class ClusterFinderTest(unittest.TestCase):
def setUp(self):
self.config = build_config([
"--cf-create-clusters", "--cf-mean-threshold", "0.6",
"--cf-min-cds", "5", "--cf-min-pfams", "5"
],
modules=[clusterfinder],
isolated=True)
update_config({"enabled_cluster_types": []})
self.record = DummyRecord(seq=Seq("A" * 2000))
for start, end, probability, pfam_id in [(10, 20, 0.1, 'PF77777'),
(30, 40, 0.3, 'PF00106'),
(50, 60, 0.4, 'PF00107'),
(60, 70, 0.7, 'PF00109'),
(70, 80, 0.98, 'PF08484'),
(90, 100, 0.8, 'PF02401'),
(100, 110, 0.32, 'PF04369'),
(110, 120, 1.0, 'PF00128'),
(130, 140, 0.2, 'PF77776'),
(500, 505, None, 'PF77775'),
(1010, 1020, 0.1, 'PF77774'),
(1030, 1040, 0.3, 'PF00106'),
(1050, 1060, 0.4, 'PF00107'),
(1060, 1070, 0.7, 'PF00109'),
(1070, 1080, 0.98, 'PF08484'),
(1090, 1100, 0.8, 'PF02401'),
(1100, 1110, 0.32, 'PF04369'),
(1110, 1120, 1.0, 'PF00128')]:
location = FeatureLocation(start, end, strand=1)
self.record.add_cds_feature(
CDSFeature(location, locus_tag=str(start), translation="A"))
pfam = DummyPFAMDomain(location=location,
protein_start=start + 1,
protein_end=end - 1,
identifier=pfam_id)
pfam.domain_id = "pfam_%d" % start
pfam.probability = probability
self.record.add_pfam_domain(pfam)
def tearDown(self):
destroy_config()
def test_options(self):
for val in [-1., -.01, -0.0001, 1.0001, 2.]:
update_config({"cf_threshold": val})
assert len(clusterfinder.check_options(self.config)) == 1
def test_check_prereqs(self):
self.assertEqual([], clusterfinder.check_prereqs(self.config))
def test_find_nr_cds(self):
left = (0, 5)
newpos, num = clusterfinder.probabilistic.find_nr_cds(
left, self.record)
self.assertEqual(left, newpos)
self.assertEqual(0, num)
right = (150, 160)
newpos, count = clusterfinder.probabilistic.find_nr_cds(
right, self.record)
assert newpos == right
assert count == 0
middle = (35, 115)
newpos, count = clusterfinder.probabilistic.find_nr_cds(
middle, self.record)
assert newpos == (30, 120)
assert count == 7
small = (501, 504)
newpos, count = clusterfinder.probabilistic.find_nr_cds(
small, self.record)
assert newpos == (500, 505)
assert count == 1
def test_find_probabilistic_clusters(self):
ret = clusterfinder.find_probabilistic_clusters(
self.record, self.config)
assert len(ret) == 2
assert ret[0].location.start == 30
assert ret[0].location.end == 120
assert ret[1].location.start == 1030
assert ret[1].location.end == 1120
def test_no_overlaps(self):
results = clusterfinder.generate_results(self.record, self.config)
areas = self.record.get_subregions()
assert len(results.areas) == 2
assert len(areas) == 2
assert list(areas) == results.areas
area = areas[0]
assert area.location.start == 30
assert area.location.end == 120
self.assertAlmostEqual(0.6429, area.probability, places=4)
area = areas[1]
assert area.location.start == 1030
assert area.location.end == 1120
self.assertAlmostEqual(0.6429, area.probability, places=4)
def test_full_loop(self):
results = clusterfinder.run_on_record(self.record, None, self.config)
old_areas = len(results.areas)
json_string = json.dumps(results.to_json())
regenned = clusterfinder.regenerate_previous_results(
json.loads(json_string), self.record, self.config)
assert len(regenned.areas) == old_areas
for old, new in zip(results.areas, regenned.areas):
assert old.location == new.location
self.assertAlmostEqual(old.probability, new.probability, places=6)
class ClusterFinderTest(unittest.TestCase):
def setUp(self):
self.config = build_config([
"--cf-create-clusters", "--cf-mean-threshold", "0.6",
