def __init__(self):
namespace = self._parse_args()
self.input_file_name = namespace.input
self.refdata_file_name = namespace.refdata
self.chunk_id = namespace.chunk
self.mapped_reads_directory = Utilities.ends_with_slash(
os.path.dirname(os.path.abspath(self.input_file_name)))
self._output_directory = Utilities.ends_with_slash("/".join(
os.path.dirname(os.path.abspath(
self.input_file_name)).split("/")[:-1]))
self.logs_directory = "{}Logs/".format(self._output_directory)
self.statistics_directory = "{}Statistics/".format(
self._output_directory)
self._create_dirs()
def prepare_nfasta_for_indexing(input_file: str,
output_dir: str,
preserve_headers: bool = False,
chop: bool = False,
chunk_length: int = int(3.6 * 10**9)):
array = FASTAArray.parse(Utilities.load_string(input_file))
if not preserve_headers:
array._fix_headers()
output_dir = Utilities.ends_with_slash(output_dir)
os.makedirs(output_dir, exist_ok=True)
output_file_mask = (output_dir + Utilities.filename_only(input_file))
annotation_file = "{}_annotation.tsv".format(output_file_mask)
array.dump_annotation(annotation_file)
arrays_dict = {"{}.fasta".format(output_file_mask): array}
if chop and array.get_total_length() >= chunk_length:
print("Too large reference nFASTA file: '{}'. Splitting sequences".
format(input_file))
arrays_dict = array._chop_sequences(chunk_length)
arrays_dict = {
"{a}_{i}.fasta".format(a=output_file_mask, i=i): arrays_dict[i]
for i in arrays_dict
}
refdatas_dict = {}
counter = 0
for chunk_file in arrays_dict:
counter += 1
arrays_dict[chunk_file].dump_fastas(chunk_file)
refdatas_dict["sequence_{}".format(counter)] = {
"reference_nfasta": chunk_file,
"annotation": annotation_file
}
print("FASTA files created: {}".format(counter))
return refdatas_dict
def fill_dict(nfasta_file: str):
mask = Utilities.ends_with_slash(os.path.dirname(os.path.realpath(nfasta_file))) + Utilities.filename_only(nfasta_file)
d = {"ebwt_mask": "{}_colorspace".format(mask),
"bt2_mask": "{}_bowtie2".format(mask),
"fai": "{}_samtools.fai".format(mask),
"genome": "{}_samtools.genome".format(mask),
"annotation": "{}_annotation.tsv".format(mask)}
return d
def __init__(self):
self._namespace = self.parse_args()
self.input_nfasta = self._namespace.input
self.preserve_headers_bool = self._namespace.preserve_headers
self.not_large_index_bool = self._namespace.not_large_index
self.chunk_length = int(self._namespace.size * 10**9)
self.output_dir = Utilities.ends_with_slash(self._namespace.output)
os.makedirs(self.output_dir, exist_ok=True)
def __init__(self):
self._namespace = self._parse_args()
self.sampledata = self._namespace.input
self.target_length = CoveragesVerifier.get_wc_l(self._namespace.genome) + 1
self.prefix = self._namespace.prefix
self.suffix = self._namespace.suffix
self.debugging_bool = self._namespace.debug
self.output = self._namespace.output
if len(self.output) == 0:
self.output = "{}sampledata/{}.sampledata".format(Utilities.ends_with_slash(os.path.dirname(self.prefix)), Utilities.get_time())
def __init__(self, parsed_dictionary: dict):
self._nfasta = parsed_dictionary["reference_nfasta"]
self.db_name = parsed_dictionary.get("alias")
if not self.db_name:
self.db_name = Utilities.filename_only(self._nfasta)
self._reference_mask = Utilities.ends_with_slash(os.path.dirname(os.path.realpath(self._nfasta))) + self.db_name
self.bowtie_index_mask = parsed_dictionary["ebwt_mask"]
self.bowtie2_index_mask = parsed_dictionary["bt2_mask"]
self.samtools_index_file = parsed_dictionary["fai"]
self.bedtools_genome_file = parsed_dictionary["genome"]
self.annotation_file = parsed_dictionary["annotation"]
def compile(input_file: str,
output_dir: str,
preserve_headers: bool = False,
chop: bool = False,
chunk_length: int = int(3.6 * 10**9)):
import json
from modules.FASTAArray import FASTAArray
from modules.RefDataLine import RefDataLine
output_dir = Utilities.ends_with_slash(output_dir)
