def get_bases_mask(run_info_xml, sample_sheet_file=None):
"""
Get bases mask string
Generates initial bases mask based on data in RunInfo.xml (which
says how many reads there are, how many cycles in each read, and
which are index reads), and optionally updates this using the
barcode information in the sample sheet file.
Arguments:
run_info_xml: name and path of RunInfo.xml file from the
sequencing run
sample_sheet_file: (optional) path to sample sheet file
Returns:
Bases mask string e.g. 'y101,I6'.
"""
# Get initial bases mask
bases_mask = IlluminaData.IlluminaRunInfo(run_info_xml).bases_mask
print "Bases mask: %s (from RunInfo.xml)" % bases_mask
if sample_sheet_file is not None:
# Update bases mask from sample sheet
example_barcode = IlluminaData.samplesheet_index_sequence(
IlluminaData.SampleSheet(sample_sheet_file).data[0])
if example_barcode is None:
example_barcode = ""
if barcode_is_10xgenomics(example_barcode):
print "Bases mask: barcode is 10xGenomics sample set ID"
else:
bases_mask = IlluminaData.fix_bases_mask(bases_mask,
example_barcode)
print "Bases mask: %s (updated for barcode sequence '%s')" % \
(bases_mask,example_barcode)
return bases_mask
def setup(self):
# Make output filenames
report_file = os.path.join(self.args.barcode_analysis_dir,
'barcodes.report')
xls_file = os.path.join(self.args.barcode_analysis_dir, 'barcodes.xls')
html_file = os.path.join(self.args.barcode_analysis_dir,
'barcodes.html')
# Remove existing copies, if found
for filen in (report_file, xls_file, html_file):
if os.path.exists(filen):
os.remove(filen)
# Build command to run the barcode analysis
cmd = PipelineCommandWrapper(
"Run analyse_barcodes.py to report barcodes",
'analyse_barcodes.py', '--report', report_file, '--xls', xls_file,
'--html', html_file)
if self.args.sample_sheet:
cmd.add_args('--sample-sheet', self.args.sample_sheet)
if self.args.lanes:
lanes = self.args.lanes
elif self.args.sample_sheet:
# Implicitly get lanes from sample sheet
try:
lanes = sorted(
set([
line['Lane'] for line in IlluminaData.SampleSheet(
self.args.sample_sheet).data
]))
except KeyError:
# No lanes
lanes = None
else:
lanes = None
if lanes:
cmd.add_args('--lanes', ','.join([str(l) for l in lanes]))
if self.args.cutoff:
cmd.add_args('--cutoff', self.args.cutoff)
if self.args.mismatches:
cmd.add_args('--mismatches', self.args.mismatches)
if self.args.title:
cmd.add_args('--title', self.args.title)
cmd.add_args('-c')
cmd.add_args(*self.args.counts_files)
self.add_cmd(cmd)
# Update the output parameters
self.output.report_file.set(report_file)
self.output.xls_file.set(xls_file)
self.output.html_file.set(html_file)
def check_barcode_collisions(sample_sheet_file, nmismatches):
"""
Check sample sheet for barcode collisions
Check barcode index sequences within each lane (or across
all samples, if no lane information is present) and find
any which differ in fewer bases than a threshold number
which is calculated as:
less than 2 times the number of mismatches plus 1
(as is stated in the output from bcl2fastq v2.)
Pairs of barcodes which are too similar (i.e. which collide)
are reported as a list of tuples, e.g.
[('ATTCCT','ATTCCG'),...]
Arguments:
sample_sheet_file (str): path to a SampleSheet.csv file
to analyse for barcode collisions
nmismatches (int): maximum number of mismatches to allow
Returns:
List: list of pairs of colliding barcodes (with each pair
wrapped in a tuple), or an empty list if no collisions
were detected.
