR-------')
g = Gene(isoforms=[p], preferred_isoform=p)
db.session.add(g)
k = Kinase(name='CDK1', is_involved_in={phosphorylation})
for pos in [9, 24]:
s = Site(position=pos,
types={phosphorylation},
residue='S',
protein=p,
kinases={k})
db.session.add(s)
db.session.commit()
with TemporaryDirectory() as temp_dir:
model = train_model(phosphorylation,
sequences_dir=temp_dir,
sampling_n=2,
threshold=2)
# the model should have one set of params - for CDK1 kinase
assert len(model) == 1
cdk_params = model.rx2('CDK1')
pwm = cdk_params.rx2('pwm')
# and the position-specific weight matrix should be created
assert pwm
# the very detailed testing should be performed by rMIMP,
# but why not test the basics?
weights_of_central_aa = {
aa: value
for aa, value in zip(pwm.rownames, pwm.rx(True, 8))
}
assert weights_of_central_aa['S'] == max(
weights_of_central_aa.values())
def test_impact_on_ptm(self):
mutations = [Mutation(position=61)]
protein = Protein(refseq='NM_00001', mutations=mutations)
db.session.add(protein)
protein.sites = [
Site(position=61),
Site(position=54),
Site(position=51)
]
mutation = mutations[0]
assert mutation.impact_on_ptm() == 'direct'
def save_protein(request, strain_id):
theStrain = get_object_or_404(Strain, pk = strain_id)
protein_file = request.FILES['protein_file']
for seqRecord in SeqIO.parse(protein_file, "fasta"):
protein = Protein()
protein.name = seqRecord.id
protein.seq = seqRecord.seq.tostring()
protein.cds = CDS.objects.get(name = protein.name)
protein.createdDate = datetime.datetime.now()
protein.modifiedDate = datetime.datetime.now()
protein.save()
return HttpResponseRedirect('/strains/')
def test_browse(self):
p = Protein(**test_protein_data())
db.session.add(p)
response = self.client.get('/protein/browse', follow_redirects=True)
assert response.status_code == 200
def create_test_data():
mappings_filename = make_named_gz_file(raw_mappings)
# create proteins from first three data rows
protein_data = [
('NM_002749',
'MAEPLKEEDGEDGSAEPPGPVKAEPAHTAASVAAKNLALLKARSFDVTFDVGDEYEIIETIGNGAYGVVSSARRRLTGQQVAIKKIPNAFDVVTNAKRTLRELKILKHFKHDNIIAIKDILRPTVPYGEFKSVYVVLDLMESDLHQIIHSSQPLTLEHVRYFLYQLLRGLKYMHSAQVIHRDLKPSNLLVNENCELKIGDFGMARGLCTSPAEHQYFMTEYVATRWYRAPELMLSLHEYTQAIDLWSVGCIFGEMLARRQLFPGKNYVHQLQLIMMVLGTPSPAVIQAVGAERVRAYIQSLPPRQPVPWETVYPGADRQALSLLGRMLRFEPSARISAAAALRHPFLAKYHDPDDEPDCAPPFDFAFDREALTRERIKEAIVAEIEDFHARREGIRQQIRFQPSLQPVASEPGCPDVEMPSPWAPSGDCAMESPPPAPPPCPGPAPDTIDLTLQPPPPVSEPAPPKKDGAISDNTKAALKAALLKSLRSRLRDGPSAPLEAPEPRKPVTAQERQREREEKRRRRQERAKEREKRRQERERKERGAGASGGPSTDPLAGLVLSDNDRSLLERWTRMARPAAPALTSVPAPAPAPTPTPTPVQPTSPPPGPVAQPTGPQPQSAGSTSGPVPQPACPPPGPAPHPTGPPGPIPVPAPPQIATSTSLLAAQSLVPPPGLPGSSTPGVLPYFPPGLPPPDAGGAPQSSMSESPDVNLVTQQLSKSQVEDPLPPVFSGTPKGSGAGYGVGFDLEEFLNQSFDMGVADGPQDGQADSASLSASLLADWLEGHGMNPADIESLQREIQMDSPMLLADLPDLQDP*'
),
('NM_139033',
'MAEPLKEEDGEDGSAEPPGPVKAEPAHTAASVAAKNLALLKARSFDVTFDVGDEYEIIETIGNGAYGVVSSARRRLTGQQVAIKKIPNAFDVVTNAKRTLRELKILKHFKHDNIIAIKDILRPTVPYGEFKSVYVVLDLMESDLHQIIHSSQPLTLEHVRYFLYQLLRGLKYMHSAQVIHRDLKPSNLLVNENCELKIGDFGMARGLCTSPAEHQYFMTEYVATRWYRAPELMLSLHEYTQAIDLWSVGCIFGEMLARRQLFPGKNYVHQLQLIMMVLGTPSPAVIQAVGAERVRAYIQSLPPRQPVPWETVYPGADRQALSLLGRMLRFEPSARISAAAALRHPFLAKYHDPDDEPDCAPPFDFAFDREALTRERIKEAIVAEIEDFHARREGIRQQIRFQPSLQPVASEPGCPDVEMPSPWAPSGDCAMESPPPAPPPCPGPAPDTIDLTLQPPPPVSEPAPPKKDGAISDNTKAALKAALLKSLRSRLRDGPSAPLEAPEPRKPVTAQERQREREEKRRRRQERAKEREKRRQERERKERGAGASGGPSTDPLAGLVLSDNDRSLLERWTRMARPAAPALTSVPAPAPAPTPTPTPVQPTSPPPGPVAQPTGPQPQSAGSTSGPVPQPACPPPGPAPHPTGPPGPIPVPAPPQIATSTSLLAAQSLVPPPGLPGSSTPGVLPYFPPGLPPPDAGGAPQSSMSESPDVNLVTQQLSKSQVEDPLPPVFSGTPKGSGAGYGVGFDLEEFLNQSFDMGVADGPQDGQADSASLSASLLADWLEGHGMNPADIESLQREIQMDSPMLLADLPDLQDP*'
),
('NM_139034',
'MAEPLKEEDGEDGSAEPPGPVKAEPAHTAASVAAKNLALLKARSFDVTFDVGDEYEIIETIGNGAYGVVSSARRRLTGQQVAIKKIPNAFDVVTNAKRTLRELKILKHFKHDNIIAIKDILRPTVPYGEFKSVYVVLDLMESDLHQIIHSSQPLTLEHVRYFLYQLLRGLKYMHSAQVIHRDLKPSNLLVNENCELKIGDFGMARGLCTSPAEHQYFMTEYVATRWYRAPELMLSLHEYTQAIDLWSVGCIFGEMLARRQLFPGKNYVHQLQLIMMVLGTPSPAVIQAVGAERVRAYIQSLPPRQPVPWETVYPGADRQALSLLGRMLRFEPSARISAAAALRHPFLAKYHDPDDEPDCAPPFDFAFDREALTRERIKEAIVAEIEDFHARREGIRQQIRFQPSLQPVASEPGCPDVEMPSPWAPSGDCAMESPPPAPPPCPGPAPDTIDLTLQPPPPVSEPAPPKKDGAISDNTKAALKAALLKSLRSRLRDGPSAPLEAPEPRKPVTAQERQREREEKRRRRQERAKEREKRRQERERKERGAGASGGPSTDPLAGLVLSDNDRSLLERWTRMARPAAPALTSVPAPAPAPTPTPTPVQPTSPPPGPVAQPTGPQPQSAGSTSGPVPQPACPPPGPAPHPTGPPGPIPVPAPPQIATSTSLLAAQSLVPPPGLPGSSTPGVLPYFPPGLPPPDAGGAPQSSMSESPDVNLVTQQLSKSQVEDPLPPVFSGTPKGSGAGYGVGFDLEEFLNQSFDMGVADGPQDGQADSASLSASLLADWLEGHGMNPADIESLQREIQMDSPMLLADLPDLQDP*'
),
]
gene = Gene(name='MAPK7')
proteins = {
refseq_nm: Protein(refseq=refseq_nm, sequence=sequence, gene=gene)
for refseq_nm, sequence in protein_data
}