os.makedirs(output_dir, exist_ok=True)
refdatas_dict = FASTAArray.prepare_nfasta_for_indexing(
input_file=input_file,
output_dir=output_dir,
preserve_headers=preserve_headers,
chop=chop,
chunk_length=chunk_length)
output_dict = {}
for sequence_id in refdatas_dict:
annotation_dict = refdatas_dict[sequence_id]
nfasta_file = annotation_dict.get("reference_nfasta")
if not nfasta_file:
continue
indexing_dict = {"alias": Utilities.filename_only(nfasta_file)}
indexing_dict.update(RefDataLine.fill_dict(nfasta_file))
indexing_dict.update(annotation_dict)
print("Processing nFASTA: '{}'".format(nfasta_file))
refdata = RefDataLine(indexing_dict)
refdata.index()
output_dict[sequence_id] = indexing_dict
output_file = "{a}{b}_refdata.json".format(
a=Utilities.ends_with_slash(output_dir),
b=Utilities.filename_only(input_file))
Utilities.dump_string(
string=json.dumps(output_dict, sort_keys=False, indent=4) + "\n",
file=output_file)
print("Created reference data linker: '{}'".format(output_file))
return output_file
def __init__(self):
namespace = self._parse_args()
self.sampledata_file_name = namespace.input
self.refdata_file_name = namespace.refdata
self.input_mask = namespace.mask
# *_output_mask are attributes of RefDataLine class
self.threads_number = self._parse_threads_number(namespace.threads)
self.no_coverage_bool = namespace.no_coverage
self.output_dir = Utilities.ends_with_slash(namespace.output)
self.logs_directory = "{}Logs/".format(self.output_dir)
[
os.makedirs(i, exist_ok=True)
for i in [self.output_dir, self.logs_directory]
]
def __init__(self, sampledata: SampleDataLine, refdata: RefDataLine,
input_mask: str, output_dir: str):
# Output directories
output_dir = Utilities.ends_with_slash(output_dir)
unmapped_reads_directory = "{}Unmapped_reads/".format(output_dir)
mapped_reads_directory = "{}Mapped_reads/".format(output_dir)
statistics_directory = "{}Statistics/".format(output_dir)
logs_directory = "{}Logs/".format(output_dir)
for path in [
unmapped_reads_directory, mapped_reads_directory,
statistics_directory, logs_directory
]:
os.makedirs(path, exist_ok=True)
# Reference data
self.bowtie_index_mask = refdata.bowtie_index_mask
self.bowtie2_index_mask = refdata.bowtie2_index_mask
self.samtools_index_file = refdata.samtools_index_file
self.bedtools_genome_file = refdata.bedtools_genome_file
self.annotation_file = refdata.annotation_file
# Output masks
mapped_output_mask = "{}_{}".format(input_mask,
refdata.db_name).strip("_")
unmapped_output_mask = "{}_no_{}".format(input_mask,
refdata.db_name).strip("_")
# Sample data
sample_name = sampledata.name
self.raw_reads_files_list = sampledata.raw_reads_files_list
self.raw_reads_file_extension = self.raw_reads_files_list[0].split(
".")[-1]
unmapped_reads_file_mask = "{a}{b}_{c}".format(
a=unmapped_reads_directory, b=sample_name, c=unmapped_output_mask)
self.unmapped_reads_file_name = "{a}.{b}".format(
a=unmapped_reads_file_mask, b=self.raw_reads_file_extension)
self.pairwise_unmapped_reads_files_list = [
"{a}.{i}.{b}".format(a=unmapped_reads_file_mask,
i=i,
b=self.raw_reads_file_extension)
for i in [1, 2]
]
mapped_reads_file_mask = "{a}{b}_{c}".format(a=mapped_reads_directory,
b=sample_name,
c=mapped_output_mask)
self.mapped_reads_file_name = "{}.sam".format(mapped_reads_file_mask)
self.samtools_converted_file_name = "{}.bam".format(
mapped_reads_file_mask)
self.samtools_sorted_file_name = "{}_sorted.bam".format(
mapped_reads_file_mask)
self.samtools_index_file_name = "{}.bai".format(
self.samtools_sorted_file_name)
statistics_file_mask = "{a}{b}_{c}".format(a=statistics_directory,
b=sample_name,
c=mapped_output_mask)
self.samtools_idxstats_file_name = "{}_idxstats.txt".format(
statistics_file_mask)
self.samtools_stats_file_name = "{}_sam_stats.txt".format(
statistics_file_mask)
self.bedtools_histogram_file_name = "{}_genomeCoverageBed.txt".format(
