def prepare_input_data(config):
""" In case of disambiguation, we want to run fusion calling on
the disambiguated reads, which are in the work_bam file.
As EricScript accepts 2 fastq files as input, we need to convert
the .bam to 2 .fq files.
"""
if not dd.get_disambiguate(config):
return dd.get_input_sequence_files(config)
work_bam = dd.get_work_bam(config)
logger.info("Converting disambiguated reads to fastq...")
fq_files = convert_bam_to_fastq(work_bam, dd.get_work_dir(config), None,
None, config)
return fq_files
def prepare_input_data(config):
""" In case of disambiguation, we want to run fusion calling on
the disambiguated reads, which are in the work_bam file.
As EricScript accepts 2 fastq files as input, we need to convert
the .bam to 2 .fq files.
"""
if not dd.get_disambiguate(config):
return dd.get_input_sequence_files(config)
work_bam = dd.get_work_bam(config)
logger.info("Converting disambiguated reads to fastq...")
fq_files = convert_bam_to_fastq(
work_bam, dd.get_work_dir(config), None, None, config
)
return fq_files
def run_salmon_reads(data):
data = utils.to_single_data(data)
files = dd.get_input_sequence_files(data)
if bam.is_bam(files[0]):
files = fastq.convert_bam_to_fastq(files[0], data["dirs"]["work"],
data, data["dirs"], data["config"])
samplename = dd.get_sample_name(data)
work_dir = dd.get_work_dir(data)
salmon_dir = os.path.join(work_dir, "salmon", samplename)
gtf_file = dd.get_gtf_file(data)
if len(files) == 2:
fq1, fq2 = files
else:
fq1, fq2 = files[0], None
fasta_file = dd.get_ref_file(data)
out_file = salmon_quant_reads(fq1, fq2, salmon_dir, gtf_file, fasta_file,
data)
data = dd.set_salmon(data, out_file)
data = dd.set_salmon_dir(data, salmon_dir)
return [[data]]
def run_salmon_reads(data):
data = utils.to_single_data(data)
files = dd.get_input_sequence_files(data)
if bam.is_bam(files[0]):
files = fastq.convert_bam_to_fastq(files[0], data["dirs"]["work"],
data, data["dirs"], data["config"])
samplename = dd.get_sample_name(data)
work_dir = dd.get_work_dir(data)
salmon_dir = os.path.join(work_dir, "salmon", samplename)
gtf_file = dd.get_gtf_file(data)
if len(files) == 2:
fq1, fq2 = files
else:
fq1, fq2 = files[0], None
fasta_file = dd.get_ref_file(data)
out_file = salmon_quant_reads(fq1, fq2, salmon_dir, gtf_file, fasta_file, data)
data = dd.set_salmon(data, out_file)
data = dd.set_salmon_dir(data, salmon_dir)
data = dd.set_salmon_fraglen_file(data, _get_fraglen_file(salmon_dir))
return [[data]]
def run_salmon_decoy(data):
data = utils.to_single_data(data)
files = dd.get_input_sequence_files(data)
if bam.is_bam(files[0]):
files = fastq.convert_bam_to_fastq(files[0], data["dirs"]["work"],
data, data["dirs"], data["config"])
samplename = dd.get_sample_name(data)
work_dir = dd.get_work_dir(data)
salmon_dir = os.path.join(work_dir, "salmon", samplename)
gtf_file = dd.get_gtf_file(data)
if len(files) == 2:
fq1, fq2 = files
else:
fq1, fq2 = files[0], None
index = salmon_decoy_index(gtf_file, data, os.path.dirname(salmon_dir))
out_file = salmon_quant_reads(fq1, fq2, salmon_dir, gtf_file, data, index)
data = dd.set_salmon(data, out_file)
data = dd.set_salmon_dir(data, salmon_dir)
data = dd.set_salmon_fraglen_file(data, _get_fraglen_file(salmon_dir))
data = dd.update_summary_qc(data, "salmon", base=dd.get_salmon_fraglen_file(data))
return [[data]]
