def test_read_hmm(self):
"""
Test that the hmm hits are well read
"""
infile = os.path.join("tests", "data", "Results_Integron_Finder_" + self.rep_name,
"other", self.rep_name + "_intI.res")
df = integron_finder.read_hmm(self.rep_name, infile)
exp = pd.DataFrame(data={"Accession_number": self.rep_name, "query_name": "intI_Cterm",
"ID_query": "-", "ID_prot": "ACBA.007.P01_13_1", "strand": 1,
"pos_beg": 55, "pos_end": 1014, "evalue": 1.9e-25},
index=[0])
exp = exp[["Accession_number", "query_name", "ID_query", "ID_prot",
"strand", "pos_beg", "pos_end", "evalue"]]
pdt.assert_frame_equal(df, exp)
def test_read_hmm_cov(self):
"""
Test that the hmm hits are well read, and returned only if coverage is > to the
given threshold.
"""
infile = os.path.join("tests", "data", "Results_Integron_Finder_" + self.rep_name,
"other", self.rep_name + "_intI.res")
df1 = integron_finder.read_hmm(self.rep_name, infile, coverage=0.945)
exp1 = pd.DataFrame(data={"Accession_number": self.rep_name, "query_name": "intI_Cterm",
"ID_query": "-", "ID_prot": "ACBA.007.P01_13_1", "strand": 1,
"pos_beg": 55, "pos_end": 1014, "evalue": 1.9e-25},
index=[0])
exp1 = exp1[["Accession_number", "query_name", "ID_query", "ID_prot",
"strand", "pos_beg", "pos_end", "evalue"]]
pdt.assert_frame_equal(df1, exp1)
df2 = integron_finder.read_hmm(self.rep_name, infile, coverage=0.95)
exp2 = pd.DataFrame(columns=["Accession_number", "query_name", "ID_query", "ID_prot",
"strand", "pos_beg", "pos_end", "evalue"])
intcols = ["pos_beg", "pos_end", "strand"]
floatcol = ["evalue"]
exp2[intcols] = exp2[intcols].astype(int)
exp2[floatcol] = exp2[floatcol].astype(float)
pdt.assert_frame_equal(df2, exp2)
def test_read_empty(self):
"""
Test that when there are no hits in the hmm result file, it returns an empty
dataframe, without error.
"""
infile = os.path.join("tests", "data", "fictive_results",
self.rep_name + "_intI-empty.res")
df = integron_finder.read_hmm(self.rep_name, infile)
exp = pd.DataFrame(columns=["Accession_number", "query_name", "ID_query", "ID_prot",
"strand", "pos_beg", "pos_end", "evalue"])
intcols = ["pos_beg", "pos_end", "strand"]
floatcol = ["evalue"]
exp[intcols] = exp[intcols].astype(int)
exp[floatcol] = exp[floatcol].astype(float)
pdt.assert_frame_equal(df, exp)
def test_read_hmm_gembase(self):
"""
Test that the hmm hits are well read, when the gembase format is used (.prt file is
provided, prodigal is not used to find the proteins).
"""
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument("--gembase", help="gembase format", action="store_true")
args = parser.parse_args(["--gembase"])
integron_finder.args = args
infile = os.path.join("tests", "data", "fictive_results", self.rep_name +
"_intI-gembase.res")
df = integron_finder.read_hmm(self.rep_name, infile)
exp = pd.DataFrame(data={"Accession_number": self.rep_name, "query_name": "intI_Cterm",
"ID_query": "-", "ID_prot": "ACBA007p01a_000009", "strand": 1,
"pos_beg": 55, "pos_end": 1014, "evalue": 1.9e-25},
index=[0])
exp = exp[["Accession_number", "query_name", "ID_query", "ID_prot",
"strand", "pos_beg", "pos_end", "evalue"]]
pdt.assert_frame_equal(df, exp)
def test_read_hmm_cov2(self):
"""
Test that the hmm hits are well read, it returns only the hits with coverage >
given threshold
"""
infile = os.path.join("tests", "data", "fictive_results",
self.rep_name + "_intI.res")
df1 = integron_finder.read_hmm(self.rep_name, infile, coverage=0.7)
exp1 = pd.DataFrame(data={"Accession_number": [self.rep_name] * 2,
"query_name": ["intI_Cterm"] * 2,
"ID_query": ["-", "-"],
"ID_prot": ["ACBA.007.P01_13_1", "ACBA.007.P01_13_2"],
"strand": [1, 1],
"pos_beg": [55, 2000], "pos_end": [1014, 2500],
"evalue": [1.9e-25, 1e-3]},
index=[0, 1])
exp1 = exp1[["Accession_number", "query_name", "ID_query", "ID_prot",
"strand", "pos_beg", "pos_end", "evalue"]]
pdt.assert_frame_equal(df1, exp1)
def test_read_multi(self):
"""
Test reading hmm results when there are multiple hits: 2 hits on the same protein: keep
only the one with the best evalue. 2 hits on 2 different proteins: keep the 2 proteins.
"""
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument("--gembase", help="gembase format", action="store_true")
args = parser.parse_args(["--gembase"])
integron_finder.args = args
infile = os.path.join("tests", "data", "fictive_results", self.rep_name +
"_intI-multi.res")
df = integron_finder.read_hmm(self.rep_name, infile)
exp = pd.DataFrame(data={"Accession_number": [self.rep_name] * 2,
"query_name": ["intI_Cterm"] * 2, "ID_query": ["-"] * 2,
"ID_prot": ["ACBA007p01a_000009", "ACBA007p01a_000008"],
"strand": [1, -1],
"pos_beg": [55, 1], "pos_end": [1014, 50],
"evalue": [4.5e-25, 2.3e-25]},
index=[0, 1])
exp = exp[["Accession_number", "query_name", "ID_query", "ID_prot",
"strand", "pos_beg", "pos_end", "evalue"]]
pdt.assert_frame_equal(df, exp)
