def test_has_attC(self):
replicon = SeqRecord(Seq.Seq(''), id='foo')
integron = Integron(replicon, self.cfg)
self.assertFalse(integron.has_attC())
replicon = SeqRecord(Seq.Seq(''), id='just_one_attC', name='bar')
just_one_attC = Integron(replicon, self.cfg)
just_one_attC.add_attC(10, 100, 1, 1e-2, "intersection_tyr_intI")
self.assertTrue(just_one_attC.has_attC())
def test_add_attc(self):
replicon_name = "acba.007.p01.13"
replicon_path = self.find_data(
os.path.join('Replicons', replicon_name + '.fst'))
topologies = Topology('lin')
with FastaIterator(replicon_path) as sequences_db:
sequences_db.topologies = topologies
replicon = next(sequences_db)
data_attc_1 = {
"pos_beg": 10,
"pos_end": 100,
"strand": -1,
"evalue": 1.1e-07,
"type_elt": "attC",
"annotation": "attC",
"model": "attc_4",
"distance_2attC": np.nan
}
attc_1 = pd.DataFrame(data_attc_1,
columns=self.columns,
index=['attc_001'])
attc_1 = attc_1.astype(dtype=self.dtype)
integron = Integron(replicon, self.cfg)
integron.add_attC(attc_1.loc['attc_001', 'pos_beg'],
attc_1.loc['attc_001',
'pos_end'], attc_1.loc['attc_001',
'strand'],
attc_1.loc['attc_001',
'evalue'], attc_1.loc['attc_001',
'model'])
pdt.assert_frame_equal(attc_1, integron.attC)
attc_2 = pd.DataFrame(data_attc_1,
columns=self.columns,
index=['attc_002'])
attc_2 = attc_2.astype(dtype=self.dtype)
attc_2['pos_beg'] = attc_2['pos_beg'] + 100
attc_2['pos_end'] = attc_2['pos_end'] + 100
attc_2["distance_2attC"] = (
attc_2.loc['attc_002', 'pos_beg'] -
attc_1.loc['attc_001', 'pos_end']) % len(replicon)
attc = attc_1.append(attc_2)
integron.add_attC(attc_2.loc['attc_002', 'pos_beg'],
attc_2.loc['attc_002',
'pos_end'], attc_2.loc['attc_002',
'strand'],
attc_2.loc['attc_002',
'evalue'], attc_2.loc['attc_002',
'model'])
pdt.assert_frame_equal(attc, integron.attC)
def test_annot_calin(self):
"""
Test func_annot when the integron is a CALIN (attC but no integrase), with 4 proteins:
for 3 of them resfam annotations are found, and not for the last 1.
"""
# Create integron
integron1 = Integron(self.replicon, self.cfg)
integrons = [integron1]
# Add only attc sites (no integrase)
integron1.add_attC(17825, 17884, -1, 7e-9, "attc_4")
integron1.add_attC(19080, 19149, -1, 7e-4, "attc_4")
integron1.add_attC(19618, 19726, -1, 7e-7, "attc_4")
# Add proteins between attC sites
integron1.add_proteins(self.prot_db)
# Check that proteins dataframe is as expected before annotation
proteins = pd.DataFrame({"pos_beg": [17375, 17886, 19090, 19721],
"pos_end": [17722, 18665, 19749, 20254],
"strand": [-1] * 4,
"evalue": [np.nan] * 4,
"type_elt": ["protein"] * 4,
"model": ["NA"] * 4,
"distance_2attC": [np.nan] * 4,
"annotation": ["protein"] * 4},
index=["ACBA.007.P01_13_20", "ACBA.007.P01_13_21",
"ACBA.007.P01_13_22", "ACBA.007.P01_13_23"])
proteins = proteins[["pos_beg", "pos_end", "strand", "evalue", "type_elt",
"model", "distance_2attC", "annotation"]]
# we need to sort the dataframe
# as protein file is parse using biopython and index
# the order os sequences is not guarantee
pdt.assert_frame_equal(proteins.sort_index(), integron1.proteins.sort_index())
# Annotate proteins
func_annot(integrons, self.replicon, self.prot_db, self.hmm_files, self.cfg, self.tmp_dir)
# Check that all files generated are as expected
files_created = [f for f in glob.glob(os.path.join(self.tmp_dir, "*")) if os.path.isfile(f)]
self.assertEqual(set(self.exp_files), set(files_created))
# Check that annotated proteins are as expected
proteins.loc["ACBA.007.P01_13_20"] = [17375, 17722, -1, 4.5e-31, "protein", "RF0066", np.nan, "emrE"]
proteins.loc["ACBA.007.P01_13_21"] = [17886, 18665, -1, 7.4e-168, "protein", "RF0027", np.nan, "ANT3"]
proteins.loc["ACBA.007.P01_13_23"] = [19721, 20254, -1, 6.2e-110, "protein", "RF0003", np.nan, "AAC3-I"]
# we need to sort the dataframe
# as protein file is parse using biopython and index
# the order os sequences is not guarantee
pdt.assert_frame_equal(proteins.sort_index(), integron1.proteins.sort_index())
def test_annot_wrong_hmmsearch(self):
"""
Test that when the given HMMSEARCH command does not exist, it raises an exception
specifying that the given command could not run.
