def get_read_pairs(self):
data_fns = glob.glob(self.data_dir + "/*.fastq") + glob.glob(self.data_dir + "/*.fq")
fn_pairs = defaultdict(lambda: {1: None, 2: None})
for data_fn in data_fns:
head, tail = os.path.split(data_fn)
root, ext = os.path.splitext(tail)
# Expect root to end in either 1 or 2
prefix, which_member = root[:-1], int(root[-1])
fn_pairs[prefix][which_member] = data_fn
read_pairs_list = []
for prefix in sorted(fn_pairs):
R1_fn = fn_pairs[prefix][1]
R2_fn = fn_pairs[prefix][2]
if R1_fn == None or R2_fn == None:
raise ValueError("unpaired file names in data_dir")
R1_lines = split_file.piece(R1_fn, self.num_pieces, self.which_piece, "fastq")
R2_lines = split_file.piece(R2_fn, self.num_pieces, self.which_piece, "fastq")
read_pairs = fastq.read_pairs(R1_lines, R2_lines, standardize_names=True, ensure_sanger_encoding=True)
read_pairs_list.append(read_pairs)
all_read_pairs = chain.from_iterable(read_pairs_list)
return all_read_pairs
def get_reads(self):
''' A generator over the reads in a piece of each data file.
Can handle a mixture of different fastq encodings across (but not
within) files.
'''
total_reads = 0
for file_name in self.data_fns:
total_reads_from_file = 0
file_piece = split_file.piece(
file_name,
self.num_pieces,
self.which_piece,
'fastq',
)
for read in fastq.reads(file_piece,
standardize_names=True,
ensure_sanger_encoding=True):
yield read
total_reads += 1
total_reads_from_file += 1
if total_reads % 10000 == 0:
logging.info('{0:,} reads processed'.format(total_reads))
head, tail = os.path.split(file_name)
self.summary.append(
('Reads in {0}'.format(tail), total_reads_from_file))
logging.info('{0:,} total reads processed'.format(total_reads))
self.summary.append(('Total reads', total_reads))
def get_sorted_sam_lines(self):
''' Get this piece's set of SAM lines from the merged SAM file, ensuring
that the piece boundary doesn't break up a set of mappings to the
same position.
'''
get_position = annotation.make_convertor(self.MappingAnnotation,
self.PositionAnnotation,
)
sam_lines = split_file.piece(self.merged_file_names['sorted_clean_sam'],
self.num_pieces,
self.which_piece,
'sam',
key=get_position,
)
return sam_lines
def get_reads(self):
""" A generator over the reads in a piece of each data file.
Can handle a mixture of different fastq encodings across (but not
within) files.
"""
total_reads = 0
for file_name in self.data_fns:
total_reads_from_file = 0
file_piece = split_file.piece(file_name, self.num_pieces, self.which_piece, "fastq")
for read in fastq.reads(file_piece, standardize_names=True, ensure_sanger_encoding=True):
yield read
total_reads += 1
total_reads_from_file += 1
if total_reads % 10000 == 0:
logging.info("{0:,} reads processed".format(total_reads))
head, tail = os.path.split(file_name)
self.summary.append(("Reads in {0}".format(tail), total_reads_from_file))
logging.info("{0:,} total reads processed".format(total_reads))
self.summary.append(("Total reads", total_reads))
