def demultiplex_samples(data):
"""
demultiplex a fastqtransformed FASTQ file into separate sample barcode files
"""
work_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(work_dir, dd.get_sample_name(data))
demulti_dir = os.path.join(sample_dir, "demultiplexed")
files = data["files"]
if len(files) == 2:
logger.error(
"Sample demultiplexing doesn't handle paired-end reads, but "
"we can add it. Open an issue here https://github.com/bcbio/bcbio-nextgen/issues if you need this and we'll add it."
)
sys.exit(1)
else:
fq1 = files[0]
# check if samples need to be demultiplexed
with open_fastq(fq1) as in_handle:
read = next(in_handle)
if "SAMPLE_" not in read:
return [[data]]
bcfile = get_sample_barcodes(dd.get_sample_barcodes(data), sample_dir)
demultiplexed = glob.glob(os.path.join(demulti_dir, "*.fq*"))
if demultiplexed:
return [split_demultiplexed_sampledata(data, demultiplexed)]
umis = config_utils.get_program("umis", data, default="umis")
cmd = ("{umis} demultiplex_samples --nedit 1 --barcodes {bcfile} "
"--out_dir {tx_dir} {fq1}")
msg = "Demultiplexing {fq1}."
with file_transaction(data, demulti_dir) as tx_dir:
do.run(cmd.format(**locals()), msg.format(**locals()))
demultiplexed = glob.glob(os.path.join(demulti_dir, "*.fq*"))
return [split_demultiplexed_sampledata(data, demultiplexed)]
def demultiplex_samples(data):
"""
demultiplex a fastqtransformed FASTQ file into separate sample barcode files
"""
files = data["files"]
if len(files) == 2:
logger.error("Sample demultiplexing doesn't handle paired-end reads, but "
"we can add it. Open an issue here https://github.com/chapmanb/bcbio-nextgen/issues if you need this and we'll add it.")
sys.exit(1)
else:
fq1 = files[0]
# check if samples need to be demultiplexed
with open_fastq(fq1) as in_handle:
read = in_handle.next()
if "SAMPLE_" not in read:
return [[data]]
bcfile = dd.get_sample_barcodes(data)
if not bcfile:
logger.error("Sample demultiplexing needs a list of known indexes provided "
"with via the sample_barcodes option in the algorithm section.")
sys.exit(1)
work_dir = os.path.join(dd.get_work_dir(data), "umis")
sample_dir = os.path.join(work_dir, dd.get_sample_name(data))
demulti_dir = os.path.join(sample_dir, "demultiplexed")
demultiplexed = glob.glob(os.path.join(demulti_dir, "*.fq*"))
if demultiplexed:
return [split_demultiplexed_sampledata(data, demultiplexed)]
umis = config_utils.get_program("umis", data, default="umis")
cmd = ("{umis} demultiplex_samples --nedit 1 --barcodes {bcfile} "
"--out_dir {tx_dir} {fq1}")
msg = "Demultiplexing {fq1}."
with file_transaction(data, demulti_dir) as tx_dir:
do.run(cmd.format(**locals()), msg.format(**locals()))
demultiplexed = glob.glob(os.path.join(demulti_dir, "*.fq*"))
return [split_demultiplexed_sampledata(data, demultiplexed)]
def scrnaseq_concatenate_metadata(samples):
"""
Create file same dimension than mtx.colnames
with metadata and sample name to help in the
creation of the SC object.
"""
barcodes = {}
counts = ""
metadata = {}
for sample in dd.sample_data_iterator(samples):
with open(dd.get_sample_barcodes(sample)) as inh:
for line in inh:
cols = line.strip().split(",")
if len(cols) == 1:
# Assign sample name in case of missing in barcodes
cols.append("NaN")
barcodes[(dd.get_sample_name(sample), cols[0])] = cols[1:]
counts = dd.get_combined_counts(sample)
meta = map(str, list(sample["metadata"].values()))
meta_cols = list(sample["metadata"].keys())
meta = ["NaN" if not v else v for v in meta]
metadata[dd.get_sample_name(sample)] = meta
metadata_fn = counts + ".metadata"
if not file_exists(metadata_fn):
with open(metadata_fn, 'w') as outh:
outh.write(",".join(["sample"] + meta_cols) + '\n')
with open(counts + ".colnames") as inh:
for line in inh:
sample = line.split(":")[0]
barcode = sample.split("-")[1]
outh.write(",".join(barcodes[(sample, barcode)] + metadata[sample]) + '\n')
return samples
def scrnaseq_concatenate_metadata(samples):
"""
Create file same dimension than mtx.colnames
with metadata and sample name to help in the
creation of the SC object.
"""
barcodes = {}
counts = ""
metadata = {}
for sample in dd.sample_data_iterator(samples):
with open(dd.get_sample_barcodes(sample)) as inh:
for line in inh:
cols = line.strip().split(",")
if len(cols) == 1:
# Assign sample name in case of missing in barcodes
cols.append("NaN")
barcodes[cols[0]] = cols[1:]
counts = dd.get_combined_counts(sample)
meta = map(str, list(sample["metadata"].values()))
meta_cols = list(sample["metadata"].keys())
meta = ["NaN" if not v else v for v in meta]
metadata[dd.get_sample_name(sample)] = meta
metadata_fn = counts + ".metadata"
if not file_exists(metadata_fn):
with open(metadata_fn, 'w') as outh:
outh.write(",".join(["sample"] + meta_cols) + '\n')
with open(counts + ".colnames") as inh:
for line in inh:
sample = line.split(":")[0]
barcode = sample.split("-")[1]
outh.write(",".join(barcodes[barcode] + metadata[sample]) + '\n')
return samples
