def __init__(self, fna_file, contamination_report):
self.sequence_file = fna_file
self.contamination_file = contamination_report
self.contamination_lines = Utilities.load_2d_array(
self.contamination_file)
exclude_index = self.find_index(self.contamination_lines, ["Exclude:"])
trim_index = self.find_index(self.contamination_lines, ["Trim:"])
duplicated_index = self.find_index(self.contamination_lines,
["Duplicated:"])
# Issue lines order: exclude, trim, duplicated
headers_to_remove = []
if exclude_index:
exclude_lines = []
if trim_index:
exclude_lines = self.contamination_lines[exclude_index +
2:trim_index]
elif duplicated_index:
exclude_lines = self.contamination_lines[exclude_index +
2:duplicated_index]
else:
exclude_lines = self.contamination_lines[exclude_index + 2:]
exclude_lines = Utilities.remove_empty_values(
[i[0] for i in exclude_lines])
headers_to_remove.extend(exclude_lines)
if trim_index:
trim_lines_processed = dict()
if duplicated_index:
trim_lines_raw = self.contamination_lines[trim_index +
2:duplicated_index]
else:
trim_lines_raw = self.contamination_lines[trim_index + 2:]
for trim_line_raw in Utilities.remove_empty_values(trim_lines_raw):
for trim_span in Utilities.remove_empty_values(
trim_line_raw[2].split(",")):
trim_indices = [
int(i.strip()) for i in trim_span.split("..")
]
# It seems that reported sequence positions are not zero-based
trim_indices[0] -= 1
trim_lines_processed[trim_line_raw[0]] = trim_indices
headers_to_remove.extend(list(trim_lines_processed.keys()))
if duplicated_index:
processed_duplicated_lines = list()
duplicated_lines = [
i for i in self.contamination_lines[duplicated_index + 2:]
]
# Removing only the first occurrence in Duplicates
for duplicated_line in duplicated_lines:
duplicated_str = duplicated_line[0]
if duplicated_str.startswith("# "):
continue
processed_duplicated_lines.append(
duplicated_str.strip().split(" ")[0])
headers_to_remove.extend(processed_duplicated_lines)
self.seq_records = list(SeqIO.parse(self.sequence_file, "fasta"))
print(
f"Imported {len(self.seq_records)} raw records from '{self.sequence_file}'"
)
headers_to_remove = sorted(
set(Utilities.remove_empty_values(headers_to_remove)))
print("{} headers were marked to remove: '{}'".format(
len(headers_to_remove), "', '".join(headers_to_remove)))
out_records = []
for record_raw in Utilities.remove_duplicate_sequences(
self.seq_records):
record_id = record_raw.id.split(" ")[0].strip()
if record_id not in headers_to_remove:
out_records.append(record_raw)
# Some positions from the "Trim" entry after NCBI processing were moved into the "Exclude" entry
# The point is removing them instead of trimming
self.valid_records = [
i for i in out_records if len(i) >= self._NCBI_MIN_SEQ_LENGTH
]
"{}_assembly_contigs_number_valid".format(
assembly_type)] = len(seq_records_valid)
assemblies_annotation["{}_assembly_bp_valid".format(
assembly_type)] = sum([len(i) for i in seq_records_valid])
for seq_record_raw in seq_records_valid:
# Example `contigs.fasta` header:
# '>NODE_1_length_42950_cov_12.6852_component_0'
# contig_number = int(Utilities.safe_findall("^NODE_([0-9]+)", seq_record_raw.id))
# Processed FASTA header example:
# >contig02 [organism=Clostridium difficile] [strain=ABDC] [plasmid-name=pABDC1] [topology=circular] [completeness=complete]
seq_record_processed = deepcopy(seq_record_raw)
if assembly_type == "plasmid":
plasmid_counter += 1
seq_record_processed.description += " PLASMID"
seq_records_processed.append(seq_record_processed)
seq_records_processed = Utilities.remove_duplicate_sequences(
seq_records_processed)
for idx, seq_record_processed in enumerate(seq_records_processed):
seq_record_processed.id = "contig{a:03d} [organism={b}] [strain={c}_{d}]".format(
a=idx + 1, b=ORGANISM, c=ISOLATE_PREFIX, d=sample_number)
if seq_record_processed.description.endswith(" PLASMID"):
plasmid_counter += 1
seq_record_processed.description = "[plasmid-name=unnamed{0:02d}]".format(
plasmid_counter)
else:
seq_record_processed.description = ""
assemblies_annotations.append(assemblies_annotation)
#
SeqIO.write(seq_records_processed, assembly_target_file, "fasta")
INDEX_COL_NAME = "sample_name"
assemblies_statistics_df = pd.DataFrame(assemblies_annotations).set_index(