# we need to have proteins with id in session - hence commit
db.session.add(gene)
db.session.commit()
return mappings_filename, gene, proteins
def test_prepare_dataset(self):
from views.mutation import prepare_datasets
p = Protein(refseq='NM_000123',
sequence='TRAN',
gene=Gene(name='TP53'))
mutation = Mutation(protein=p, position=2, alt='K')
details = MC3Mutation(mutation=mutation, count=2)
db.session.add(mutation)
datasets, user_datasets = prepare_datasets(mutation)
expected_datasets = [{
'filter': 'Mutation.sources:in:' + source.name,
'name': source.display_name,
'mutation_present': False
} if source is not MC3Mutation else {
'filter': 'Mutation.sources:in:' + MC3Mutation.name,
'name': MC3Mutation.display_name,
'mutation_present': [details]
} for source in source_manager.confirmed]
assert datasets == expected_datasets
assert not user_datasets
def test_import(self):
protein = Protein(
refseq='NM_001741',
sequence=
'MGFQKFSPFLALSILVLLQAGSLHAAPFRSALESSPADPATLSEDEARLLLAALVQNYVQMKASELEQEQEREGSSLDSPRSKRCGNLSTCMLGTYTQDFNKFHTFPQTAIGVGAPGKKRDMSSDLERDHRPHVSMPQNAN*'
)
db.session.add(protein)
with initialized_importer(SimpleCase, 'O-GalNAc') as importer:
sites = importer.load_sites(site_datasets=['O-GalNAc'])
assert len(sites) == 2
sites_by_pos = {site.position: site for site in sites}
assert sites_by_pos[105].residue == sites_by_pos[109].residue == 'T'
assert sites_by_pos[105].types_names == {'O-glycosylation'}
# check re-loading
db.session.add_all(sites)
db.session.commit()
site = Site.query.filter_by(position=105).one()
assert site.types_names == {'O-glycosylation'}
def test_search_proteins(self):
from views.search import search_proteins
# create 15 genes and proteins
mock_proteins_and_genes(15)
# control: do we start with the mocked proteins not others?
assert not search_proteins('TP53')
# does respect limit? does symbol search work?
results = search_proteins('Gene', 10)
assert results
assert len(results) == 10
assert results[0].name.startswith('Gene')
# are results sorted?
db.session.add_all([
Gene(name=name, preferred_isoform=Protein(refseq='NM_%s' % 20 * i))
for i, name in enumerate(['TPK', 'TPKK'])
])
results = search_proteins('TPK', 2)
assert results[0].name == 'TPK'
assert results[0].best_score < results[1].best_score
# does include both: refseq and symbol search?
assert search_proteins('NM_0003', 1)
