def test_init():
"""test init"""
gtyper = genotyper.Genotyper(0, 20, 0.0001)
assert gtyper.min_cov_more_than_error == 0
assert gtyper.no_of_successes == 0
assert gtyper.prob_of_success == 0
gtyper = genotyper.Genotyper(10, 20, 0.0001)
assert gtyper.no_of_successes == 10
assert gtyper.prob_of_success == 0.5
assert gtyper.min_cov_more_than_error == 1
gtyper = genotyper.Genotyper(10, 20, 0.01)
assert gtyper.no_of_successes == 10
assert gtyper.prob_of_success == 0.5
assert gtyper.min_cov_more_than_error == 2
gtyper = genotyper.Genotyper(100, 200, 0.001)
assert gtyper.no_of_successes == 100
assert gtyper.prob_of_success == 0.5
assert gtyper.min_cov_more_than_error == 8
# variance < mean, so will hit the code where it forces
# variance = 2 * mean = 20
gtyper = genotyper.Genotyper(10, 5, 0.01)
assert gtyper.no_of_successes == 10
assert gtyper.prob_of_success == 0.5
assert gtyper.min_cov_more_than_error == 2
def _simulate_confidence_scores(cls, mean_depth, depth_variance, error_rate, iterations, allele_length=1, seed=42):
np.random.seed(seed)
allele_groups_dict = {'1': {0}, '2': {1}}
i = 0
confidences = []
# We can't use the negative binomial unless depth_variance > mean_depth.
# So force it to be so.
if depth_variance < mean_depth:
depth_variance = 2 * mean_depth
logging.warn('Variance in read depth is smaller than mean read depth. Setting variance = 2 * mean, so that variant simulations can run. GT_CONF_PERCENTILE in the output VCF file may not be very useful as a result of this.')
no_of_successes = (mean_depth ** 2) / (depth_variance - mean_depth)
prob_of_success = 1 - (depth_variance - mean_depth) / depth_variance
while i < iterations:
correct_coverage = np.random.negative_binomial(no_of_successes, prob_of_success)
incorrect_coverage = np.random.binomial(mean_depth, error_rate)
if correct_coverage + incorrect_coverage == 0:
continue
allele_combination_cov = {}
if incorrect_coverage > 0:
allele_combination_cov['1'] = incorrect_coverage
if correct_coverage > 0:
allele_combination_cov['2'] = correct_coverage
allele_per_base_cov = [[incorrect_coverage] * allele_length, [correct_coverage] * allele_length]
gtyper = genotyper.Genotyper(mean_depth, error_rate, allele_combination_cov, allele_per_base_cov, allele_groups_dict)
gtyper.run()
confidences.append(round(gtyper.genotype_confidence))
i += 1
assert len(confidences) == iterations
confidences.sort()
return confidences
def test_log_likelihood_homozygous():
"""test _log_likelihood_homozygous"""
gtyper = genotyper.Genotyper(100, 200, 0.01)
allele_depth = 90
total_depth = 95
allele_length = 5
non_zeros = allele_length
got = gtyper._log_likelihood_homozygous(allele_depth, total_depth,
allele_length, non_zeros)
assert round(got, 2) == -26.78
gtyper = genotyper.Genotyper(10, 200, 0.01)
allele_depth = 1
total_depth = 9
got = gtyper._log_likelihood_homozygous(allele_depth, total_depth,
allele_length, non_zeros)
assert round(got, 2) == -39.34
def test_run_zero_coverage():
"""test run when all alleles have zero coverage"""
gtyper = genotyper.Genotyper(20, 40, 0.01)
allele_combination_cov = {}
allele_groups_dict = {"1": {0}, "2": {1}, "3": {0, 1}, "4": {2}}
allele_per_base_cov = [[0], [0, 0]]
gtyper.run(allele_combination_cov, allele_per_base_cov, allele_groups_dict)
assert gtyper.genotype == {"."}
assert gtyper.genotype_confidence == 0.0
assert gtyper.genotype_frs == "."
def test_run_zero_coverage(self):
'''test run when all alleles have zero coverage'''
mean_depth = 20
error_rate = 0.01
allele_combination_cov = {}
allele_groups_dict = {'1': {0}, '2': {1}, '3': {0, 1}, '4': {2}}
allele_per_base_cov = [[0], [0, 0]]
gtyper = genotyper.Genotyper(mean_depth, error_rate,
allele_combination_cov,
allele_per_base_cov, allele_groups_dict)
gtyper.run()
self.assertEqual({'.'}, gtyper.genotype)
self.assertEqual(0.0, gtyper.genotype_confidence)
def test_nomatherror_mean_depth0():
"""
Can get a mean_depth of zero but try to genotype a non-zero coverage site due to rounding imprecision.
