def main(
fastq_dirs: Iterable[Path],
output_dir: Path = Path(),
barcode_filename: Path = BARCODE_ALLOWLIST_FILE,
n6_dt_mapping_file: Path = N6_DT_MAPPING_FILE,
):
barcode_allowlist = read_barcode_allowlist(barcode_filename)
correcter = bu.BarcodeCorrecter(barcode_allowlist, edit_distance=1)
n6_dt_mapping = read_n6_dt_mapping(n6_dt_mapping_file)
buf = output_dir / BARCODE_UMI_FASTQ_PATH
trf = output_dir / TRANSCRIPT_FASTQ_PATH
all_fastqs = chain.from_iterable(
find_grouped_fastq_files(fastq_dir, 2) for fastq_dir in fastq_dirs)
with open(buf, "w") as cbo, open(trf, "w") as tro:
for transcript_fastq, barcode_umi_fastq in all_fastqs:
usable_count = 0
i = 0
print("Correcting barcodes in", transcript_fastq, "and",
barcode_umi_fastq)
transcript_reader = fastq_reader(transcript_fastq)
barcode_umi_reader = fastq_reader(barcode_umi_fastq)
for i, (tr, br) in enumerate(
zip(transcript_reader, barcode_umi_reader), 1):
barcode_pieces = [revcomp(br.seq[s]) for s in BARCODE_SEGMENTS]
rc_corrected = [
correcter.correct(barcode) for barcode in barcode_pieces
]
if all(rc_corrected):
rc_corrected[2] = n6_dt_mapping[rc_corrected[2]]
corrected = [revcomp(rc_bc) for rc_bc in rc_corrected]
usable_count += 1
umi_seq = br.seq[UMI_SEGMENT]
umi_qual = br.qual[UMI_SEGMENT]
new_seq = "".join(corrected + [umi_seq])
new_qual = BARCODE_QUAL_DUMMY + umi_qual
new_br = Read(
read_id=br.read_id,
seq=new_seq,
unused=br.unused,
qual=new_qual,
)
print(tr.serialize(), file=tro)
print(new_br.serialize(), file=cbo)
print("Total count:", i)
print("Usable count:", usable_count)
print("Proportion:", usable_count / i)
def convert(mapper: BarcodeMapper, input_fastq: Path, output_dir: Path,
basename: str):
output_dir.mkdir(exist_ok=True, parents=True)
print("Converting", input_fastq)
barcode_umi_path = output_dir / f"{basename}_R1.fastq"
transcript_path = output_dir / f"{basename}_R2.fastq"
decompress_fastq(input_fastq, transcript_path)
with smart_open(barcode_umi_path, "wt") as f:
for transcript_read in fastq_reader(input_fastq):
id_pieces = transcript_read.read_id.lstrip("@").split("|")
p7 = mapper.p7_mapping[id_pieces[2]]
p5 = mapper.p5_mapping[id_pieces[3]]
rt2_id, lig_id = id_pieces[4].split("_")
rt2 = mapper.rt2_mapping[rt2_id]
lig = mapper.ligation_mapping[lig_id]
umi = id_pieces[5]
barcode_umi = umi + p7 + p5 + rt2 + lig
barcode_umi_read = Read(
read_id=transcript_read.read_id,
seq=barcode_umi,
unused=transcript_read.unused,
qual=get_base_qual_str(len(barcode_umi)),
)
print(barcode_umi_read.serialize(), file=f)
def main(assay: Assay, fastq_dirs: Iterable[Path], output_filename_prefix,
output_dir: Path):
baraddedf1 = output_dir / f"{output_filename_prefix}_R1.fastq"
baraddedf2 = output_dir / f"{output_filename_prefix}_R2.fastq"
all_fastqs = chain.from_iterable(
find_grouped_fastq_files(fastq_dir, assay.fastq_count)
for fastq_dir in fastq_dirs)
with open(baraddedf1, "w") as barf1addedout, open(baraddedf2,
"w") as barf2addedout:
for fastq1_file, fastq2_file, barcode_file in all_fastqs:
i = 0
print("Adding barcodes to", fastq1_file, "and", fastq2_file,
"using", barcode_file)
fastq1_reader = fastq_reader(fastq1_file)
fastq2_reader = fastq_reader(fastq2_file)
barcode_reader = fastq_reader(barcode_file)
for i, (f1r, f2r, bar) in enumerate(
zip(fastq1_reader, fastq2_reader, barcode_reader), 1):
if assay == Assay.SNARESEQ:
# This code assumes the barcode fastq is the third fastq; e.g. '...R3...'
barcode_pieces = [
revcomp(bar.seq[s]) for s in SNARESEQ_BARCODE_SEGMENTS
]
# For some reason the barcode pieces are reversed in the list
# so get them back in the right order
barcode_pieces.reverse()
umi_seq = bar.seq[UMI_SEGMENT]
elif assay == Assay.SNSEQ:
barcode_pieces = [f2r.seq[SNSEQ_BARCODE_SEGMENT]]
# print("barcode pieces={}".format(barcode_pieces))
umi_seq = ""
else:
print(
"Could not adjust barcodes for assay {}".format(assay))
create_and_output_barcode_adjusted_reads(
f1r, f2r, umi_seq, barcode_pieces, barf1addedout,
barf2addedout)
def convert_fastq(input_path: Path, output_path: Union[str, Path]):
print("Converting", input_path, "to", output_path)
with open(output_path, "wt") as f:
for read in fastq_reader(input_path):
# We know the read ID format of this single data set, but
# be lenient in what we accept and how we parse this
barcode, *rest = read.read_id.lstrip("@").split(":")
new_read_id = READ_ID_FORMAT.format(
barcode=barcode,
umi="",
previous_read_id="".join(rest),
)
new_read = Read(
read_id=new_read_id,
seq=read.seq,
unused=read.unused,
qual=read.qual,
)
print(new_read.serialize(), file=f)
def convert(mapper: BarcodeMapper, input_fastq: Path, output_dir: Path,
basename: str):
output_dir.mkdir(exist_ok=True, parents=True)
print('Converting', input_fastq)
barcode_umi_path = output_dir / f'{basename}_R1.fastq'
transcript_path = output_dir / f'{basename}_R2.fastq'
decompress_fastq(input_fastq, transcript_path)
with smart_open(barcode_umi_path, 'wt') as f:
for transcript_read in fastq_reader(input_fastq):
id_pieces = transcript_read.read_id.lstrip('@').split('|')
p7 = mapper.p7_mapping[id_pieces[2]]
p5 = mapper.p5_mapping[id_pieces[3]]
rt2 = mapper.rt2_mapping[id_pieces[4]]
umi = id_pieces[5]
barcode_umi = p7 + p5 + rt2 + umi
barcode_umi_read = Read(
read_id=transcript_read.read_id,
seq=barcode_umi,
unused=transcript_read.unused,
qual=get_base_qual_str(len(barcode_umi)),
)
print(barcode_umi_read.serialize(), file=f)