# can we change subset of searched features?
assert not search_proteins('NM_0003', 1, features=['gene_symbol'])
assert not search_proteins('Gene', 1, features=['refseq'])
def test_sites(self):
mutations = [Mutation(position=x) for x in (0, 5, 12, 57)]
protein = Protein(refseq='NM_00002',
mutations=mutations,
sites=[Site(position=x) for x in (10, 14, 15, 57)])
db.session.add(protein)
db.session.commit()
# ==test_find_closest_sites==
# for mutation at position 0 there is no closest site;
# for mutation at position 5 there should be 1 closest site
expected_closest_sites = dict(zip(mutations, [0, 1, 2, 1]))
for mutation, expected_sites_cnt in expected_closest_sites.items():
sites_found = mutation.find_closest_sites()
assert len(sites_found) == expected_sites_cnt
# ==test_get_affected_ptm_sites==
expected_affected_sites = dict(zip(mutations, [0, 1, 3, 1]))
for mutation, expected_sites_cnt in expected_affected_sites.items():
sites_found = mutation.get_affected_ptm_sites()
assert len(sites_found) == expected_sites_cnt
def test_types(self):
methylation = SiteType(name='methylation')
p = Protein(refseq='NM_007', id=1, sequence='ABCD')
db.session.add(p)
site = Site(position=2, types={methylation}, residue='B', protein=p)
db.session.add(site)
db.session.commit()
query = Protein.query
assert query.filter(Protein.sites.any(
Site.types.contains(methylation))).one()
assert not query.filter(
Protein.sites.any(~Site.types.contains(methylation))).all()
assert Site.query.filter(Site.types.contains(methylation)).count() == 1
assert not Site.query.filter(~Site.types.contains(methylation)).all()
phosphorylation = SiteType(name='phosphorylation')
assert not query.filter(
Protein.sites.any(Site.types.contains(phosphorylation))).all()
assert query.filter(
Protein.sites.any(~Site.types.contains(phosphorylation))).one()
assert Site.query.filter(
Site.types.contains(phosphorylation)).count() == 0
def test_prepare_tracks():
protein = Protein(refseq='NM_01',
sequence='123456789',
sites=[Site(position=4)])
sequence_track = SequenceTrack(protein)
site = sequence_track.subtracks[0].elements[0]
assert site.start >= 0
def create_test_proteins(refseqs) -> Dict[str, Protein]:
# reset cache
proteins = get_proteins(reload_cache=True)
for refseq in refseqs:
proteins[refseq] = Protein(refseq=refseq)
return proteins
def mock_proteins_and_genes(count):
from database import db
from models import Gene, Protein
for i in range(count):
g = Gene(name='Gene_%s' % i, full_name='Full name of gene %s' % i)
p = Protein(refseq='NM_000%s' % i, gene=g)
g.preferred_isoform = p
db.session.add(g)
def test_refseq(self):
from search.gene import RefseqGeneSearch
# create 15 genes and proteins
mock_proteins_and_genes(10)
search = RefseqGeneSearch().search
# negative control
for phase in ['9999', 'NM_00000', 'Gene']:
assert not search(phase)
# limiting
results = search('NM_', limit=5)
assert len(results) == 5
assert results[0].name.startswith('Gene')
# test the search itself
for refseq in ['NM_0003', 'nm_0003', '0003']:
results = search(refseq)
assert len(results) == 1
assert results[0].name == 'Gene_3'
isoforms = results[0].matched_isoforms
assert len(isoforms) == 1
assert isoforms.pop().refseq == 'NM_0003'
db.session.add_all([
Gene(name='Gene X',
isoforms=[
Protein(refseq='NM_000301'),
Protein(refseq='NM_000302'),
]),
Gene(name='Gene Y', isoforms=[Protein(refseq='NM_000309')])
])