In which case we need to avoid trying to do log(0) in likelihood calculation and should return no call.
"""
gtyper = genotyper.Genotyper(0, 0, 0.01)
allele_combination_cov = {"1": 1}
allele_groups_dict = {"1": {0}, "2": {1}}
allele_per_base_cov = [[1], [0, 0]]
gtyper.run(allele_combination_cov, allele_per_base_cov, allele_groups_dict)
assert gtyper.genotype == {"."}
assert gtyper.genotype_confidence == 0.0
assert gtyper.genotype_frs == "."
def _simulate_confidence_scores(
cls,
mean_depth,
depth_variance,
error_rate,
iterations,
allele_length=1,
seed=42,
call_hets=False,
):
np.random.seed(seed)
allele_groups_dict = {"1": {0}, "2": {1}}
i = 0
confidences = []
gtyper = genotyper.Genotyper(
mean_depth, depth_variance, error_rate, call_hets=call_hets,
)
logging.debug(
"Simulation:\titeration\tcorrect_coverage\tincorrect_coverage\tgenotype_confidence"
)
while i < iterations:
correct_coverage = np.random.negative_binomial(
gtyper.no_of_successes, gtyper.prob_of_success
)
incorrect_coverage = np.random.binomial(mean_depth, error_rate)
if correct_coverage + incorrect_coverage == 0:
continue
allele_combination_cov = {}
if incorrect_coverage > 0:
allele_combination_cov["1"] = incorrect_coverage
if correct_coverage > 0:
allele_combination_cov["2"] = correct_coverage
allele_per_base_cov = [
[incorrect_coverage] * allele_length,
[correct_coverage] * allele_length,
]
gtyper.run(allele_combination_cov, allele_per_base_cov, allele_groups_dict)
logging.debug(
f"Simulation:\t{i}\t{correct_coverage}\t{incorrect_coverage}\t{gtyper.genotype_confidence}"
)
confidences.append(round(gtyper.genotype_confidence))
i += 1
assert len(confidences) == iterations
confidences.sort()
return confidences
def test_run():
"""test run"""
gtyper = genotyper.Genotyper(20, 40, 0.01)
allele_combination_cov = {"1": 2, "2": 20, "3": 1}
allele_groups_dict = {"1": {0}, "2": {1}, "3": {0, 1}, "4": {2}}
allele_per_base_cov = [[0, 1], [20, 19]]
gtyper.run(allele_combination_cov, allele_per_base_cov, allele_groups_dict)
depth0 = round(3 / 23, 4)
depth1 = round(21 / 23, 4)
expected = [({1}, -12.03, depth1), ({0}, -114.57, depth0)]
assert len(gtyper.likelihoods) == len(expected)
for i in range(len(expected)):
assert gtyper.likelihoods[i][0] == expected[i][0]
assert round(gtyper.likelihoods[i][1], 2) == round(expected[i][1], 2)
assert gtyper.likelihoods[i][2] == expected[i][2]
def test_run_zero_coverage(self):
"""test run when all alleles have zero coverage"""
mean_depth = 20
error_rate = 0.01
allele_combination_cov = {}
allele_groups_dict = {"1": {0}, "2": {1}, "3": {0, 1}, "4": {2}}
allele_per_base_cov = [[0], [0, 0]]
gtyper = genotyper.Genotyper(
mean_depth,
error_rate,
allele_combination_cov,
allele_per_base_cov,
allele_groups_dict,
)
gtyper.run()
self.assertEqual({"."}, gtyper.genotype)
self.assertEqual(0.0, gtyper.genotype_confidence)
def test_calculate_log_likelihoods(self):
'''test _calculate_log_likelihoods'''
mean_depth = 20
error_rate = 0.01
allele_combination_cov = {'1': 2, '2': 20, '3': 1}
allele_groups_dict = {'1': {0}, '2': {1}, '3': {0, 1}, '4': {2}}
allele_per_base_cov = [[0, 1], [20, 19]]
gtyper = genotyper.Genotyper(mean_depth, error_rate,
allele_combination_cov,
allele_per_base_cov, allele_groups_dict)
gtyper._calculate_log_likelihoods()
expected = [
({1}, -11.68),
({0, 1}, -22.92),
({0}, -124.91),
]
self.assertEqual(3, len(gtyper.likelihoods))
gtyper.likelihoods = [(x[0], round(x[1], 2))
for x in gtyper.likelihoods]
self.assertEqual(expected, gtyper.likelihoods)
def test_nomatherror_mean_depth0(self):
"""
Can get a mean_depth of zero but try to genotype a non-zero coverage site due to rounding imprecision.
