def test_both_empty(self, empty_feature_list) -> None:
# Test how the function hadles both empty lists
new_feature_list: FeatureList = copy.deepcopy(empty_feature_list)
extant_feature_list: FeatureList = copy.deepcopy(empty_feature_list)
deduplicated_features: FeatureList = dedupl_features(
new_feature_list, extant_feature_list)
assert len(deduplicated_features) == 0
def test_new_empty(self, empty_feature_list,
extant_feature_list_1) -> None:
# Test how the function hadles case when `new_features` is empty
new_feature_list: FeatureList = copy.deepcopy(empty_feature_list)
extant_feature_list: FeatureList = copy.deepcopy(extant_feature_list_1)
deduplicated_features: FeatureList = dedupl_features(
new_feature_list, extant_feature_list)
assert len(deduplicated_features) == 0
def test_both_new_dupl(self, new_feature_list_4,
extant_feature_list_1) -> None:
# Test how the function hadles case when two of `new_features` are duplicated
new_feature_list: FeatureList = copy.deepcopy(new_feature_list_4)
extant_feature_list: FeatureList = copy.deepcopy(extant_feature_list_1)
int_len_new: int = len(new_feature_list)
deduplicated_features: FeatureList = dedupl_features(
new_feature_list, extant_feature_list)
assert len(deduplicated_features) == int_len_new - 2
def test_all_new_unique(self, new_feature_list_1,
extant_feature_list_1) -> None:
# Test how the function hadles case when all `new_features` are unique
new_feature_list: FeatureList = copy.deepcopy(new_feature_list_1)
extant_feature_list: FeatureList = copy.deepcopy(extant_feature_list_1)
int_len_new: int = len(new_feature_list)
deduplicated_features: FeatureList = dedupl_features(
new_feature_list, extant_feature_list)
assert len(deduplicated_features) == int_len_new
def test_one_new_half_unique(self, new_feature_list_2,
extant_feature_list_1) -> None:
# Test how the function hadles case when one of `new_features` has only start
# occuring somewhere in `extant_features`
new_feature_list: FeatureList = copy.deepcopy(new_feature_list_2)
extant_feature_list: FeatureList = copy.deepcopy(extant_feature_list_1)
int_len_new: int = len(new_feature_list)
deduplicated_features: FeatureList = dedupl_features(
new_feature_list, extant_feature_list)
assert len(deduplicated_features) == int_len_new
def main(version: str, last_update_date: str) -> None:
# Parse arguments
params: HighlighterParams = parse_arguments()
# This string will be used for annotation of result GenBank file
base_feature_note: str = f'generated by consensus-highlighter v{version}'
# String for storing info about warnings
with_warnings: str = ''
# Read fasta records from input file
print('Importing fasta from `{}`...'.format(params.target_fasta_fpath),
end=' ')
sys.stdout.flush()
fasta_records: Sequence[SeqRecord] = pfr.parse_fasta_reference(
params.target_fasta_fpath)
print('done')
# Create ouput directory
_create_outdir_from_outfile(params.outfpath)
out.create_or_emply_file(params.outfpath)
# Obtain path to coverage file
coverage_fpath: str = out.conf_path_to_depth_file(params.outfpath)
# Count coverages with samtools depth
print('Silently counting coverages with `samtools depth`...', end=' ')
sys.stdout.flush()
cov_fpath: str = oc.count_cov_for_all_refs(params.target_fasta_fpath,
params.bam_fpath,
coverage_fpath)
print('done\n')
# Proceed with annotation
rec: SeqRecord
for rec in fasta_records:
print(f'Processing sequence `{rec.description}`')
# Obtain coverages for current sequence
cov_array: CoverageArray = oc.get_coverage_for_reference(
rec.id, cov_fpath)
# Check length of the coverage array
if len(cov_array) == 0:
print(
f'! Warning: no coverage information found for sequence `{rec.id}`.'
)
print(
f"""! Please, make sure that field `RNAME` (3-rd column) in your BAM file contains
! id of this sequence specified in fasta header (i.e. `{rec.id}`).""")
print('! Omitting this sequence.')
print('=' * 10)
with_warnings = ' with warnings'
continue
# end if
if len(cov_array) != len(rec.seq):
print(
f"""! Warning: length of sequence `{rec.id}` ({len(rec.seq)} bp)
! is not equal to number of coverage positions ({len(cov_array)}) reported by `samtools depth`
! and stored in coverage file `{cov_fpath}`.""")
print(
'! Re-creating the bam file might be the solution of this issue.'
)
print('! Omitting this sequence.')
print('=' * 10)
with_warnings = ' with warnings'
continue
# end if
mean_coverage = round(sts.mean(cov_array.coverages), 2)
print(f'Average coverage: {mean_coverage}')
cov_threshold: CoverageThreshold
coverage_features: MutableSequence[SeqFeature]
# Detect all necessary coverage features
for cov_threshold in params.coverage_thresholds:
print(
f'Screening the sequence for regions with {cov_threshold.get_label()}...',
end=' ')
sys.stdout.flush()
# Get coverage features
coverage_features = hlft.highlight_coverage_features(
cov_array, cov_threshold, base_feature_note)
coverage_features = ddf.dedupl_features(coverage_features,
rec.features)
# Append features to list
rec.features.extend(coverage_features)
print('done')
# end for
print(f'Writing annotated sequence to `{params.outfpath}`...', end=' ')
sys.stdout.flush()
# Write result GanBank record
out.write_genbank_output(rec, params.topology, params.organism,
params.outfpath)
print('done')
print('=' * 10)
# end for
print(f'Completed{with_warnings}!')