def test_trial_summary(self):
on_trial['_genomic'] = {'hugo_symbol': [{'value': 'TEST'}]}
on_trial['_clinical'] = {'disease_status': [{'value': ['TEST']}]}
other = {'management_group': [{'value': 'TEST'}]}
# create trial tree
db = get_db()
me = MatchEngine(db)
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
# validate summary
summary = Summary(on_trial['_clinical'],
on_trial['_genomic'],
other,
trial_tree)
item = summary.create_summary(on_trial)
status_fields = ['drugs', 'genes', 'tumor_types', 'sponsor',
'phase_summary', 'accrual_goal', 'investigator', 'age_summary', 'protocol_number',
'disease_status', 'nct_number', 'disease_center', 'short_title',
'hormone_receptor_status']
for field in status_fields:
assert field in item, self._debug(item, field)
if field not in ['dfci_investigator', 'hormone_receptor_status']:
assert item[field], '%s| %s' % (field, item)
# remove all fields and validate that the summary will not error
del on_trial['age']
del on_trial['phase']
del on_trial['nct_id']
del on_trial['protocol_no']
del on_trial['principal_investigator']
del on_trial['cancer_center_accrual_goal_upper']
del on_trial['site_list']
del on_trial['sponsor_list']
del on_trial['drug_list']
del on_trial['staff_list']
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
summary = Summary(on_trial['_clinical'],
on_trial['_genomic'],
other,
trial_tree)
item = summary.create_summary(on_trial)
for field in status_fields:
assert field in item, self._debug(item, field)
def test_trial_summary(self):
on_trial['_genomic'] = {'hugo_symbol': [{'value': 'TEST'}]}
on_trial['_clinical'] = {'disease_status': [{'value': ['TEST']}]}
other = {'management_group': [{'value': 'TEST'}]}
# create trial tree
db = get_db()
me = MatchEngine(db)
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
# validate summary
summary = Summary(on_trial['_clinical'], on_trial['_genomic'], other,
trial_tree)
item = summary.create_summary(on_trial)
status_fields = [
'drugs', 'genes', 'tumor_types', 'sponsor', 'phase_summary',
'accrual_goal', 'investigator', 'age_summary', 'protocol_number',
'disease_status', 'nct_number', 'disease_center', 'short_title',
'hormone_receptor_status'
]
for field in status_fields:
assert field in item, self._debug(item, field)
if field not in ['dfci_investigator', 'hormone_receptor_status']:
assert item[field], '%s| %s' % (field, item)
# remove all fields and validate that the summary will not error
del on_trial['age']
del on_trial['phase']
del on_trial['nct_id']
del on_trial['protocol_no']
del on_trial['principal_investigator']
del on_trial['cancer_center_accrual_goal_upper']
del on_trial['site_list']
del on_trial['sponsor_list']
del on_trial['drug_list']
del on_trial['staff_list']
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
summary = Summary(on_trial['_clinical'], on_trial['_genomic'], other,
trial_tree)
item = summary.create_summary(on_trial)
for field in status_fields:
assert field in item, self._debug(item, field)
def test_ms_status(self):
on_trial['_clinical'] = {}
on_trial['_genomic'] = {'mmr_status': [{'value': 'MMR-Proficient'}]}
db = get_db()
me = MatchEngine(db)
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
summary = Summary(on_trial['_clinical'], on_trial['_genomic'], {},
trial_tree)
item = summary.create_summary(on_trial)
assert 'mmr_status' in item, self._debug(item, 'mmr_status')
on_trial['_genomic'] = {'ms_status': [{'value': 'MSI-H'}]}
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
summary = Summary(on_trial['_clinical'], on_trial['_genomic'], {},
trial_tree)
item = summary.create_summary(on_trial)
assert 'ms_status' in item, self._debug(item, 'ms_status')
def test_ms_status(self):
on_trial['_clinical'] = {}
on_trial['_genomic'] = {'mmr_status': [{'value': 'MMR-Proficient'}]}
db = get_db()
me = MatchEngine(db)
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
summary = Summary(on_trial['_clinical'],
on_trial['_genomic'],
{},
trial_tree)
item = summary.create_summary(on_trial)
assert 'mmr_status' in item, self._debug(item, 'mmr_status')
on_trial['_genomic'] = {'ms_status': [{'value': 'MSI-H'}]}
status, trial_tree = me.create_trial_tree(on_trial, no_validate=True)
summary = Summary(on_trial['_clinical'],
on_trial['_genomic'],
{},
trial_tree)
item = summary.create_summary(on_trial)
assert 'ms_status' in item, self._debug(item, 'ms_status')
def trial_insert(items):