"""
self.cfg._args.hmmsearch = "nimportnaoik"
# Create integron
integron1 = Integron(self.replicon.name, self.cfg)
integrons = [integron1]
# Add only attc sites (no integrase)
integron1.add_attC(17825, 17884, -1, 7e-9, "attc_4")
integron1.add_attC(19080, 19149, -1, 7e-4, "attc_4")
integron1.add_attC(19618, 19726, -1, 7e-7, "attc_4")
# Add proteins between attC sites
integron1.add_proteins(self.prot_db)
# Annotate proteins
with self.assertRaises(RuntimeError) as ctx:
func_annot(integrons, self.replicon, self.prot_db, self.hmm_files, self.cfg, self.tmp_dir)
self.assertTrue(re.search("failed : \[Errno 2\] No such file or directory: 'nimportnaoik'", str(ctx.exception)))
def test_annot_wrong_hmm(self):
"""
Test that when the given hmm file does not exist, it returns an error specifying that
the hmm command ended with a non-zero return code.
"""
wrong_hmm_files = ["myhmm.hmm"]
# Create integron
integron1 = Integron(self.replicon, self.cfg)
integrons = [integron1]
# Add only attc sites (no integrase)
integron1.add_attC(17825, 17884, -1, 7e-9, "attc_4")
integron1.add_attC(19080, 19149, -1, 7e-4, "attc_4")
integron1.add_attC(19618, 19726, -1, 7e-7, "attc_4")
# Add proteins between attC sites
integron1.add_proteins(self.prot_db)
# Annotate proteins
with self.assertRaises(RuntimeError) as ctx:
func_annot(integrons, self.replicon, self.prot_db, wrong_hmm_files, self.cfg, self.tmp_dir)
self.assertTrue(str(ctx.exception).endswith(" failed return code = 1"))
def test_type(self):
replicon = SeqRecord(Seq.Seq(''), id='foo')
no_integrase = Integron(replicon, self.cfg)
self.assertIsNone(no_integrase.type())
replicon = SeqRecord(Seq.Seq(''), id='just_one_integrase')
just_one_integrase = Integron(replicon, self.cfg)
just_one_integrase.add_integrase(10,
100,
'foo',
1,
1e-2,
"intersection_tyr_intI")
self.assertEqual(just_one_integrase.type(), "In0")
replicon = SeqRecord(Seq.Seq(''), id='just_one_attC')
just_one_attC = Integron(replicon, self.cfg)
just_one_attC.add_attC(10,
100,
1,
1e-2,
"intersection_tyr_intI")
self.assertEqual(just_one_attC.type(), "CALIN")
replicon = SeqRecord(Seq.Seq(''), id='one_integrase_one_attC')
one_integrase_one_attC = Integron(replicon, self.cfg)
one_integrase_one_attC.add_integrase(10,
100,
'foo',
1,
1e-2,
"intersection_tyr_intI")
one_integrase_one_attC.add_attC(10,
100,
1,
1e-2,
"intersection_tyr_intI")
self.assertEqual(one_integrase_one_attC.type(), "complete")
def test_annot_calin_empty(self):
"""
Test func_annot when the integron is a CALIN (attC but no integrase), without any protein:
nothing to annotate
"""
# Create integron
integron1 = Integron(self.replicon, self.cfg)
integrons = [integron1]
# Add only attc sites (no integrase)
integron1.add_attC(17825, 17884, -1, 7e-9, "attc_4")
integron1.add_attC(19080, 19149, -1, 7e-4, "attc_4")
integron1.add_attC(19618, 19726, -1, 7e-7, "attc_4")
# check proteins before annotation
proteins = pd.DataFrame(columns=["pos_beg", "pos_end", "strand",
"evalue", "type_elt", "model",
"distance_2attC", "annotation"])
proteins = proteins.astype(dtype={"pos_beg": "int", "pos_end": "int", "strand": "int",
"evalue": "float", "type_elt": "str", "model": "str",