"""
# Load the sample sheet data
sample_sheet = IlluminaData.SampleSheet(sample_sheet_file)
# List of index sequences (barcodes)
barcodes = {}
has_lanes = sample_sheet.has_lanes
for line in sample_sheet:
# Lane
if has_lanes:
lane = line['Lane']
else:
lane = 1
# Index sequence
try:
# Try dual-indexed IEM4 format
indx = "%s%s" % (line['index'].strip(), line['index2'].strip())
except KeyError:
# Try single indexed IEM4 (no index2)
try:
indx = line['index'].strip()
except KeyError:
# Try CASAVA format
try:
indx = line['Index'].strip()
except KeyError:
# No index columns
indx = ""
# Explicitly set empty index to None
if not indx:
indx = None
try:
barcodes[lane].append(indx)
except KeyError:
barcodes[lane] = [
indx,
]
# Mismatch threshold
mismatch_threshold = 2 * nmismatches + 1
# Check for collisions
collisions = []
for lane in barcodes:
for i, seq1 in enumerate(barcodes[lane][:-1]):
for seq2 in barcodes[lane][i + 1:]:
ndiff = 0
for c1, c2 in zip(seq1, seq2):
if c1 != c2:
ndiff += 1
if ndiff < mismatch_threshold:
collisions.append((seq1, seq2))
return collisions
def make_custom_sample_sheet(input_sample_sheet,
output_sample_sheet=None,
lanes=None,
fmt=None):
"""
Creates a corrected copy of a sample sheet file
Creates and returns a SampleSheet object with a copy of the
input sample sheet, with any illegal or duplicated names fixed.
Optionally it can also: write the updated sample sheet data to a
new file, switch the format, and include only a subset of lanes
from the original file
Arguments:
input_sample_sheet (str): name and path of the original sample
sheet file
output_sample_sheet (str): (optional) name and path to write
updated sample sheet to, or `None`
lanes (list): (optional) list of lane numbers to keep in the
output sample sheet; if `None` then all lanes will be kept
(the default), otherwise lanes will be dropped if they don't
appear in the supplied list
fmt (str): (optional) format for the output sample sheet,
either 'CASAVA' or 'IEM'; if this is `None` then the format
of the original file will be used
Returns:
SampleSheet object with the data for the corrected sample
sheet.
"""
# Load the sample sheet data
sample_sheet = IlluminaData.SampleSheet(input_sample_sheet)
# Determine the column names for this format
if sample_sheet.format == 'CASAVA':
sample_col = 'SampleID'
project_col = 'SampleProject'
elif sample_sheet.format == 'IEM':
sample_col = 'Sample_ID'
project_col = 'Sample_Project'
else:
raise Exception("Unknown sample sheet format: %s" %
sample_sheet.format)
# Add project names if not supplied
for line in sample_sheet:
if not line[project_col]:
line[project_col] = line[sample_col]
# Fix other problems
sample_sheet.fix_illegal_names()
sample_sheet.fix_duplicated_names()
# Select subset of lanes if requested
if lanes is not None:
logging.debug("Updating to include only specified lanes: %s" %
','.join([str(l) for l in lanes]))
i = 0
while i < len(sample_sheet):
line = sample_sheet[i]
if line['Lane'] in lanes:
logging.debug("Keeping %s" % line)
i += 1
else:
del (sample_sheet[i])
# Write out new sample sheet
if output_sample_sheet is not None:
sample_sheet.write(output_sample_sheet, fmt=fmt)
return sample_sheet
"IEM sample sheet to older format)")
p.add_argument('sample_sheet',metavar="SAMPLE_SHEET",
help="input sample sheet file")
# Process command line
args = p.parse_args()
if args.miseq:
logging.warning("--miseq option no longer necessary; "
"MiSEQ-style sample sheets are now converted "
"automatically")
# Get input sample sheet file
samplesheet = args.sample_sheet
if not os.path.isfile(samplesheet):
logging.error("sample sheet '%s': not found" % samplesheet)
sys.exit(1)
# Read in the sample sheet
data = IlluminaData.SampleSheet(samplesheet)
if data.format is None:
logging.error("Unable to determine samplesheet format")
sys.exit(1)
print "Sample sheet format: %s" % data.format
# Remove lanes
if args.lanes is not None:
if not data.has_lanes:
logging.error("sample sheet doesn't define any lanes")
sys.exit(1)
lanes = parse_lanes(args.lanes)
print "Keeping lanes %s, removing the rest" % \
','.join([str(x) for x in lanes])
i = 0
while i < len(data):
line = data[i]
def check_barcode_collisions(sample_sheet_file, nmismatches, use_index='all'):
"""
Check sample sheet for barcode collisions
Check barcode index sequences within each lane (or across
all samples, if no lane information is present) and find
any which differ in fewer bases than a threshold number
which is calculated as:
less than 2 times the number of mismatches plus 1
(as is stated in the output from bcl2fastq v2.)
