def create_message(self):
content = KQMLList('FIND-MUTEX')
gene = ekb_from_text('TP53')
disease = ekb_from_text('breast cancer')
content.set('gene', gene)
content.set('disease', disease)
msg = get_request(content)
return msg, content
def test_get_disease():
disease_ekb = ekb_from_text('pancreatic cancer')
disease = get_disease(ET.fromstring(disease_ekb))
disease_ekb = ekb_from_text('lung cancer')
disease = get_disease(ET.fromstring(disease_ekb))
disease_ekb = ekb_from_text('diabetes')
disease = get_disease(ET.fromstring(disease_ekb))
disease_ekb = ekb_from_text('common cold')
disease = get_disease(ET.fromstring(disease_ekb))
def test_get_disease():
disease_ekb = ekb_from_text('pancreatic cancer')
disease = get_disease(ET.fromstring(disease_ekb))
disease_ekb = ekb_from_text('lung cancer')
disease = get_disease(ET.fromstring(disease_ekb))
disease_ekb = ekb_from_text('diabetes')
disease = get_disease(ET.fromstring(disease_ekb))
disease_ekb = ekb_from_text('common cold')
disease = get_disease(ET.fromstring(disease_ekb))
def create_message_1(self):
content = KQMLList('FIND-VARIANTS-FOR-GENES')
genes = ekb_from_text('EGFR and PTEN')
content.sets('genes', str(genes))
disease = ekb_from_text('glioblastoma')
content.sets('disease', disease)
content.sets('dataset', "tcga")
msg = get_request(content)
return msg, content
def test_expand_model_from_ekb():
m = MRA()
ekb = ekb_from_text('MAP2K1 phosphorylates MAPK1.')
res = m.build_model_from_ekb(ekb)
model_id = res.get('model_id')
assert(res.get('model'))
assert(res.get('model_id') == 1)
assert(len(m.models[1]) == 1)
ekb = ekb_from_text('MAP2K2 phosphorylates MAPK1.')
res = m.expand_model_from_ekb(ekb, model_id)
assert(res.get('model'))
assert(res.get('model_id') == 2)
assert(len(m.models[2]) == 2)
def create_message(self):
content = KQMLList('GET-COMMON')
ekb = ekb_from_text('MEK')
content.sets('genes', ekb)
content.sets('up-down', 'ONT::SUCCESSOR')
msg = get_request(content)
return msg, content
def create_message_AKT1(self):
content = KQMLList('FIND-GENE-SUMMARY')
genes = ekb_from_text('AKT1')
content.sets('gene', str(genes))
msg = get_request(content)
return msg, content
def create_message_3(self):
content = KQMLList('FIND-CELLULAR-LOCATION')
genes = ekb_from_text('AKT1, MAPK1')
content.sets('genes', str(genes))
msg = get_request(content)
return msg, content
def _get_message(heading, target=None, residue=None, position=None):
msa = msa_module.MSA_Module(testing=True)
content = KQMLList(heading)
if target is not None:
content.sets('target', ekb_from_text(target))
if residue and position:
content.sets('site', '%s-%s' % (residue, position))
return msa.respond_phosphorylation_activating(content)
def test_respond_choose_nonsense():
bs = BioSense_Module(testing=True)
msg_content = KQMLList('CHOOSE-SENSE')
msg_content.sets('ekb-term', ekb_from_text('bagel'))
res = bs.respond_choose_sense(msg_content)
print(res)
assert res.head() == 'SUCCESS'
assert res.get('agents')[0].gets('ont-type') is None
def test_make_cm():
m = MRA()
ekb = ekb_from_text('MEK binds MAPK1. MEK binds MAPK3.')
res = m.build_model_from_ekb(ekb)
pysb_model = res['model_exec']
cm = make_contact_map(pysb_model)
assert len(list(cm.nodes())) == 3
assert len(list(cm.edges())) == 2
def test_make_im():
m = MRA()
ekb = ekb_from_text('KRAS activates BRAF. Active BRAF binds MEK.')
res = m.build_model_from_ekb(ekb)
pysb_model = res['model_exec']
im = make_influence_map(pysb_model)
assert len(list(im.nodes())) == 3
assert len(list(im.edges())) == 3
def create_message_1(self):
content = KQMLList('FIND-DRUGS-FOR-MUTATION-DATASET')
genes = ekb_from_text('TP53')
content.sets('genes', str(genes))
content.sets('dataset', "CTRP")
msg = get_request(content)
return msg, content
def test_sbgn():
m = MRA()
ekb = ekb_from_text('KRAS activates BRAF.')