"distance_2attC": "float", "annotation": "str"})
pdt.assert_frame_equal(proteins, integron1.proteins)
# Annotate proteins
func_annot(integrons, self.replicon, self.prot_db, self.hmm_files, self.cfg, self.tmp_dir)
# Check that all files generated are as expected
files_created = [f for f in glob.glob(os.path.join(self.tmp_dir, "*")) if os.path.isfile(f)]
exp_files = ["{}{}".format(self.replicon.id, suffix) for suffix in ("_intI_table.res",
"_phage_int_table.res",
"_intI.res",
"_phage_int.res")]
exp_files = [os.path.join(self.tmp_dir, file) for file in exp_files]
self.assertEqual(set(exp_files), set(files_created))
# Check proteins after annotation
pdt.assert_frame_equal(proteins, integron1.proteins)
def test_annot_multi(self):
"""
Test func_annot when there are 4 integrons:
- 1 calin with 4 proteins, 2 having a resfam annotation
- 1 calin with 2 proteins, none having a resfam annotation
- 1 in0
- 1 complete with 4 proteins, 3 having a resfam annotation
"""
# resfam pour: 16, 13, 3, 12
# Create integron in0
integron1 = Integron(self.replicon.name, self.cfg)
integron1.add_integrase(56, 1014, "ACBA.007.P01_13_1", 1, 1.9e-25, "intersection_tyr_intI")
# Create integron CALIN with resfam proteins
integron2 = Integron(self.replicon, self.cfg)
integron2.add_attC(7400, 7650, -1, 7e-9, "attc_4")
integron2.add_attC(8600, 8650, -1, 7e-4, "attc_4")
integron2.add_attC(10200, 10400, -1, 7e-7, "attc_4")
integron2.add_attC(10800, 10900, -1, 7e-7, "attc_4")
integron2.add_proteins(self.prot_db)
# Create integron CALIN without any resfam proteins
integron3 = Integron(self.replicon, self.cfg)
integron3.add_attC(4320, 4400, -1, 7e-9, "attc_4")
integron3.add_proteins(self.prot_db)
# Create complete integron
integron4 = Integron(self.replicon, self.cfg)
integron4.add_attC(17825, 17884, -1, 7e-9, "attc_4")
integron4.add_attC(19080, 19149, -1, 7e-4, "attc_4")
integron4.add_attC(19618, 19726, -1, 7e-7, "attc_4")
integron4.add_integrase(16542, 17381, "ACBA.007.P01_13_19", -1, 1.9e-25, "intersection_tyr_intI")
integron4.add_proteins(self.prot_db)
integrons = [integron1, integron2, integron3, integron4]
# Create dataframes for expected proteins before annotation
proteins1 = pd.DataFrame(columns=["pos_beg", "pos_end", "strand",
"evalue", "type_elt", "model",
"distance_2attC", "annotation"])
proteins1 = proteins1.astype(dtype={"pos_beg": "int", "pos_end": "int", "strand": "int",
"evalue": "float", "type_elt": "str", "model": "str",
"distance_2attC": "float", "annotation": "str"})
proteins1 = proteins1[["pos_beg", "pos_end", "strand", "evalue", "type_elt",
"model", "distance_2attC", "annotation"]]
proteins1 = proteins1.astype(dtype=self.prot_dtype)
proteins2 = pd.DataFrame({"pos_beg": [7088, 7710, 8650, 10524],
"pos_end": [7351, 8594, 10125, 11699],
"strand": [1, -1, -1, -1],
"evalue": [np.nan] * 4,
"type_elt": ["protein"] * 4,
"model": ["NA"] * 4,
"distance_2attC": [np.nan] * 4,
"annotation": ["protein"] * 4},
index=["ACBA.007.P01_13_11", "ACBA.007.P01_13_12",
"ACBA.007.P01_13_13", "ACBA.007.P01_13_14"])
proteins2 = proteins2[["pos_beg", "pos_end", "strand", "evalue", "type_elt",
"model", "distance_2attC", "annotation"]]
proteins2 = proteins2.astype(dtype=self.prot_dtype)