# get database connection.
db = database.get_db()
# loop over each item.
for item in items:
# log this.
logging.info("trial inserted")
# build tree.
me = MatchEngine(db)
status, trial_tree = me.create_trial_tree(item, no_validate=True)
# look at every node.
genomic = {}
clinical = {}
other = {}
for n in trial_tree.nodes():
# get parent.
if 'node_id' not in trial_tree.node[n]:
continue
node_id = trial_tree.node[n]['node_id']
# look for multi-level nodes (right now its only match).
if 'match_tree' in trial_tree.node[n]:
# compress categories.
mt = trial_tree.node[n]['match_tree']
for x in mt:
if mt.node[x]['type'] == 'genomic':
insert_data_genomic(genomic, mt.node[x]['value'],
node_id)
if mt.node[x]['type'] == 'clinical':
insert_data_clinical(clinical, mt.node[x]['value'],
node_id)
# add the other nodes.
insert_data_other(trial_tree, node_id, n, other)
# create _summary, _suggest, and _elasticsearch fields
summary = Summary(clinical, genomic, other, trial_tree)
item['_summary'] = summary.create_summary(item)
autocomplete = Autocomplete(item)
item['_suggest'], item['_elasticsearch'], item['_summary']['primary_tumor_types'] = \
autocomplete.add_autocomplete()
return items
def trial_insert(items):
# get database connection.
db = database.get_db()
# loop over each item.
for item in items:
# log this.
logging.info("trial inserted")
# build tree.
me = MatchEngine(db)
status, trial_tree = me.create_trial_tree(item, no_validate=True)
# look at every node.
genomic = {}
clinical = {}
other = {}
for n in trial_tree.nodes():
# get parent.
if 'node_id' not in trial_tree.node[n]:
continue
node_id = trial_tree.node[n]['node_id']
# look for multi-level nodes (right now its only match).
if 'match_tree' in trial_tree.node[n]:
# compress categories.
mt = trial_tree.node[n]['match_tree']
for x in mt:
if mt.node[x]['type'] == 'genomic':
insert_data_genomic(genomic, mt.node[x]['value'], node_id)
if mt.node[x]['type'] == 'clinical':
insert_data_clinical(clinical, mt.node[x]['value'], node_id)
# add the other nodes.
insert_data_other(trial_tree, node_id, n, other)
# create _summary, _suggest, and _elasticsearch fields
summary = Summary(clinical, genomic, other, trial_tree)
item['_summary'] = summary.create_summary(item)
autocomplete = Autocomplete(item)
item['_suggest'], item['_elasticsearch'], item['_summary']['primary_tumor_types'] = \
autocomplete.add_autocomplete()
return items
class TestMatchEngine(TestSetUp):
# global vars.
me = None
def setUp(self):
super(TestMatchEngine, self).setUp()
# add clinical collection
self.db.clinical.insert_many([{
'ONCOTREE_PRIMARY_DIAGNOSIS_NAME': onc,
'SAMPLE_ID': self.sample_id,
'VITAL_STATUS': 'alive',
'DFCI_MRN': self.mrn,
'REPORT_DATE': self.static_date,
'BIRTH_DATE': self.static_date,
'GENDER': 'Male'
} for onc in ['_LIQUID_', '_SOLID_']])
self.add_clinical()
self.add_genomic()
def tearDown(self):
self.db.clinical.drop()
self.db.genomic.drop()
def test_validate_yaml_format(self):
# Read yaml file
test_inp = read_file(os.path.join(YAML_DIR, '00-000.yml'))
# Parse yaml document, The status should be 1 as validation should fail
status, data = self.me.validate_yaml_format(test_inp)
assert status == 1
# Parse yaml document, The status should be 0 as validation should pass
test_inp = read_file(os.path.join(YAML_DIR, '00-001.yml'))
status, data = self.me.validate_yaml_format(test_inp)
assert status == 0
# Assert the protocol id is correctly annotated
assert data['protocol_no'] == '00-001'
assert data['protocol_id'] == 00001
def test_validate_yaml_data(self):
# Read yaml file
test_inp = read_file(os.path.join(YAML_DIR, '00-001.yml'))
status, data = self.me.validate_yaml_format(test_inp)
# Validate the schema for yaml document
errors = self.me.validate_yaml_data(data)
# Assert that there are no errors
assert len(errors) == 0
test_inp = read_file(os.path.join(YAML_DIR, '00-002.yml'))
status, data = self.me.validate_yaml_format(test_inp)
# Assert Schema check fails
errors = self.me.validate_yaml_data(data)
assert errors['protocol_id'][0] == 'required field'
