def main(input_file, out, reference, ambiguous):
"""Calculate allele frequencies from the given input multialignment.
Input can be either a fasta or csv file with multialigned sequences,
which may or may not contain the reference sequence in the first
position. In the latter case, an additional reference sequence file
is needed, either in fasta or csv format.
"""
input_ext = input_file.split(".")[-1]
if input_ext == "fasta":
a = AlleleFreqs.from_fasta(input_file, reference, ambiguous)
elif input_ext == "csv":
a = AlleleFreqs.from_csv(input_file, reference, ambiguous)
else:
click.echo("Input not recognised. "
"Please provide either a fasta or csv file.")
return 1
a.to_csv(out)
click.echo(f"Allele frequencies saved to {out}.")
return 0
def setUp(self) -> None:
self.af = AlleleFreqs.from_fasta(sequences=REAL_ALG_L6_NOREF_FASTA,
reference=REAL_RSRS_FASTA)
def setUp(self) -> None:
ref = Reference("AAG-CTNGGGCATTTCAGGGTGAGCCCGGGCAATACAGGG-TAT")
alg = MultiAlignment(SAMPLE_SEQUENCES_DICT)
self.af = AlleleFreqs(multialg=alg, reference=ref)
self.af_amb = AlleleFreqs(multialg=alg, reference=ref, ambiguous=True)
def setUp(self) -> None:
self.af = AlleleFreqs.from_fasta(sequences=REAL_ALG_L6_FASTA)
def setUp(self) -> None:
self.af = AlleleFreqs.from_csv(sequences=SAMPLE_MULTIALG_NOREF_CSV,
reference=SAMPLE_REF_CSV)
class TestBasic(unittest.TestCase):
def setUp(self) -> None:
ref = Reference("AAG-CTNGGGCATTTCAGGGTGAGCCCGGGCAATACAGGG-TAT")
alg = MultiAlignment(SAMPLE_SEQUENCES_DICT)
self.af = AlleleFreqs(multialg=alg, reference=ref)
self.af_amb = AlleleFreqs(multialg=alg, reference=ref, ambiguous=True)
def test_df(self):
# Given/When
exp_df = sample_sequences_df()
# Then
pdtest.assert_frame_equal(self.af.df, exp_df)
def test_frequencies(self):
# Given/When
exp_freqs = sample_sequences_freqs()
# Then
pdtest.assert_frame_equal(self.af.frequencies, exp_freqs)
def test_frequencies_ambiguous(self):
# Given/When
exp_freqs = sample_sequences_freqs_amb()
# Then
pdtest.assert_frame_equal(self.af_amb.frequencies, exp_freqs)
def test__get_frequencies(self):
# Given
test_freq = pd.Series({
'A': 0.2,
'C': 0.2,
'G': 0.1,
'T': 0.3,
'-': 0.1,
'N': 0.1
})
exp_freq = {
'A': 0.2,
'C': 0.2,
'G': 0.1,
'T': 0.3,
'gap': 0.1,
'oth': 0.1
}
# When
result = self.af._get_frequencies(test_freq)
# Then
self._dict_almost_equal(result, exp_freq)
def test_to_csv(self):
# Given/When
self.af.to_csv(TEST_CSV)
result = pd.read_csv(TEST_CSV)
expected = pd.read_csv(SAMPLE_FREQUENCIES)
# Then
pdtest.assert_frame_equal(result, expected)
def test_to_csv_ambiguous(self):
# Given/When
self.af_amb.to_csv(TEST_CSV)
result = pd.read_csv(TEST_CSV)
expected = pd.read_csv(SAMPLE_FREQUENCIES_AMB)
# Then
pdtest.assert_frame_equal(result, expected)
@staticmethod
def _dict_almost_equal(expected: dict, result: dict, acc=10**-8) -> bool:
"""Compare to dictionaries and ensure that all their values are the
same, accounting for some fluctuation up to the given accuracy value.
Args:
expected: expected dictionary
result: resulting dictionary
acc: accuracy to use [default: 10**-8]
"""
if expected.keys() == result.keys():
for key in expected.keys():
if abs(expected[key] - result[key]) < acc:
continue
return True
return False
def setUp(self) -> None:
self.af = AlleleFreqs.from_csv(sequences=SAMPLE_MULTIALG_CSV)
def setUp(self) -> None:
self.af = AlleleFreqs.from_fasta(sequences=SAMPLE_MULTIALG_NOREF_FASTA,
reference=SAMPLE_REF_FASTA)
def setUp(self) -> None:
self.af = AlleleFreqs.from_fasta(sequences=SAMPLE_MULTIALG_FASTA)