proteins3 = pd.DataFrame({"pos_beg": [3546, 4380],
"pos_end": [4313, 4721],
"strand": [1, 1],
"evalue": [np.nan] * 2,
"type_elt": ["protein"] * 2,
"model": ["NA"] * 2,
"distance_2attC": [np.nan] * 2,
"annotation": ["protein"] * 2},
index=["ACBA.007.P01_13_6", "ACBA.007.P01_13_7"])
proteins3 = proteins3[["pos_beg", "pos_end", "strand", "evalue", "type_elt",
"model", "distance_2attC", "annotation"]]
proteins3 = proteins3.astype(dtype=self.prot_dtype)
proteins4 = pd.DataFrame({"pos_beg": [17375, 17886, 19090, 19721],
"pos_end": [17722, 18665, 19749, 20254],
"strand": [-1] * 4,
"evalue": [np.nan] * 4,
"type_elt": ["protein"] * 4,
"model": ["NA"] * 4,
"distance_2attC": [np.nan] * 4,
"annotation": ["protein"] * 4},
index=["ACBA.007.P01_13_20", "ACBA.007.P01_13_21",
"ACBA.007.P01_13_22", "ACBA.007.P01_13_23"])
proteins4 = proteins4[["pos_beg", "pos_end", "strand", "evalue", "type_elt",
"model", "distance_2attC", "annotation"]]
proteins4 = proteins4.astype(dtype=self.prot_dtype)
# Check proteins before annotation
expected_proteins = [proteins1, proteins2, proteins3, proteins4]
for inte, exp_prot in zip(integrons, expected_proteins):
# we need to sort the dataframe
# as protein file is parse using biopython and index
# the order os sequences is not guarantee
pdt.assert_frame_equal(inte.proteins.sort_index(), exp_prot.sort_index())
# Annotate proteins with evalue threshold
func_annot(integrons, self.replicon, self.prot_db, self.hmm_files, self.cfg, self.tmp_dir, evalue=1e-32)
# Check that all files generated are as expected
files_created = [f for f in glob.glob(os.path.join(self.tmp_dir, "*")) if os.path.isfile(f)]
self.assertEqual(set(self.exp_files), set(files_created))
# Check that annotated proteins are as expected
proteins2.loc["ACBA.007.P01_13_13"] = [8650, 10125, -1, 2.4e-86, "protein",
"RF0007", np.nan, "ABC_efflux"]
proteins4.loc["ACBA.007.P01_13_21"] = [17886, 18665, -1, 7.4e-168, "protein",
"RF0027", np.nan, "ANT3"]
proteins4.loc["ACBA.007.P01_13_23"] = [19721, 20254, -1, 6.2e-110, "protein",
"RF0003", np.nan, "AAC3-I"]
for inte, prots in zip(integrons, expected_proteins):
# we need to sort the dataframe
# as protein file is parse using biopython and index
# the order os sequences is not guarantee
pdt.assert_frame_equal(inte.proteins.sort_index(), prots.sort_index())
# Annotate proteins with default evalue (1 more annotation)
with self.catch_io(out=True):
func_annot(integrons, self.replicon, self.prot_db, self.hmm_files, self.cfg, self.tmp_dir)
proteins4.loc["ACBA.007.P01_13_20"] = [17375, 17722, -1, 4.5e-31, "protein",
"RF0066", np.nan, "emrE"]
for inte, prots in zip(integrons, expected_proteins):
pdt.assert_frame_equal(inte.proteins.sort_index(), prots.sort_index())
# Annotate proteins with lower coverage threshold (1 more annotation)
with self.catch_io(out=True):
func_annot(integrons, self.replicon, self.prot_db, self.hmm_files, self.cfg, self.tmp_dir, coverage=0.4)
proteins2.loc["ACBA.007.P01_13_12"] = [7710, 8594, -1, 1.6e-5, "protein",
"RF0033", np.nan, "APH3"]
for inte, prots in zip(integrons, expected_proteins):
pdt.assert_frame_equal(inte.proteins.sort_index(), prots.sort_index())