def _maybe_add_transcriptome_alignment(sample, out):
transcriptome_bam = dd.get_transcriptome_bam(sample)
if transcriptome_bam and utils.file_exists(transcriptome_bam):
out.append({"path": transcriptome_bam,
"type": "bam",
"ext": "transcriptome"})
return out
def _maybe_add_transcriptome_alignment(sample, out):
transcriptome_bam = dd.get_transcriptome_bam(sample)
if transcriptome_bam and utils.file_exists(transcriptome_bam):
out.append({"path": transcriptome_bam,
"type": "bam",
"ext": "transcriptome"})
return out
def generate_transcript_counts(data):
"""Generate counts per transcript and per exon from an alignment"""
data["count_file"] = featureCounts.count(data)
if dd.get_fusion_mode(data, False) and not dd.get_fusion_caller(data):
oncofuse_file = oncofuse.run(data)
if oncofuse_file:
data = dd.set_oncofuse_file(data, oncofuse_file)
if dd.get_transcriptome_align(data):
# to create a disambiguated transcriptome file realign with bowtie2
if dd.get_disambiguate(data):
logger.info("Aligning to the transcriptome with bowtie2 using the "
"disambiguated reads.")
bam_path = data["work_bam"]
fastq_paths = alignprep._bgzip_from_bam(bam_path, data["dirs"], data, is_retry=False, output_infix='-transcriptome')
if len(fastq_paths) == 2:
file1, file2 = fastq_paths
else:
file1, file2 = fastq_paths[0], None
ref_file = dd.get_ref_file(data)
data = bowtie2.align_transcriptome(file1, file2, ref_file, data)
else:
file1, file2 = dd.get_input_sequence_files(data)
if not dd.get_transcriptome_bam(data):
ref_file = dd.get_ref_file(data)
logger.info("Transcriptome alignment was flagged to run, but the "
"transcriptome BAM file was not found. Aligning to the "
"transcriptome with bowtie2.")
data = bowtie2.align_transcriptome(file1, file2, ref_file, data)
data = spikein.counts_spikein(data)
return [[data]]
def run(data):
"""Quantitaive isoforms expression by eXpress"""
name = dd.get_sample_name(data)
in_bam = dd.get_transcriptome_bam(data)
config = data['config']
if not in_bam:
logger.info("Transcriptome-mapped BAM file not found, skipping eXpress.")
return data
gtf_fasta = gtf.gtf_to_fasta(dd.get_gtf_file(data), dd.get_ref_file(data))
out_dir = os.path.join(dd.get_work_dir(data), "express", name)
out_file = os.path.join(out_dir, name + ".xprs")
express = config_utils.get_program("express", data['config'])
strand = _set_stranded_flag(in_bam, data)
if not file_exists(out_file):
with tx_tmpdir(data) as tmp_dir:
with file_transaction(out_dir) as tx_out_dir:
bam_file = _prepare_bam_file(in_bam, tmp_dir, config)
cmd = ("{express} --no-update-check -o {tx_out_dir} {strand} {gtf_fasta} {bam_file}")
do.run(cmd.format(**locals()), "Run express on %s." % in_bam, {})
shutil.move(os.path.join(out_dir, "results.xprs"), out_file)
eff_count_file = _get_column(out_file, out_file.replace(".xprs", "_eff.counts"), 7)
tpm_file = _get_column(out_file, out_file.replace("xprs", "tpm"), 14)
fpkm_file = _get_column(out_file, out_file.replace("xprs", "fpkm"), 10)
data = dd.set_express_counts(data, eff_count_file)
data = dd.set_express_tpm(data, tpm_file)
data = dd.set_express_fpkm(data, fpkm_file)
return data
def generate_transcript_counts(data):
"""Generate counts per transcript and per exon from an alignment"""
data["count_file"] = featureCounts.count(data)
if dd.get_fusion_mode(data, False):
oncofuse_file = oncofuse.run(data)
if oncofuse_file:
data = dd.set_oncofuse_file(data, oncofuse_file)
if dd.get_transcriptome_align(data) and not dd.get_transcriptome_bam(data):
file1, file2 = None, None
if dd.get_disambiguate(data):
bam_path = data["work_bam"]
fastq_paths = alignprep._bgzip_from_bam(bam_path, data["dirs"], data["config"], is_retry=False, output_infix='-transcriptome')
if len(fastq_paths) == 2:
file1, file2 = fastq_paths
else:
file1, file2 = fastq_paths[0], None
else:
file1, file2 = dd.get_input_sequence_files(data)
ref_file = dd.get_ref_file(data)
logger.info("Transcriptome alignment was flagged to run, but the "
"transcriptome BAM file was not found. Aligning to the "
"transcriptome with bowtie2.")