Pairs of barcodes which are too similar (i.e. which collide)
are reported as a list of tuples, e.g.
[('ATTCCT','ATTCCG'),...]
Arguments:
sample_sheet_file (str): path to a SampleSheet.csv file
to analyse for barcode collisions
nmismatches (int): maximum number of mismatches to allow
use_index (str): flag indicating how to treat index
sequences: 'all' (the default) combines indexes into a
single sequence before checking for collisions, '1' only
checks index 1 (i7), and '2' only checks index 2 (i5)
Returns:
List: list of pairs of colliding barcodes (with each pair
wrapped in a tuple), or an empty list if no collisions
were detected.
"""
# Load the sample sheet data
sample_sheet = IlluminaData.SampleSheet(sample_sheet_file)
# Convert index flag to string
use_index = str(use_index)
# List of index sequences (barcodes)
barcodes = {}
has_lanes = sample_sheet.has_lanes
for line in sample_sheet:
# Lane
if has_lanes:
lane = line['Lane']
else:
lane = 1
# Extract i7 index sequence
indx_i7 = None
try:
# IEM4 format
indx_i7 = line['index'].strip()
except KeyError:
# CASAVA format
try:
indx_i7 = line['Index'].strip()
except KeyError:
pass
# Extract i5 index sequence
indx_i5 = None
try:
# IEM4 format
indx_i5 = line['index2'].strip()
except KeyError:
# No i5 for CASAVA
pass
# Assemble index sequence to check for mismatches
if use_index == "all":
# Combine i5 and i7 into a single sequence
indx = "%s%s" % (indx_i7 if indx_i7 else '',
indx_i5 if indx_i5 else '')
elif use_index == "1":
# Only use i7
indx = indx_i7
elif use_index == "2":
# Only use i5
indx = indx_i5
else:
# Undefined index type
raise Exception("Unrecognised index: '%s'" % use_index)
# Explicitly set empty index to None
if not indx:
indx = None
try:
barcodes[lane].append(indx)
except KeyError:
barcodes[lane] = [
indx,
]
# Mismatch threshold
mismatch_threshold = 2 * nmismatches + 1
# Check for collisions
collisions = []
for lane in barcodes:
for i, seq1 in enumerate(barcodes[lane][:-1]):
for seq2 in barcodes[lane][i + 1:]:
ndiff = 0
for c1, c2 in zip(seq1, seq2):
if c1 != c2:
ndiff += 1
if ndiff < mismatch_threshold:
collisions.append((seq1, seq2))
return collisions
def make_fastqs(ap,
protocol='standard',
platform=None,
unaligned_dir=None,
sample_sheet=None,
lanes=None,
ignore_missing_bcl=False,
ignore_missing_stats=False,
skip_rsync=False,
remove_primary_data=False,
nprocessors=None,
require_bcl2fastq_version=None,
bases_mask=None,
no_lane_splitting=None,
minimum_trimmed_read_length=None,
mask_short_adapter_reads=None,
generate_stats=True,
stats_file=None,
per_lane_stats_file=None,
analyse_barcodes=True,
barcode_analysis_dir=None,
skip_fastq_generation=False,
only_fetch_primary_data=False,
create_empty_fastqs=None,
runner=None,
cellranger_jobmode=None,
cellranger_mempercore=None,
cellranger_maxjobs=None,
cellranger_jobinterval=None,
cellranger_localcores=None,
cellranger_localmem=None,
cellranger_ignore_dual_index=False):
"""Create and summarise FASTQ files
Wrapper for operations related to FASTQ file generation and analysis.
The operations are typically:
- get primary data (BCL files)
- run bcl-to-fastq conversion
- generate statistics
If the number of processors and the job runner are not explicitly
specified then these are taken from the settings for the bcl2fastq
and the statistics generation steps, which may differ from each other.
However if either of these values are set explicitly then the same
values will be used for both steps.