# so there are three genes with isoforms starting with NM_0003
# (those are Gene_3, Gene X, Gene Y). Let see if limiting work
# well when applied per-gene.
queries = {'NM_0003': 2, 'NM_00030': 2, 'NM_000301': 1, 'NM_000302': 1}
for query, expected_result in queries.items():
assert len(search(query, limit=2)) == expected_result
def test_domains(self):
proteins = [
Protein(
refseq='NM_018163',
sequence=
'MAVTKELLQMDLYALLGIEEKAADKEVKKAYRQKALSCHPDKNPDNPRAAELFHQLSQALEVLTDAAARAAYDKVRKAKKQAAERTQKLDEKRKKVKLDLEARERQAQAQESEEEEESRSTRTLEQEIERLREEGSRQLEEQQRLIREQIRQERDQRLRGKAENTEGQGTPKLKLKWKCKKEDESKGGYSKDVLLRLLQKYGEVLNLVLSSKKPGTAVVEFATVKAAELAVQNEVGLVDNPLKISWLEGQPQDAVGRSHSGLSKGSVLSERDYESLVMMRMRQAAERQQLIARMQQEDQEGPPT*',
gene=Gene(chrom='15')),
Protein(
refseq='NM_004671',
sequence=
'MADFEELRNMVSSFRVSELQVLLGFAGRNKSGRKHDLLMRALHLLKSGCSPAVQIKIRELYRRRYPRTLEGLSDLSTIKSSVFSLDGGSSPVEPDLAVAGIHSLPSTSVTPHSPSSPVGSVLLQDTKPTFEMQQPSPPIPPVHPDVQLKNLPFYDVLDVLIKPTSLVQSSIQRFQEKFFIFALTPQQVREICISRDFLPGGRRDYTVQVQLRLCLAETSCPQEDNYPNSLCIKVNGKLFPLPGYAPPPKNGIEQKRPGRPLNITSLVRLSSAVPNQISISWASEIGKNYSMSVYLVRQLTSAMLLQRLKMKGIRNPDHSRALIKEKLTADPDSEIATTSLRVSLMCPLGKMRLTIPCRAVTCTHLQCFDAALYLQMNEKKPTWICPVCDKKAAYESLILDGLFMEILNDCSDVDEIKFQEDGSWCPMRPKKEAMKVSSQPCTKIESSSVLSKPCSVTVASEASKKKVDVIDLTIESSSDEEEDPPAKRKCIFMSETQSSPTKGVLMYQPSSVRVPSVTSVDPAAIPPSLTDYSVPFHHTPISSMSSDLPGLDFLSLIPVDPQYCPPMFLDSLTSPLTASSTSVTTTSSHESSTHVSSSSSRSETGVITSSGSNIPDIISLD*',
gene=Gene(chrom='18'))
]
db.session.add_all(proteins)
filename = make_named_temp_file(domains_data)
new_domains = load_domains(filename)
assert len(new_domains) == 6
assert len(proteins[0].domains) == 2
domains = defaultdict(list)
for domain in proteins[1].domains:
domains[domain.interpro.short_description].append(domain)
def assert_ranges(domain, start, end):
assert domain.start == start and domain.end == end
# two SAP domains should be merged for representation purposes due to similarity criteria
# (these two domain annotation overlap so the smaller one is contained in the bigger)
sap_domain = domains['SAP_dom'][0]
assert_ranges(sap_domain, 1, 65)
intepro_domain = sap_domain.interpro
assert intepro_domain.accession == 'IPR003034'
assert intepro_domain.description == 'SAP domain'