In which case we need to avoid trying to do log(0) in likelihood calculation and should return no call.
"""
mean_depth = 0
error_rate = 0.01
allele_combination_cov = {"1": 1}
allele_groups_dict = {"1": {0}, "2": {1}}
allele_per_base_cov = [[1], [0, 0]]
gtyper = genotyper.Genotyper(
mean_depth,
error_rate,
allele_combination_cov,
allele_per_base_cov,
allele_groups_dict,
)
gtyper.run()
self.assertEqual({"."}, gtyper.genotype)
self.assertEqual(0.0, gtyper.genotype_confidence)
def test_run(self):
'''test run'''
mean_depth = 20
error_rate = 0.01
allele_combination_cov = {'1': 2, '2': 20, '3': 1}
allele_groups_dict = {'1': {0}, '2': {1}, '3': {0, 1}, '4': {2}}
allele_per_base_cov = [[0, 1], [20, 19]]
gtyper = genotyper.Genotyper(mean_depth, error_rate,
allele_combination_cov,
allele_per_base_cov, allele_groups_dict)
expected = [
({1}, -11.68),
({0, 1}, -22.92),
({0}, -124.91),
]
gtyper.run()
self.assertEqual(len(expected), len(gtyper.likelihoods))
for i in range(len(expected)):
self.assertEqual(expected[i][0], gtyper.likelihoods[i][0])
self.assertAlmostEqual(expected[i][1],
gtyper.likelihoods[i][1],
places=2)
def test_calculate_log_likelihoods():
"""test _calculate_log_likelihoods"""
gtyper = genotyper.Genotyper(20, 40, 0.01)
allele_combination_cov = {"1": 2, "2": 20, "3": 1}
allele_groups_dict = {"1": {0}, "2": {1}, "3": {0, 1}, "4": {2}}
allele_per_base_cov = [[0, 1], [20, 19]]
depth0 = round(3 / 23, 4)
depth01 = 1
depth1 = round(21 / 23, 4)
gtyper._init_alleles_and_genotypes(
allele_combination_cov=allele_combination_cov,
allele_per_base_cov=allele_per_base_cov,
allele_groups_dict=allele_groups_dict,
)
gtyper._calculate_log_likelihoods()
assert len(gtyper.likelihoods) == 2
expected = [
({1}, -12.03, depth1),
({0}, -114.57, depth0),
]
gtyper.likelihoods = [(x[0], round(x[1], 2), x[2])
for x in gtyper.likelihoods]
assert gtyper.likelihoods == expected
def update_vcf_record_using_gramtools_allele_depths(
vcf_record,
allele_combination_cov,
allele_per_base_cov,
allele_groups_dict,
mean_depth,
read_error_rate,
min_cov_more_than_error=None,
):
"""allele_depths should be a dict of allele -> coverage.
The REF allele must also be in the dict.
So keys of dict must be equal to REF + ALTs sequences.
This also changes all columns from QUAL onwards.
Returns a VcfRecord the same as vcf_record, but with all zero
coverage alleles removed, and GT and COV fixed accordingly"""
gtyper = genotyper.Genotyper(
mean_depth,
read_error_rate,
allele_combination_cov,
allele_per_base_cov,
allele_groups_dict,
min_cov_more_than_error=min_cov_more_than_error,
)
gtyper.run()
genotype_indexes = set()
if "." in gtyper.genotype:
genotype = "./."