res = m.build_model_from_ekb(ekb)
ekb = ekb_from_text('NRAS activates BRAF.')
res = m.expand_model_from_ekb(ekb, 1)
sbgn = res['diagrams']['sbgn']
tree = ET.fromstring(sbgn)
glyphs = tree.findall('s:map/s:glyph',
namespaces={'s': 'http://sbgn.org/libsbgn/0.3'})
assert len(glyphs) == 6
res = m.model_undo()
sbgn = res['diagrams']['sbgn']
tree = ET.fromstring(sbgn)
glyphs = tree.findall('s:map/s:glyph',
namespaces={'s': 'http://sbgn.org/libsbgn/0.3'})
assert len(glyphs) == 4
def create_message(self):
content = KQMLList('PHOSPHORYLATION-ACTIVATING')
content.sets('target', ekb_from_text('MAPK1'))
for name, value in [('residue', 'T'), ('position', '185')]:
if value is not None:
content.sets(name, value)
msg = get_request(content)
return msg, content
def create_message(self):
content = KQMLList('PHOSPHORYLATION-ACTIVATING')
content.sets('target', ekb_from_text('MAPK1'))
for name, value in [('residue', 'T'), ('position', '185')]:
if value is not None:
content.sets(name, value)
msg = get_request(content)
return (msg, content)
def create_message_PAAD(self):
content = KQMLList('FIND-MUTATION-SIGNIFICANCE')
gene = ekb_kstring_from_text('ACTN4')
disease = ekb_from_text('pancreatic adenocarcinoma')
content.set('gene', gene)
content.set('disease', disease)
msg = get_request(content)
return msg, content
def create_message_failure_2(self):
content = KQMLList('FIND-MUTATION-SIGNIFICANCE')
gene = ekb_kstring_from_text('ABC')
disease = ekb_from_text('breast cancer')
content.set('gene', gene)
content.set('disease', disease)
msg = get_request(content)
return msg, content
def create_message_OV(self):
content = KQMLList('FIND-MUTATION-FREQUENCY')
gene = ekb_kstring_from_text('TP53')
disease = ekb_from_text('Ovarian serous cystadenocarcinoma')
content.set('gene', gene)
content.set('disease', disease)
msg = get_request(content)
return msg, content
def _get_message(heading, target=None, residue=None, position=None):
msa = msa_module.MSA_Module(testing=True)
content = KQMLList(heading)
if target is not None:
content.sets('target', ekb_from_text(target))
for name, value in [('residue', residue), ('position', position)]:
if value is not None:
content.sets(name, value)
return msa.respond_phosphorylation_activating(content)
def test_build_model_from_ekb():
m = MRA()
ekb = ekb_from_text('MAP2K1 phosphorylates MAPK1.')
res = m.build_model_from_ekb(ekb)
assert(res.get('model'))
assert(res.get('model_id') == 1)
assert(res.get('model_exec'))
assert(len(m.models[1]) == 1)
assert(isinstance(m.models[1][0], sts.Phosphorylation))
assert(m.models[1][0].enz.name == 'MAP2K1')
def test_choose_nonsense():
"""ekb terms that aren't biological agents should have ont-type None
BAGEL is from ONT::BAGELS-BISCUITS
"""
bs = BioSense()
case = ekb_from_text('bagel')
agents, _ = bs.choose_sense(case)
_, ont_type, _ = list(agents.values())[0]
assert ont_type is None
def test_make_diagrams():
m = MRA()
ekb = ekb_from_text('KRAS activates BRAF. Active BRAF binds MEK.')