# here the two annotations overlap with more than 75% of common
assert_ranges(domains['PINIT'][0], 141, 299)
# and here overlap was too small to merge those domains
assert len(domains['Znf_MIZ']) == 2
def make_test_shared_proteins():
proteins = [
Protein(
refseq='NM_004318',
sequence=
'MAQRKNAKSSGNSSSSGSGSGSTSAGSSSPGARRETKHGGHKNGRKGGLSGTSFFTWFMVIALLGVWTSVAVVWFDLVDYEEVLGKLGIYDADGDGDFDVDDAKVLLGLKERSTSEPAVPPEEAEPHTEPEEQVPVEAEPQNIEDEAKEQIQSLLHEMVHAEHVEGEDLQQEDGPTGEPQQEDDEFLMATDVDDRFETLEPEVSHEETEHSYHVEETVSQDCNQDMEEMMSEQENPDSSEPVVEDERLHHDTDDVTYQVYEEQAVYEPLENEGIEITEVTAPPEDNPVEDSQVIVEEVSIFPVEEQQEVPPETNRKTDDPEQKAKVKKKKPKLLNKFDKTIKAELDAAEKLRKRGKIEEAVNAFKELVRKYPQSPRARYGKAQCEDDLAEKRRSNEVLRGAIETYQEVASLPDVPADLLKLSLKRRSDRQQFLGHMRGSLLTLQRLVQLFPNDTSLKNDLGVGYLLIGDNDNAKKVYEEVLSVTPNDGFAKVHYGFILKAQNKIAESIPYLKEGIESGDPGTDDGRFYFHLGDAMQRVGNKEAYKWYELGHKRGHFASVWQRSLYNVNGLKAQPWWTPKETGYTELVKSLERNWKLIRDEGLAVMDKAKGLFLPEDENLREKGDWSQFTLWQQGRRNENACKGAPKTCTLLEKFPETTGCRRGQIKYSIMHPGTHVWPHTGPTNCRLRMHLGLVIPKEGCKIRCANETKTWEEGKVLIFDDSFEHEVWQDASSFRLIFIVDVWHPELTPQQRRSLPAI*'
),
Protein(
refseq='NM_020164',
sequence=
'MAEDKETKHGGHKNGRKGGLSGTSFFTWFMVIALLGVWTSVAVVWFDLVDYEEVLAKAKDFRYNLSEVLQGKLGIYDADGDGDFDVDDAKVLLEGPSGVAKRKTKAKVKELTKEELKKEKEKPESRKESKNEERKKGKKEDVRKDKKIADADLSRKESPKGKKDREKEKVDLEKSAKTKENRKKSTNMKDVSSKMASRDKDDRKESRSSTRYAHLTKGNTQKRNG*'
)
]
db.session.add_all(proteins)
db.session.commit()
def create_test_kinase(name, refseq):
interactor = Kinase(name=name)
kinase_gene = Gene(name='Gene of ' + interactor.name)
kinase_protein = Protein(refseq=refseq, gene=kinase_gene)
interactor.protein = kinase_protein
return interactor
def test_search_mutations(self):
s = Site(position=13, types={SiteType(name='methylation')})
p = Protein(refseq='NM_007', id=7, sites=[s], sequence='XXXXXXXXXXXXV')
m_in_site = Mutation(protein=p, position=13, alt='V')
m_out_site = Mutation(protein=p, position=50, alt='K')
db.session.add(p)
# points to the same location as first record in VCF_FILE_CONTENT
test_query = 'chr20 14370 G A'
from database import bdb
# map the first genomic mutation from VCF_FILE_CONTENT
# to some (mocked) protein mutation
bdb.add_genomic_mut('20', 14370, 'G', 'A', m_in_site, is_ptm=True)
#
# basic test - is appropriate mutation in results?
#
response = self.search_mutations(mutations=test_query)