else:
if 0 in gtyper.genotype:
genotype_indexes.add(0)
for i in range(len(vcf_record.ALT)):
if i + 1 in gtyper.genotype:
genotype_indexes.add(i + 1)
if len(genotype_indexes) == 1:
genotype_index = genotype_indexes.pop()
genotype = str(genotype_index) + "/" + str(genotype_index)
genotype_indexes.add(genotype_index)
else:
genotype = "/".join(
[str(x) for x in sorted(list(genotype_indexes))])
cov_values = [
gtyper.singleton_allele_coverages.get(x, 0)
for x in range(1 + len(vcf_record.ALT))
]
cov_string = ",".join([str(x) for x in cov_values])
vcf_record.QUAL = None
vcf_record.INFO.clear()
vcf_record.FILTER = set()
vcf_record.FORMAT.clear()
vcf_record.set_format_key_value("DP",
str(sum(allele_combination_cov.values())))
vcf_record.set_format_key_value("GT", genotype)
vcf_record.set_format_key_value("COV", cov_string)
vcf_record.set_format_key_value("GT_CONF", str(gtyper.genotype_confidence))
# Make new record where all zero coverage alleles are removed
filtered_record = copy.deepcopy(vcf_record)
if genotype in ["./.", "0/0"]:
return filtered_record
indexes_to_keep = set(
[i for i in range(len(cov_values)) if i == 0 or cov_values[i] > 0])
indexes_to_keep.update(genotype_indexes)
indexes_to_keep = list(indexes_to_keep)
indexes_to_keep.sort()
filtered_record.set_format_key_value(
"COV", ",".join([str(cov_values[i]) for i in indexes_to_keep]))
assert indexes_to_keep[0] == 0
filtered_record.ALT = [
filtered_record.ALT[i - 1] for i in indexes_to_keep[1:]
]
# The indexes of the genotype string 'n/m' are shifted because
# we probably removed some alleles
genotype_strings = {
vcf_record.REF if i == 0 else vcf_record.ALT[i - 1]
for i in genotype_indexes
}
new_genotype_indexes = set()
if 0 in genotype_indexes:
new_genotype_indexes.add(0)
for i, genotype_string in enumerate(filtered_record.ALT):
if genotype_string in genotype_strings:
new_genotype_indexes.add(i + 1)
if len(genotype_strings) == len(new_genotype_indexes):
break
new_genotype_indexes = list(new_genotype_indexes)
if len(new_genotype_indexes) == 1:
new_genotype_indexes.append(new_genotype_indexes[0])
assert len(new_genotype_indexes) == 2
filtered_record.set_format_key_value(
"GT", "/".join([str(x) for x in new_genotype_indexes]))
return filtered_record
def write_vcf_annotated_using_coverage_from_gramtools(
mean_depth,
depth_variance,
vcf_records,
all_allele_coverage,
allele_groups,
read_error_rate,
outfile,
sample_name="SAMPLE",
filtered_outfile=None,
ref_seq_lengths=None,
call_hets=False,
):
"""mean_depth, vcf_records, all_allele_coverage, allele_groups should be those
returned by load_gramtools_vcf_and_allele_coverage_files().
Writes a new VCF that has allele counts for all the ALTs"""
assert len(vcf_records) == len(all_allele_coverage)
if call_hets:
raise NotImplementedError("Heterozygous calling is not implemented")
header_lines = [
"##fileformat=VCFv4.2",
"##source=minos, version " + minos_version,
"##fileDate=" + str(datetime.date.today()),
'##FORMAT=<ID=COV,Number=R,Type=Integer,Description="Number of reads on ref and alt alleles">',
'##FORMAT=<ID=FRS,Number=1,Type=Float,Description="Fraction of reads that support the genotype call">',
'##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">',
'##FORMAT=<ID=DP,Number=1,Type=Integer,Description="total read depth from gramtools">',
'##FORMAT=<ID=DPF,Number=1,Type=Float,Description="Depth Fraction, defined as DP divided by mean depth">',
'##FORMAT=<ID=GT_CONF,Number=1,Type=Float,Description="Genotype confidence. Difference in log likelihood of most likely and next most likely genotype">',
f"##minosMeanReadDepth={mean_depth}",
]
if ref_seq_lengths is not None:
for name, length in sorted(ref_seq_lengths.items()):
header_lines.append(f"##contig=<ID={name},length={length}>")
header_lines.append(
"\t".join(
[
"#CHROM",
"POS",
"ID",
"REF",
"ALT",
"QUAL",
"FILTER",
"INFO",
"FORMAT",
sample_name,
]
)
)
gtyper = genotyper.Genotyper(
mean_depth, depth_variance, read_error_rate, call_hets=call_hets,
)
if filtered_outfile is not None:
f_filter = open(filtered_outfile, "w")
print(*header_lines, sep="\n", file=f_filter)
with open(outfile, "w") as f:
print(*header_lines, sep="\n", file=f)
for i in range(len(vcf_records)):
logging.debug("Genotyping: " + str(vcf_records[i]))
filtered_record = update_vcf_record_using_gramtools_allele_depths(
vcf_records[i],
gtyper,
all_allele_coverage[i][0],
all_allele_coverage[i][1],
allele_groups,
)
print(vcf_records[i], file=f)
if filtered_outfile is not None:
print(filtered_record, file=f_filter)
if filtered_outfile is not None:
f_filter.close()
def update_vcf_record_using_gramtools_allele_depths(
vcf_record, allele_combination_cov, allele_per_base_cov,
allele_groups_dict, mean_depth, read_error_rate, kmer_size):
'''allele_depths should be a dict of allele -> coverage.