data = bowtie2.align_transcriptome(file1, file2, ref_file, data)
return [[data]]
def tagcount(data):
bam = dd.get_transcriptome_bam(data)
umi_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(umi_dir, dd.get_sample_name(data))
out_prefix = os.path.join(sample_dir, dd.get_sample_name(data))
out_file = out_prefix + ".mtx"
if file_exists(out_file):
data = dd.set_count_file(data, out_file)
return [[data]]
safe_makedir(sample_dir)
cutoff = dd.get_minimum_barcode_depth(data)
cb_histogram = os.path.join(sample_dir, "cb-histogram.txt")
positional = "--positional" if dd.get_positional_umi(data, False) else ""
if use_installed_transcriptome(data):
gtf_file = dd.get_gtf_file(data)
else:
gtf_file = dd.get_transcriptome_gtf(data, None)
if gtf_file:
gene_map_file = os.path.join(
dd.get_work_dir(data), "annotation",
os.path.basename(os.path.splitext(gtf_file)[0]) + "-tx2gene.tsv")
gene_map_file = gtf.tx2genefile(gtf_file, gene_map_file, tsv=True)
gene_map_flag = " --genemap {0} ".format(gene_map_file)
else:
gene_map_flag = ""
message = "Counting alignments of transcripts in %s." % bam
umis = _umis_cmd(data)
cmd = ("{umis} fasttagcount --cb_cutoff {cutoff} "
"{gene_map_flag} "
"{positional} "
"--cb_histogram {cb_histogram}")
out_files = [out_file, out_file + ".rownames", out_file + ".colnames"]
umi_matrix_file = out_prefix + "-dupes.mtx"
out_files += [
umi_matrix_file, umi_matrix_file + ".rownames",
umi_matrix_file + ".colnames"
]
if has_umi_matrix(data):
umi_matrix_flag = " --umi_matrix {tx_umi_matrix_full} "
else:
umi_matrix_flag = ""
cmd += umi_matrix_flag
cmd += " {bam} {tx_out_file_full}"
with file_transaction(out_files) as tx_out_files:
tx_out_file = tx_out_files[0]
tx_out_file_full = tx_out_file + ".full"
tx_umi_matrix = tx_out_files[3]
tx_umi_matrix_full = tx_out_files[3] + ".full"
do.run(cmd.format(**locals()), message)
cmd = ("{umis} sparse {tx_out_file_full} {tx_out_file}")
message = "Converting %s to sparse format." % tx_out_file_full
do.run(cmd.format(**locals()), message)
if has_umi_matrix(data):
cmd = ("{umis} sparse {tx_umi_matrix_full} {tx_umi_matrix}")
message = "Converting %s to sparse format." % tx_umi_matrix_full
do.run(cmd.format(**locals()), message)
data = dd.set_count_file(data, out_file)
return [[data]]
def run(data):
"""Quantitaive isoforms expression by express"""
name = dd.get_sample_name(data)
in_bam = dd.get_transcriptome_bam(data)
tophat_index = get_in(data, ('genome_resources', 'rnaseq', 'transcriptome_index', 'tophat'))
if not tophat_index:
logger.info("Tophat index not found, skipping running eXpress.")
return None
tophat_fa = tophat_index.replace("ver", "fa")
out_dir = os.path.join(dd.get_work_dir(data), "express", name)
out_file = os.path.join(out_dir, name + ".xprs")
safe_makedir(out_dir)
express = config_utils.get_program("express", data['config'])
if not in_bam:
logger.info("Transcriptome-mapped BAM file not found, skipping eXpress.")
return None
if not file_exists(out_file):
with tx_tmpdir() as tmp_dir:
chdir(tmp_dir)
ref_transcript = _do_fasta(tophat_fa)
cmd = ("{express} {ref_transcript} {in_bam}")
do.run(cmd.format(**locals()), "Run express", {})
shutil.move("results.xprs", out_file)
eff_count_file = _get_column(out_file, out_file.replace(".xprs", "_eff.counts"), 7)
tpm_file = _get_column(out_file, out_file.replace("xprs", "tpm"), 14)
fpkm_file = _get_column(out_file, out_file.replace("xprs","fpkm"), 10)
return (eff_count_file, tpm_file, fpkm_file)
def run(data):
"""Quantitaive isoforms expression by eXpress"""
name = dd.get_sample_name(data)
in_bam = dd.get_transcriptome_bam(data)
if not in_bam:
logger.info(
"Transcriptome-mapped BAM file not found, skipping eXpress.")