# assert we don't need a match clause at root.
test_inp = read_file(os.path.join(YAML_DIR, '00-003.yml'))
status, data = self.me.validate_yaml_format(test_inp)
assert status == 0
def test_run_query(self):
# reinstantiate MatchEngine so that the set of all sample ids in the database includes the documents that were
# posted by the unit test setUp
self.me = MatchEngine(self.db)
# define a clinical node
node = {'type': 'clinical', 'value': {'ONCOTREE_PRIMARY_DIAGNOSIS': 'Adrenal Gland', 'AGE_NUMERICAL': '>=18'}}
# run query
result, matches = self.me.run_query(node)
# assert number of samples are 89
assert len(result) == 1, len(result)
assert self.sample_id in result
# define a genomic criteria
node = {'type': 'genomic', 'value': {'HUGO_SYMBOL': '!BRAF'}}
# run query
result, matches = self.me.run_query(node)
# assert number of samples is 1
assert len(result) == 9, len(result)
assert self.sample_id not in result
self.add_genomic_v2()
node = {'type': 'genomic', 'value': {'HUGO_SYMBOL': 'WHSC1'}}
result, matches = self.me.run_query(node)
assert 'actionability' in matches[0]
assert matches[0]['mmr_status'] == 'Proficient (MMR-P / MSS)'
def test_prepare_clinical_criteria(self):
onc = 'ONCOTREE_PRIMARY_DIAGNOSIS'
oncname = 'ONCOTREE_PRIMARY_DIAGNOSIS_NAME'
# create clinical criteria
item = {'AGE_NUMERICAL': '>=18', onc: 'Melanoma'}
# convert to mongo query
c = self.me.prepare_clinical_criteria(item)
# assert length of ONCOTREE_DIAGNOSIS for 'Melanoma' is 9
assert len(c[oncname]['$in']) == 8
# check 'BIRTH DATE mongo query does less than search'
assert c['BIRTH_DATE'].keys()[0] == '$lte'
# check "!"
item = {'AGE_NUMERICAL': '<=18', onc: '!Melanoma'}
c = self.me.prepare_clinical_criteria(item)
assert c['BIRTH_DATE'].keys()[0] == '$gte'
assert len(c[oncname]['$nin']) == 8
# check with a list of diagnoses
item = {'AGE_NUMERICAL': '>=18', onc: ['!Melanoma', '!Glioblastoma', 'Pheochromocytoma', 'Astrocytoma']}
c = self.me.prepare_clinical_criteria(item)
assert c['BIRTH_DATE'].keys()[0] == '$lte'
assert '$nin' in c[oncname]
assert '$in' in c[oncname]
assert len(c[oncname]['$in']) == 2
assert len(c[oncname]['$nin']) == 12
# check _SOLID_ && _LIQUID_
liquid_item = {'AGE_NUMERICAL': '>=18', onc: '_LIQUID_'}
solid_item = {'AGE_NUMERICAL': '>=18', onc: '_SOLID_'}
liqc = self.me.prepare_clinical_criteria(liquid_item)
solc = self.me.prepare_clinical_criteria(solid_item)
assert len(liqc[oncname]['$in']) == 51, len(liqc[oncname]['$in'])
assert len(solc[oncname]['$in']) == 561, len(solc[oncname]['$in'])
def test_prepare_genomic_criteria(self):
# create a genomic criteria
item = {'HUGO_SYMBOL': '!KRAS', 'PROTEIN_CHANGE': 'p.V600E'}
# convert to mongo query
c, neg, _ = self.me.prepare_genomic_criteria(item)
# check ! symbol
assert c['$and'][0]['TRUE_HUGO_SYMBOL']['$eq'] == 'KRAS'
assert neg is True
# check protein change
assert c['$and'][0]['TRUE_PROTEIN_CHANGE']['$eq'] == 'p.V600E'
# check wildtype
assert '$or' in c['$and'][1], c
assert c['$and'][1]['$or'] == [{'WILDTYPE': False}, {'WILDTYPE': {'$exists': False}}]
def test_sv(self):
# create a genomic criteria
item = {'HUGO_SYMBOL': 'KRAS', 'VARIANT_CATEGORY': 'SV'}
# convert to mongo query
c, neg, _ = self.me.prepare_genomic_criteria(item)
# check sv
assert c['$and'][0]['VARIANT_CATEGORY']['$eq'] == 'SV'
# check wildtype
assert '$or' in c['$and'][1], c
assert c['$and'][1]['$or'] == [{'WILDTYPE': False}, {'WILDTYPE': {'$exists': False}}]
def test_create_trial_tree(self):