The REF allele must also be in the dict.
So keys of dict must be equal to REF + ALTs sequences.
This also changes all columns from QUAL onwards.
Returns a VcfRecord the same as vcf_record, but with all zero
coverage alleles removed, and GT and COV fixed accordingly'''
gtyper = genotyper.Genotyper(mean_depth, read_error_rate,
allele_combination_cov, allele_per_base_cov,
allele_groups_dict)
gtyper.run()
genotype_indexes = set()
if '.' in gtyper.genotype:
genotype = './.'
else:
if 0 in gtyper.genotype:
genotype_indexes.add(0)
for i in range(len(vcf_record.ALT)):
if i + 1 in gtyper.genotype:
genotype_indexes.add(i + 1)
if len(genotype_indexes) == 1:
genotype_index = genotype_indexes.pop()
genotype = str(genotype_index) + '/' + str(genotype_index)
genotype_indexes.add(genotype_index)
else:
genotype = '/'.join(
[str(x) for x in sorted(list(genotype_indexes))])
cov_values = [
gtyper.singleton_alleles_cov.get(x, 0)
for x in range(1 + len(vcf_record.ALT))
]
cov_string = ','.join([str(x) for x in cov_values])
vcf_record.QUAL = None
vcf_record.FILTER = '.'
vcf_record.INFO = {'KMER': str(kmer_size)}
vcf_record.format_keys = ['DP', 'GT', 'COV', 'GT_CONF']
vcf_record.FORMAT = {
'DP': str(sum(allele_combination_cov.values())),
'GT': genotype,
'COV': cov_string,
'GT_CONF': str(gtyper.genotype_confidence)
}
# Make new record where all zero coverage alleles are removed
filtered_record = copy.deepcopy(vcf_record)
if genotype in ['./.', '0/0']:
return filtered_record
indexes_to_keep = set(
[i for i in range(len(cov_values)) if i == 0 or cov_values[i] > 0])
indexes_to_keep.update(genotype_indexes)
indexes_to_keep = list(indexes_to_keep)
indexes_to_keep.sort()
filtered_record.FORMAT['COV'] = ','.join(
[str(cov_values[i]) for i in indexes_to_keep])
assert indexes_to_keep[0] == 0
filtered_record.ALT = [
filtered_record.ALT[i - 1] for i in indexes_to_keep[1:]
]
# The indexes of the genotype string 'n/m' are shifted because
# we probably removed some alleles
genotype_strings = {
vcf_record.REF if i == 0 else vcf_record.ALT[i - 1]
for i in genotype_indexes
}
new_genotype_indexes = set()
if 0 in genotype_indexes:
new_genotype_indexes.add(0)
for i, genotype_string in enumerate(filtered_record.ALT):
if genotype_string in genotype_strings:
new_genotype_indexes.add(i + 1)
if len(genotype_strings) == len(new_genotype_indexes):
break
new_genotype_indexes = list(new_genotype_indexes)
if len(new_genotype_indexes) == 1:
new_genotype_indexes.append(new_genotype_indexes[0])
assert len(new_genotype_indexes) == 2
filtered_record.FORMAT['GT'] = '/'.join(
[str(x) for x in new_genotype_indexes])
return filtered_record