assert response.status_code == 200
# this mutation is exactly at a PTM site and should be included in results
assert '<td>{0}</td>'.format(m_in_site.alt).encode() in response.data
# this mutation lies outside of a PTM site - be default should be filtered out
assert '<td>{0}</td>'.format(m_out_site.alt).encode() not in response.data
#
# count test - is mutation for this query annotated as shown twice?
#
response = self.search_mutations(
mutations='{0}\n{0}'.format(test_query)
)
assert response.status_code == 200
assert b'<td>2</td>' in response.data
#
# VCF file test
#
response = self.client.post(
'/search/mutations',
content_type='multipart/form-data',
data={
'vcf-file': (BytesIO(VCF_FILE_CONTENT), 'exemplar_vcf.vcf')
}
)
assert response.status_code == 200
assert b'NM_007' in response.data
def test_trim_ends():
# protein sequences are 1-based
track = SequenceTrack(Protein(sequence='1234567890'))
element = [-5, 10] #
track.trim_ends([element])
assert element == [1, 4]
element = [5, 10] # 567890----
track.trim_ends([element])
assert element == [5, 6] # should include 0
def test_redirect(self):
p = Protein(**test_protein_data())
db.session.add(p)
response = self.client.get(
'/protein/show/NM_000123?filters=Mutation.sources:in:MC3')
assert response.status_code == 302
assert relative_location(
response
) == '/sequence/show/NM_000123?filters=Mutation.sources:in:MC3'
def test_map_site_to_isoform(self):
mapper = SiteMapper([], lambda s: f'{s.position}{s.sequence}')
site = RawSite(sequence='FIN', position=6, left_sequence_offset=1)
protein = Protein(sequence='LKIQYTKIFINNEWHDSVSG')
assert mapper.map_site_to_isoform(site, protein) == [10]
with warns(UserWarning, match='More than one match for: 2KI'):
site = RawSite(sequence='KI', position=2, left_sequence_offset=0)
assert mapper.map_site_to_isoform(site, protein) == [2, 7]
def loadProtein(request):
f = open('C:/Users/anna/Desktop/Doktorat/typeii/src/typeii/sourceData/nonsystemalso_new.csv')
proteins = []
headers = 2
'''#uncomment to use test mode (upload only 5 records)
temp = 40#test'''
# possibly needed to indicate protein affiliation
#genomes = Genome.objects.all()
#pieces = DNAPiece.objects.all()
systems = System.objects.all()
for line in f:
data = line.split(',')
gene_id = data[0].replace('"', '')
if gene_id in proteins or headers != 0:
headers -= 1
pass
else:
system = int(data[4].replace('"', ''))
genome_location = data[8].replace('"', '')
if data[9].replace('"', '') == '+':
strand = '+'
else:
strand = '-'
margin_left = int(data[10].replace('"', ''))
system_part = data[11].replace('"', '')
clans_cluster = '' #fixed value till data available
hammer_cluster = data[12].replace('"', '')
subunit_kind = data[13].replace('"', '')
dna_length = int(data[15].replace('"', ''))
aa_sequence = data[17].replace('"', '')
hh_pfam_id = data[18].replace('"', '')
hh_pfam_short_desc = data[19].replace('"', '')
hh_probability_raw = data[20].replace('"','')
if hh_probability_raw != '':
hh_probability = decimal.Decimal(hh_probability_raw)
else:
hh_probability = decimal.Decimal(0.0) #default for records without hh value
hh_probability.quantize(decimal.Decimal('.01'))
hh_e_value = data[21].replace('"', '')
hh_pfam_desc = data[22].replace('"', '')
m_probability = 0 #fixed value till data from Vilno
r_probability = 0 #fixed value till data from Vilno
s_probability = 0 #fixed value till data from Vilno
print (gene_id)
proteins.append(gene_id)
for record in systems:
if record.id == system:
#uncomment for verbose upload
print(record.id, gene_id + ' ' + genome_location + ' ' +
strand, margin_left, system_part + ' ' +
clans_cluster + ' ' + hammer_cluster + ' ' +
subunit_kind, dna_length, aa_sequence + ' ' +
hh_pfam_id + ' ' + hh_pfam_short_desc,
hh_probability, hh_e_value + ' ' +
hh_pfam_desc, m_probability,
r_probability, s_probability)
p = Protein(system=record, gene_id=gene_id, genome_location=genome_location,
strand=strand, margin_left=margin_left, system_part=system_part,
clans_cluster=clans_cluster, hammer_cluster=hammer_cluster,
subunit_kind=subunit_kind, dna_length=dna_length, aa_sequence=aa_sequence,
hh_pfam_id=hh_pfam_id, hh_pfam_short_desc=hh_pfam_short_desc,
hh_probability=hh_probability, hh_e_value=hh_e_value,
hh_pfam_desc=hh_pfam_desc, m_probability=m_probability,
r_probability=r_probability, s_probability=s_probability)
p.save()
print('Protein appended.')
'''#uncomment to use test mode (upload only 5 records)
temp -= 1#test
if temp == 0:#test
break#test'''
return HttpResponse('Download complete.')