# parse yaml file and create tree.
test_inp = read_file(os.path.join(YAML_DIR, '00-004.yml'))
status, trial_tree = self.me.create_trial_tree(test_inp)
# assert it was successful.
assert status == 0
# check that we have 2 match trees.
cnt = 0
for n in trial_tree.nodes():
if 'match_tree' in trial_tree.node[n]:
cnt += 1
assert cnt == 2
# parse yaml file and create tree.
test_inp = read_file(os.path.join(YAML_DIR, '00-004.yml'))
status, trial_tree = self.me.create_trial_tree(test_inp)
# check that we have 14 nodes.
assert len(list(trial_tree.nodes())) == 4
# assert we have 3 match trees.
cnt = 0
for n in trial_tree.nodes():
if 'match_tree' in trial_tree.node[n]:
cnt += 1
assert cnt == 2
def test_create_match_tree(self):
# parse yaml file and create trial tree.
test_inp = read_file(os.path.join(YAML_DIR, '00-004.yml'))
status, trial_tree = self.me.create_trial_tree(test_inp)
# get the graph for the only match.
g = None
i = -1
number_of_nodes = [2, 10]
edges = [[(1, 2)], [(1, 2), (2, 3), (2, 4), (4, 5), (4, 6), (4, 7), (4, 8), (4, 9), (4, 10)]]
for n in trial_tree.nodes():
if 'match_tree' in trial_tree.node[n]:
i += 1
g = trial_tree.node[n]['match_tree']
assert g is not None
# Check if tree contain correct number of nodes
assert g.number_of_nodes() == number_of_nodes[i]
# Check edges are correctly created
assert list(nx.dfs_edges(g)) == edges[i]
# First node should be and
if i == 0:
assert g.node[1]['type'] == 'match'
assert g.node[2]['type'] == 'clinical'
print g.node[2]['value']
assert g.node[2]['value'] == {'disease_status': ['Advanced']}
elif i == 1:
assert g.node[1]['type'] == 'match'
assert g.node[2]['type'] == 'and'
assert g.node[3]['type'] == 'genomic'
assert g.node[3]['value'] == {'hugo_symbol': 'IDH1', 'wildcard_protein_change': 'p.R132', 'variant_category': 'Mutation'}
assert g.node[4]['type'] == 'or'
assert g.node[5]['type'] == 'clinical'
assert g.node[5]['value'] == {'age_numerical': '>=18', 'oncotree_primary_diagnosis': '_SOLID_'}
assert g.node[6]['type'] == 'clinical'
assert g.node[6]['value'] == {'age_numerical': '>=18', 'oncotree_primary_diagnosis': 'Diffuse Glioma'}
assert g.node[7]['type'] == 'clinical'
assert g.node[7]['value'] == {'age_numerical': '>=18', 'oncotree_primary_diagnosis': 'Encapsulated Glioma'}
assert g.node[8]['type'] == 'clinical'
assert g.node[8]['value'] == {'age_numerical': '>=18', 'oncotree_primary_diagnosis': 'Cholangiocarcinoma'}
assert g.node[9]['type'] == 'clinical'
assert g.node[9]['value'] == {'age_numerical': '>=18', 'oncotree_primary_diagnosis': 'Acute Myeloid Leukemia'}
assert g.node[10]['type'] == 'clinical'
assert g.node[10]['value'] == {'age_numerical': '>=18', 'oncotree_primary_diagnosis': 'Myelodysplasia'}
def test_search_oncotree_diagnosis(self):
# Glioblastoma
c = {'ONCOTREE_PRIMARY_DIAGNOSIS_NAME': {'$eq': 'Glioblastoma'}}
oncotree = build_oncotree()
c['ONCOTREE_PRIMARY_DIAGNOSIS_NAME'] = self.me._search_oncotree_diagnosis(oncotree, c)
conc = c['ONCOTREE_PRIMARY_DIAGNOSIS_NAME']
assert '$in' in conc, conc
assert conc['$in'] == ['Small Cell Glioblastoma', 'Gliosarcoma', 'Glioblastoma Multiforme', 'Glioblastoma'], conc
# Melanoma
c = {'ONCOTREE_PRIMARY_DIAGNOSIS_NAME': {'$eq': 'Melanoma'}}
conc = self.me._search_oncotree_diagnosis(oncotree, c)
assert '$in' in conc, conc
assert conc['$in'] == [
'Melanoma', 'Congenital Nevus', 'Genitourinary Mucosal Melanoma', 'Cutaneous Melanoma',
'Melanoma of Unknown Primary', 'Desmoplastic Melanoma', 'Lentigo Maligna Melanoma', 'Acral Melanoma'
]