return data
gtf_fasta = gtf.gtf_to_fasta(dd.get_gtf_file(data), dd.get_ref_file(data))
out_dir = os.path.join(dd.get_work_dir(data), "express", name)
out_file = os.path.join(out_dir, name + ".xprs")
express = config_utils.get_program("express", data['config'])
strand = _set_stranded_flag(in_bam, data)
if not file_exists(out_file):
with file_transaction(out_dir) as tx_out_dir:
cmd = (
"{express} --no-update-check -o {tx_out_dir} {strand} {gtf_fasta} {in_bam}"
)
do.run(cmd.format(**locals()), "Run express on %s." % in_bam, {})
shutil.move(os.path.join(out_dir, "results.xprs"), out_file)
eff_count_file = _get_column(out_file,
out_file.replace(".xprs", "_eff.counts"), 7)
tpm_file = _get_column(out_file, out_file.replace("xprs", "tpm"), 14)
fpkm_file = _get_column(out_file, out_file.replace("xprs", "fpkm"), 10)
data = dd.set_express_counts(data, eff_count_file)
data = dd.set_express_tpm(data, tpm_file)
data = dd.set_express_fpkm(data, fpkm_file)
return data
def tagcount(data):
bam = dd.get_transcriptome_bam(data)
umi_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(umi_dir, dd.get_sample_name(data))
out_prefix = os.path.join(sample_dir, dd.get_sample_name(data))
out_file = out_prefix + ".mtx"
if file_exists(out_file):
data = dd.set_count_file(data, out_file)
return [[data]]
umis = config_utils.get_program("umis", data, default="umis")
safe_makedir(sample_dir)
cutoff = dd.get_minimum_barcode_depth(data)
cb_histogram = os.path.join(sample_dir, "cb-histogram.txt")
positional = "--positional" if dd.get_positional_umi(data, False) else ""
if use_installed_transcriptome(data):
gtf_file = dd.get_gtf_file(data)
else:
gtf_file = dd.get_transcriptome_gtf(data, None)
if gtf_file:
gene_map_file = os.path.join(dd.get_work_dir(data), "annotation",
os.path.splitext(gtf_file)[0] + "-tx2gene.tsv")
gene_map_file = gtf.tx2genefile(gtf_file, gene_map_file, tsv=True)
gene_map_flag = " --genemap {0} ".format(gene_map_file)
else:
gene_map_flag = ""
message = "Counting alignments of transcripts in %s." % bam
cmd = ("{umis} fasttagcount --cb_cutoff {cutoff} "
"{gene_map_flag} "
"{positional} "
"--cb_histogram {cb_histogram}")
out_files = [out_file, out_file + ".rownames", out_file + ".colnames"]
umi_matrix_file = out_prefix + "-dupes.mtx"
out_files += [umi_matrix_file, umi_matrix_file + ".rownames",
umi_matrix_file + ".colnames"]
if has_umi_matrix(data):
umi_matrix_flag = " --umi_matrix {tx_umi_matrix_full} "
else:
umi_matrix_flag = ""
cmd += umi_matrix_flag
cmd += " {bam} {tx_out_file_full}"
with file_transaction(out_files) as tx_out_files:
tx_out_file = tx_out_files[0]
tx_out_file_full = tx_out_file + ".full"
tx_umi_matrix = tx_out_files[3]
tx_umi_matrix_full = tx_out_files[3] + ".full"
do.run(cmd.format(**locals()), message)
cmd = ("{umis} sparse {tx_out_file_full} {tx_out_file}")
message = "Converting %s to sparse format." % tx_out_file_full
do.run(cmd.format(**locals()), message)
if has_umi_matrix(data):
cmd = ("{umis} sparse {tx_umi_matrix_full} {tx_umi_matrix}")
message = "Converting %s to sparse format." % tx_umi_matrix_full
do.run(cmd.format(**locals()), message)
data = dd.set_count_file(data, out_file)
return [[data]]
def run_salmon_bam(data):
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)
bam_file = dd.get_transcriptome_bam(data)
fasta_file = dd.get_ref_file(data)
out_file = salmon_quant_bam(bam_file, 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_bam(data):
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)
bam_file = dd.get_transcriptome_bam(data)
fasta_file = dd.get_ref_file(data)
out_file = salmon_quant_bam(bam_file, 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_bam(data):
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)
bam_file = dd.get_transcriptome_bam(data)
out_file = salmon_quant_bam(bam_file, salmon_dir, gtf_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))
data = dd.update_summary_qc(data, "salmon", base=dd.get_salmon_fraglen_file(data))
return [[data]]
def run_salmon_bam(data):
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)
bam_file = dd.get_transcriptome_bam(data)
assert file_exists(gtf_file), "%s was not found, exiting." % gtf_file
fasta_file = dd.get_ref_file(data)
assert file_exists(fasta_file), "%s was not found, exiting." % fasta_file
out_file = salmon_quant_bam(bam_file, 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_bam(data):
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)
bam_file = dd.get_transcriptome_bam(data)
assert file_exists(gtf_file), "%s was not found, exiting." % gtf_file
fasta_file = dd.get_ref_file(data)
assert file_exists(fasta_file), "%s was not found, exiting." % fasta_file
out_file = salmon_quant_bam(bam_file, 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 generate_transcript_counts(data):
"""Generate counts per transcript and per exon from an alignment"""
data["count_file"] = featureCounts.count(data)
if dd.get_fusion_mode(data, False):
oncofuse_file = oncofuse.run(data)
if oncofuse_file:
data = dd.set_oncofuse_file(data, oncofuse_file)
# if RSEM set to run, but the aligner didn't create the transcriptome BAM
# file, make one with bwa
if dd.get_rsem(data) and not dd.get_transcriptome_bam(data):
file1, file2 = dd.get_input_sequence_files(data)
ref_file = dd.get_ref_file(data)
logger.info("RSEM was flagged to run, but the transcriptome BAM file "
"was not found. Aligning to the transcriptome with bowtie2.")