statistics_file_mask)
self.stacked_coverage_file_name = "{}_pos_bp.txt".format(
statistics_file_mask)
self.final_coverage_file_name = "{}_coverage.tsv".format(
statistics_file_mask)
logs_file_mask = "{a}{b}_{c}".format(a=logs_directory,
b=sample_name,
c=mapped_output_mask)
self.aligner_log_file_name = "{}_aligner.log".format(logs_file_mask)
self.samtools_converted_log_file_name = "{}_samtools_sort.log".format(
logs_file_mask)
self.samtools_index_log_file_name = "{}_samtools_index.log".format(
logs_file_mask)
self.samtools_idxstats_log_file_name = "{}_samtools_idxstats.log".format(
logs_file_mask)
self.samtools_stats_log_file_name = "{}_samtools_stats.log".format(
logs_file_mask)
self.genomeCoverageBed_log_file_name = "{}_genomeCoverageBed.log".format(
logs_file_mask)
def __init__(self, refdata: RefDataLine):
# Output directories
output_dir = Utilities.ends_with_slash(
os.path.dirname(os.path.realpath(mainInitializer.input_file_name)))
mapped_reads_directory = "{}Mapped_reads/".format(output_dir)
statistics_directory = "{}Statistics/".format(output_dir)
logs_directory = "{}Logs/".format(output_dir)
for path in [
mapped_reads_directory, statistics_directory, logs_directory
]:
os.makedirs(path, exist_ok=True)
# Reference data
self.samtools_index_file = refdata.samtools_index_file
self.bedtools_genome_file = refdata.bedtools_genome_file
self.annotation_file = refdata.annotation_file
# Output files
if mainInitializer.input_file_name.endswith("_sorted.bam"):
sample_name = re.sub("_sorted.bam$", "",
mainInitializer.input_file_name)
else:
sample_name = ".".join(
mainInitializer.input_file_name.split(".")[:-1])
mapped_reads_file_mask = "{a}{b}".format(a=mapped_reads_directory,
b=sample_name)
self.mapped_reads_file_name = "{}.sam".format(mapped_reads_file_mask)
self.samtools_converted_file_name = "{}.bam".format(
mapped_reads_file_mask)
self.samtools_sorted_file_name = "{}_sorted.bam".format(
mapped_reads_file_mask)
self._mapped_output_mask = refdata.db_name
unmapped_output_mask = "_".join(["no", self._mapped_output_mask])
# Sample data
sample_name = sampledata.name
self.raw_reads_files_list = sampledata.raw_reads_files_list
self.raw_reads_file_extension = self.raw_reads_files_list[0].split(
".")[-1]
unmapped_reads_file_mask = "{a}{b}_{c}".format(
a=unmapped_reads_directory, b=sample_name, c=unmapped_output_mask)
self.unmapped_reads_file_name = "{a}.{b}".format(
a=unmapped_reads_file_mask, b=self.raw_reads_file_extension)
self.pairwise_unmapped_reads_files_list = [
"{a}.{i}.{b}".format(a=unmapped_reads_file_mask,
i=i,
b=self.raw_reads_file_extension)
for i in [1, 2]
]
mapped_reads_file_mask = "{a}{b}_{c}".format(
a=mapped_output_mask, b=sample_name, c=self._mapped_output_mask)
self.mapped_reads_file_name = "{}.sam".format(mapped_reads_file_mask)
self.samtools_converted_file_name = "{}.bam".format(
mapped_reads_file_mask)
self.samtools_sorted_file_name = "{}_sorted.bam".format(
mapped_reads_file_mask)
self.samtools_index_file_name = "{}.bai".format(
self.samtools_sorted_file_name)
statistics_file_mask = "{a}{b}_{c}".format(a=statistics_directory,
b=sample_name,
c=self._mapped_output_mask)
self.samtools_idxstats_file_name = "{}_idxstats.txt".format(
statistics_file_mask)
self.samtools_stats_file_name = "{}_sam_stats.txt".format(
statistics_file_mask)
self.bedtools_histogram_file_name = "{}_genomeCoverageBed.txt".format(
statistics_file_mask)
self.stacked_coverage_file_name = "{}_pos_bp.txt".format(
statistics_file_mask)
self.final_coverage_file_name = "{}_coverage.tsv".format(
statistics_file_mask)
logs_file_mask = "{a}{b}_{c}".format(a=logs_directory,
b=sample_name,
c=self._mapped_output_mask)
self.aligner_log_file_name = "{}_aligner.log".format(logs_file_mask)
self.samtools_converted_log_file_name = "{}_sam2bam.log".format(
logs_file_mask)
self.samtools_index_log_file_name = "{}_index_bam.log".format(
logs_file_mask)