res = m.build_model_from_ekb(ekb)
diagrams = res['diagrams']
assert diagrams['reactionnetwork']
assert diagrams['reactionnetwork'].endswith('.png')
assert diagrams['contactmap']
assert diagrams['contactmap'].endswith('.png')
assert diagrams['influencemap']
assert diagrams['influencemap'].endswith('.png')
def test_respond_choose_sense_ambiguity():
bs = BioSense_Module(testing=True)
msg_content = KQMLList('CHOOSE-SENSE')
pdk1_ekb = ekb_from_text('PDK1')
msg_content.sets('ekb-term', pdk1_ekb)
res = bs.respond_choose_sense(msg_content)
print(res)
agents = res.get('agents')
assert agents and agents.data
agent = agents[0]
name = agent.gets('name')
assert name == 'PDK1'
ont_type = agent.get('ont-type')
assert ont_type == 'ONT::GENE'
def test_choose_sense_category():
bs = BioSense()
cases = [(mek1_ekb, [('kinase activity', 'TRUE'),
('enzyme', 'TRUE'),
('kinase', 'TRUE'),
('transcription-factor', 'FALSE'),
('W::KINASE', 'TRUE'),
('phosphatase', 'FALSE')]),
(dusp_ekb, [('phosphatase', 'TRUE'), ('enzyme', 'TRUE')]),
(ekb_from_text('BRAF'), [('kinase', 'TRUE')])]
for ekb, result_tuples in cases:
for cat, result in result_tuples:
print('Testing: %s. Expect result %s.' % (cat, result))
in_category = bs.choose_sense_category(ekb, cat)
assert in_category == (result == 'TRUE')
def test_respond_choose_sense_category():
bs = BioSense_Module(testing=True)
cases = [(mek1_ekb, [('kinase activity', 'TRUE'),
('enzyme', 'TRUE'),
('kinase', 'TRUE'),
('transcription-factor', 'FALSE'),
('W::KINASE', 'TRUE'),
('phosphatase', 'FALSE')]),
(dusp_ekb, [('phosphatase', 'TRUE'), ('enzyme', 'TRUE')]),
(ekb_from_text('BRAF'), [('kinase', 'TRUE')])]
for ekb, result_tuples in cases:
msg_content = KQMLList('CHOOSE-SENSE-CATEGORY')
msg_content.sets('ekb-term', ekb)
for cat, result in result_tuples:
print('Testing: %s. Excpet result %s.' % (cat, result))
msg_content.sets('category', cat)
res = bs.respond_choose_sense_category(msg_content)
print(res)
print(res.head())
assert(res.head() == 'SUCCESS')
assert(res.get('in-category') == result)
def create_message(self):
content = KQMLList('FIND-COMMON-UPSTREAMS')
genes = ekb_from_text('AKT1, BRAF and MAPK1')
content.sets('genes', str(genes))
msg = get_request(content)
return msg, content
def create_message_failure(self):
content = KQMLList('FIND-MUTEX')
gene = ekb_from_text('BRAF')
content.set('gene', gene)
msg = get_request(content)
return msg, content
def test_has_mechanism():
m = MRA()
ekb = ekb_from_text('BRAF binds MEK')
m.build_model_from_ekb(ekb)
has_mechanism = m.has_mechanism(ekb, 1)
assert (has_mechanism)
def create_message_failure(self):
content = KQMLList('FIND-COMMON-UPSTREAMS')
genes = ekb_from_text('UGT2B10, PTEN')
content.sets('genes', str(genes))
msg = get_request(content)
return msg, content
def test_get_synonyms_no_synonyms_for_type():
"""raises InvalidAgentError when the agent is not recognized or if the
input submitted is not valid XML or is not in the correct format
"""
bs = BioSense()
bs.get_synonyms(ekb_from_text('vemurafenib'))
import unittest
from nose.tools import raises
from kqml import KQMLList
from bioagents.tests.util import ekb_from_text
from bioagents.biosense.biosense_module import BioSense_Module
from bioagents.biosense.biosense import BioSense, InvalidAgentError, \
InvalidCollectionError, UnknownCategoryError, \
CollectionNotFamilyOrComplexError, SynonymsUnknownError
# example ekb terms
mek1_ekb = ekb_from_text('MAP2K1') # agent
dusp_ekb = ekb_from_text('DUSP6') # agent
mek_ekb = ekb_from_text('MEK') # family
foo_ekb = ekb_from_text('foo') # invalid
# BioSense python API unit tests
def test_choose_sense():
bs = BioSense()
cases = [(mek1_ekb, 'MAP2K1', 'ONT::GENE'),
(dusp_ekb, 'DUSP6', 'ONT::GENE'),
(mek_ekb, 'MEK', 'ONT::PROTEIN-FAMILY')]
for case in cases:
agents, _ = bs.choose_sense(case[0])
agent, ont_type, _ = list(agents.values())[0]
assert agent.name == case[1]
assert ont_type == case[2]
@raises(InvalidAgentError)
def create_type_and_source(self):
return self._get_content('FIND-RELATIONS-FROM-LITERATURE',
type='Phosphorylation',
source=ekb_from_text('None'),
target=ekb_from_text('TP53'))
def create_message(self):
return self._get_content('CONFIRM-RELATION-FROM-LITERATURE',
type='phosphorylation',
source=ekb_from_text('MAP2K1'),
target=ekb_from_text('MAPK1'))