data = bowtie2.align_transcriptome(file1, file2, ref_file, data)
return [[data]]
def generate_transcript_counts(data):
"""Generate counts per transcript and per exon from an alignment"""
data["count_file"] = featureCounts.count(data)
if dd.get_fusion_mode(data, False):
oncofuse_file = oncofuse.run(data)
if oncofuse_file:
data = dd.set_oncofuse_file(data, oncofuse_file)
# if RSEM set to run, but the aligner didn't create the transcriptome BAM
# file, make one with bwa
if dd.get_rsem(data) and not dd.get_transcriptome_bam(data):
file1, file2 = dd.get_input_sequence_files(data)
ref_file = dd.get_ref_file(data)
logger.info(
"RSEM was flagged to run, but the transcriptome BAM file "
"was not found. Aligning to the transcriptome with bowtie2.")
data = bowtie2.align_transcriptome(file1, file2, ref_file, data)
return [[data]]
def tagcount(data):
bam = dd.get_transcriptome_bam(data)
umi_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(umi_dir, dd.get_sample_name(data))
out_file = os.path.join(sample_dir, dd.get_sample_name(data) + ".counts")
if file_exists(out_file):
data = dd.set_count_file(data, out_file)
return [[data]]
umis = config_utils.get_program("umis", data, default="umis")
safe_makedir(sample_dir)
cutoff = dd.get_minimum_barcode_depth(data)
cb_histogram = os.path.join(sample_dir, "cb-histogram.txt")
message = "Counting alignments of transcripts in %s." % bam
cmd = ("{umis} tagcount --positional --cb_cutoff {cutoff} --cb_histogram "
"{cb_histogram} {bam} {tx_out_file}")
with file_transaction(out_file) as tx_out_file:
do.run(cmd.format(**locals()), message)
data = dd.set_count_file(data, out_file)
return [[data]]
def tagcount(data):
bam = dd.get_transcriptome_bam(data)
umi_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(umi_dir, dd.get_sample_name(data))
out_file = os.path.join(sample_dir, dd.get_sample_name(data) + ".counts")
if file_exists(out_file):
data = dd.set_count_file(data, out_file)
return [[data]]
umis = config_utils.get_program("umis", data, default="umis")
safe_makedir(sample_dir)
cutoff = dd.get_minimum_barcode_depth(data)
cb_histogram = os.path.join(sample_dir, "cb-histogram.txt")
message = "Counting alignments of transcripts in %s." % bam
cmd = ("{umis} tagcount --positional --cb_cutoff {cutoff} --cb_histogram "
"{cb_histogram} {bam} {tx_out_file}")
with file_transaction(out_file) as tx_out_file:
do.run(cmd.format(**locals()), message)
data = dd.set_count_file(data, out_file)
return [[data]]
def generate_transcript_counts(data):
"""Generate counts per transcript and per exon from an alignment"""
data["count_file"] = featureCounts.count(data)
if dd.get_fusion_mode(data, False):
oncofuse_file = oncofuse.run(data)
if oncofuse_file:
data = dd.set_oncofuse_file(data, oncofuse_file)
# if RSEM set to run, but the aligner didn't create the transcriptome BAM
# file, make one with bwa
if dd.get_disambiguate(data):
logger.info("RSEM is not supported yet for disambiguation protocols. "
"See https://github.com/chapmanb/bcbio-nextgen/issues/859")
return [[data]]
if dd.get_rsem(data) and not dd.get_transcriptome_bam(data):
file1, file2 = dd.get_input_sequence_files(data)
ref_file = dd.get_ref_file(data)
logger.info("RSEM was flagged to run, but the transcriptome BAM file "
"was not found. Aligning to the transcriptome with bowtie2.")