"--cf-min-cds", "5", "--cf-min-pfams", "5"
],
modules=[clusterfinder],
isolated=True)
update_config({"enabled_cluster_types": []})
self.record = DummyRecord(seq=Seq("A" * 2000))
for start, end, probability, pfam_id in [(10, 20, 0.1, 'FAKE007'),
(30, 40, 0.3, 'PF00106'),
(50, 60, 0.4, 'PF00107'),
(60, 70, 0.7, 'PF00109'),
(70, 80, 0.98, 'PF08484'),
(90, 100, 0.8, 'PF02401'),
(100, 110, 0.32, 'PF04369'),
(110, 120, 1.0, 'PF00128'),
(130, 140, 0.2, 'FAKE234'),
(500, 505, None, 'FAKE505'),
(1010, 1020, 0.1, 'FAKE007'),
(1030, 1040, 0.3, 'PF00106'),
(1050, 1060, 0.4, 'PF00107'),
(1060, 1070, 0.7, 'PF00109'),
(1070, 1080, 0.98, 'PF08484'),
(1090, 1100, 0.8, 'PF02401'),
(1100, 1110, 0.32, 'PF04369'),
(1110, 1120, 1.0, 'PF00128')]:
location = FeatureLocation(start, end)
self.record.add_cds_feature(
CDSFeature(location, locus_tag=str(start)))
pfam = PFAMDomain(location, "dummy_description")
pfam.db_xref.append(pfam_id)
pfam.probability = probability
self.record.add_pfam_domain(pfam)
def tearDown(self):
destroy_config()
def test_options(self):
for val in [-1., -.01, -0.0001, 1.0001, 2.]:
update_config({"cf_threshold": val})
assert len(clusterfinder.check_options(self.config)) == 1
def test_check_prereqs(self):
self.assertEqual([], clusterfinder.check_prereqs())
def test_find_nr_cds(self):
left = (0, 5)
newpos, num = clusterfinder.probabilistic.find_nr_cds(
left, self.record)
self.assertEqual(left, newpos)
self.assertEqual(0, num)
right = (150, 160)
newpos, count = clusterfinder.probabilistic.find_nr_cds(
right, self.record)
assert newpos == right
assert count == 0
middle = (35, 115)
newpos, count = clusterfinder.probabilistic.find_nr_cds(
middle, self.record)
assert newpos == [30, 120]
assert count == 7
small = (501, 504)
newpos, count = clusterfinder.probabilistic.find_nr_cds(
small, self.record)
assert newpos == [500, 505]
assert count == 1
def test_find_probabilistic_clusters(self):
ret = clusterfinder.find_probabilistic_clusters(
self.record, self.config)
assert len(ret) == 2
assert ret[0].location.start == 30
assert ret[0].location.end == 120
assert ret[1].location.start == 1030
assert ret[1].location.end == 1120
def test_no_overlaps(self):
results = clusterfinder.generate_results(self.record, self.config)
self.assertEqual(2, len(results.borders))
assert list(self.record.get_cluster_borders()) == results.borders
cluster1, cluster2 = self.record.get_cluster_borders()
assert cluster1.location.start == 30
assert cluster1.location.end == 120
assert not cluster1.high_priority_product
self.assertAlmostEqual(0.6429, cluster1.probability, places=4)
assert cluster2.location.start == 1030
assert cluster2.location.end == 1120
assert not cluster2.high_priority_product
self.assertAlmostEqual(0.6429, cluster2.probability, places=4)
def test_merges(self):
clusterfinder.generate_results(self.record, self.config)
assert len(self.record.get_cluster_borders()) == 2
for start, end in [(10, 40), (1040, 1050), (110, 400)]:
loc = FeatureLocation(start, end)
self.record.add_cluster_border(
ClusterBorder(loc, "testtool", product=str(start)))
assert not self.record.get_clusters()
self.record.create_clusters_from_borders()
assert len(self.record.get_clusters()) == 2
cluster1, cluster2 = self.record.get_clusters()
assert cluster1.location.start == 10
assert cluster1.location.end == 400
assert cluster1.products == ("10", "110")
assert cluster2.location.start == 1030
assert cluster2.location.end == 1120
assert cluster2.products == ("1040", )