data = bowtie2.align_transcriptome(file1, file2, ref_file, data)
return [[data]]
def tagcount(data):
bam = dd.get_transcriptome_bam(data)
umi_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(umi_dir, dd.get_sample_name(data))
out_file = os.path.join(sample_dir, dd.get_sample_name(data) + ".mtx")
if file_exists(out_file):
data = dd.set_count_file(data, out_file)
return [[data]]
umis = config_utils.get_program("umis", data, default="umis")
safe_makedir(sample_dir)
cutoff = dd.get_minimum_barcode_depth(data)
cb_histogram = os.path.join(sample_dir, "cb-histogram.txt")
positional = "--positional" if dd.get_positional_umi(data, False) else ""
message = "Counting alignments of transcripts in %s." % bam
cmd = ("{umis} tagcount {positional} --cb_cutoff {cutoff} --sparse "
"--cb_histogram {cb_histogram} {bam} {tx_out_file}")
out_files = [out_file, out_file + ".rownames", out_file + ".colnames"]
with file_transaction(out_files) as tx_out_files:
tx_out_file = tx_out_files[0]
do.run(cmd.format(**locals()), message)
data = dd.set_count_file(data, out_file)
return [[data]]
def tagcount(data):
bam = dd.get_transcriptome_bam(data)
umi_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(umi_dir, dd.get_sample_name(data))
out_file = os.path.join(sample_dir, dd.get_sample_name(data) + ".mtx")
if file_exists(out_file):
data = dd.set_count_file(data, out_file)
return [[data]]
umis = config_utils.get_program("umis", data, default="umis")
safe_makedir(sample_dir)
cutoff = dd.get_minimum_barcode_depth(data)
cb_histogram = os.path.join(sample_dir, "cb-histogram.txt")
positional = "--positional" if dd.get_positional_umi(data, False) else ""
message = "Counting alignments of transcripts in %s." % bam
cmd = ("{umis} tagcount {positional} --cb_cutoff {cutoff} --sparse "
"--cb_histogram {cb_histogram} {bam} {tx_out_file}")
out_files = [out_file, out_file + ".rownames", out_file + ".colnames"]
with file_transaction(out_files) as tx_out_files:
tx_out_file = tx_out_files[0]
do.run(cmd.format(**locals()), message)
data = dd.set_count_file(data, out_file)
return [[data]]
def tagcount(data):
bam = dd.get_transcriptome_bam(data)
umi_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(umi_dir, dd.get_sample_name(data))
out_file = os.path.join(sample_dir, dd.get_sample_name(data) + ".mtx")
if file_exists(out_file):
data = dd.set_count_file(data, out_file)
return [[data]]
umis = config_utils.get_program("umis", data, default="umis")
safe_makedir(sample_dir)
cutoff = dd.get_minimum_barcode_depth(data)
cb_histogram = os.path.join(sample_dir, "cb-histogram.txt")
positional = "--positional" if dd.get_positional_umi(data, False) else ""
gtf_file = dd.get_transcriptome_gtf(data, None)
if gtf_file:
gene_map_file = os.path.join(
dd.get_work_dir(data), "annotation",
os.path.splitext(gtf_file)[0] + "-tx2gene.tsv")
gene_map_file = gtf.tx2genefile(gtf_file, gene_map_file, tsv=True)
gene_map_flag = " --genemap {0} ".format(gene_map_file)
else:
gene_map_flag = ""
message = "Counting alignments of transcripts in %s." % bam
cmd = ("{umis} fasttagcount --cb_cutoff {cutoff} "
"{gene_map_flag}"
"--cb_histogram {cb_histogram} {bam} {tx_out_file_full}")
out_files = [out_file, out_file + ".rownames", out_file + ".colnames"]
with file_transaction(out_files) as tx_out_files:
tx_out_file = tx_out_files[0]
tx_out_file_full = tx_out_file + ".full"
do.run(cmd.format(**locals()), message)
cmd = ("{umis} sparse {tx_out_file_full} {tx_out_file}")
message = "Converting %s to sparse format." % tx_out_file_full
do.run(cmd.format(**locals()), message)
data = dd.set_count_file(data, out_file)
return [[data]]