Arguments:
ap (AutoProcessor): autoprocessor pointing to the analysis
directory to create Fastqs for
protocol (str): if set then specifies the protocol to use
for fastq generation, otherwise use the 'standard' bcl2fastq
protocol
platform (str): if set then specifies the sequencing platform
(otherwise platform will be determined from the primary data)
unaligned_dir (str): if set then use this as the output directory
for bcl-to-fastq conversion. Default is 'bcl2fastq' (unless
an alternative is already specified in the config file)
sample_sheet (str): if set then use this as the input samplesheet
lanes (list): (optional) specify a list of lane numbers to
use in the processing; lanes not in the list will be excluded
(default is to include all lanes)
nprocessors (int) : number of processors to run bclToFastq.py with
ignore_missing_bcl (bool): if True then run bcl2fastq with
--ignore-missing-bcl
ignore_missing_stats (bool): if True then run bcl2fastq with
--ignore-missing-stats
skip_rsync (bool): if True then don't rsync primary data at the
start of bcl2fastq conversion
remove_primary_data (bool): if True then remove primary data at
the end of bcl2fastq conversion (default is to keep it)
generate_stats (bool): if True then (re)generate statistics file
for fastqs
analyse_barcodes (bool): if True then (re)analyse barcodes for
fastqs
require_bcl2fastq_version (str): (optional) specify bcl2fastq
version to use. Should be a string of the form '1.8.4' or
'>2.0'. Set to None to automatically determine required
bcl2fastq version.
bases_mask (str): if set then use this as an alternative bases
mask setting
no_lane_splitting (bool): if True then run bcl2fastq with
--no-lane-splitting
minimum_trimmed_read_length (int): if set then specify minimum
length for reads after adapter trimming (shorter reads will
be padded with Ns to make them long enough)
mask_short_adapter_reads (int): if set then specify the minimum
length of ACGT bases that must be present in a read after
adapter trimming for it not to be masked completely
with Ns.
stats_file (str): if set then use this as the name of the output
per-fastq stats file.
per_lane_stats_file (str): if set then use this as the name of
the output per-lane stats file.
barcode_analysis_dir (str): if set then specifies path to the
output directory for barcode analysis
skip_fastq_generation (bool): if True then don't perform fastq
generation
only_fetch_primary_data (bool): if True then fetch primary data,
don't do anything else
create_empty_fastqs (bool): if True then create empty 'placeholder'
fastq files for any missing fastqs after bcl2fastq
(must have completed with zero exit status)
runner (JobRunner): (optional) specify a non-default job runner
to use for fastq generation
cellranger_jobmode (str): (optional) job mode to run cellranger in
(10xGenomics Chromium SC data only)
cellranger_mempercore (int): (optional) memory assumed per core
(in Gbs) (10xGenomics Chromium SC data only)
cellranger_maxjobs (int): (optional) maxiumum number of concurrent
jobs to run (10xGenomics Chromium SC data only)
cellranger_jobinterval (int): (optional) how often jobs are
submitted (in ms) (10xGenomics Chromium SC data only)
cellranger_localcores (int): (optional) maximum number of cores
cellranger can request in jobmode 'local' (10xGenomics Chromium
SC data only)
cellranger_localmem (int): (optional) maximum memory cellranger
can request in jobmode 'local' (10xGenomics Chromium SC data
only)
cellranger_ignore_dual_index (bool): (optional) on a dual-indexed
flowcell where the second index was not used for the 10x
sample, ignore it (10xGenomics Chromium SC data only)
"""
# Report protocol
print "Protocol : %s" % protocol
if protocol not in MAKE_FASTQS_PROTOCOLS:
raise Exception("Unknown protocol: '%s' (must be one of "
"%s)" % (protocol, ','.join([MAKE_FASTQS_PROTOCOLS])))
# Unaligned dir
if unaligned_dir is not None:
ap.params['unaligned_dir'] = unaligned_dir
elif ap.params['unaligned_dir'] is None:
ap.params['unaligned_dir'] = 'bcl2fastq'
print "Output dir : %s" % ap.params.unaligned_dir
# Sample sheet
if sample_sheet is None:
sample_sheet = ap.params.sample_sheet
if not os.path.isabs(sample_sheet):
sample_sheet = os.path.join(ap.analysis_dir, sample_sheet)
if not os.path.isfile(sample_sheet):
raise Exception("Missing sample sheet '%s'" % sample_sheet)
ap.params['sample_sheet'] = sample_sheet
print "Source sample sheet : %s" % ap.params.sample_sheet
# Check requested lanes are actually present
print "Lanes : %s" % ('all' if lanes is None else ','.join(
[str(l) for l in lanes]))
if lanes is not None:
s = IlluminaData.SampleSheet(ap.params.sample_sheet)
if not s.has_lanes:
raise Exception("Requested subset of lanes but "
"samplesheet doesn't contain any "
"lane information")
samplesheet_lanes = list(set([l['Lane'] for l in s]))
for l in lanes:
if l not in samplesheet_lanes:
raise Exception("Requested lane '%d' not present "
"in samplesheet" % l)
# Make a temporary sample sheet
if lanes:
lanes_id = ".L%s" % ''.join([str(l) for l in lanes])
else:
lanes_id = ""
sample_sheet = os.path.join(
ap.tmp_dir,
"SampleSheet%s.%s.csv" % (lanes_id, time.strftime("%Y%m%d%H%M%S")))
make_custom_sample_sheet(ap.params.sample_sheet, sample_sheet, lanes=lanes)
# Check the temporary sample sheet
print "Checking temporary sample sheet"
invalid_barcodes = SampleSheetLinter(
sample_sheet_file=sample_sheet).has_invalid_barcodes()
if invalid_barcodes:
logger.error("Invalid barcodes detected")
for line in invalid_barcodes:
logger.critical("%s" % line)
invalid_characters = SampleSheetLinter(
sample_sheet_file=sample_sheet).has_invalid_characters()
if invalid_characters:
logger.critical("Invalid non-printing/non-ASCII characters "
"detected")
if invalid_barcodes or invalid_characters:
raise Exception("Errors detected in generated sample sheet")
# Adjust verification settings for 10xGenomics Chromium SC
# data if necessary
verify_include_sample_dir = False
if has_chromium_sc_indices(sample_sheet):
if protocol in (
'10x_chromium_sc',
'10x_chromium_sc_atac',
):
# Force inclusion of sample-name subdirectories
# when verifying Chromium SC data
print "Sample sheet includes Chromium SC indices"
verify_include_sample_dir = True
else:
# Chromium SC indices detected but not using
# 10x_chromium_sc protocol
raise Exception("Detected 10xGenomics Chromium SC indices "
"in generated sample sheet but protocol "
"'%s' has been specified; use an "
"appropriate '10x_...' protocol for these "
"indices" % protocol)
# Check for pre-existing Fastq outputs
if verify_fastq_generation(ap,
unaligned_dir=ap.params.unaligned_dir,
lanes=lanes,
include_sample_dir=verify_include_sample_dir):
print "Expected Fastq outputs already present"
skip_rsync = True
skip_fastq_generation = True
# Check if there's anything to do
if (skip_rsync and skip_fastq_generation) and \
not (generate_stats or analyse_barcodes):
print "Nothing to do"
return
# Log dir
log_dir = 'make_fastqs'
if protocol != 'standard':
log_dir += "_%s" % protocol
if lanes:
log_dir += "_L%s" % ''.join([str(l) for l in sorted(lanes)])
ap.set_log_dir(ap.get_log_subdir(log_dir))
# Fetch primary data
if not skip_rsync and not ap.params.acquired_primary_data:
if get_primary_data(ap) != 0:
logger.error("Failed to acquire primary data")
raise Exception("Failed to acquire primary data")
else:
ap.params['acquired_primary_data'] = True
if only_fetch_primary_data:
return
# Deal with platform information
if not platform:
platform = ap.metadata.platform
# Do fastq generation using the specified protocol
if not skip_fastq_generation:
# Set primary data location and report info
primary_data_dir = os.path.join(ap.params.primary_data_dir,
os.path.basename(ap.params.data_dir))
print "Primary data dir : %s" % primary_data_dir
try:
illumina_run = IlluminaData.IlluminaRun(primary_data_dir,
platform=platform)
except IlluminaData.IlluminaDataPlatformError as ex:
logger.critical("Error loading primary data: %s" % ex)
if platform is None:
logger.critical("Try specifying platform using --platform?")
else:
logger.critical("Check specified platform is valid (or "
"omit --platform")
raise Exception("Error determining sequencer platform")
print "Platform : %s" % illumina_run.platform
print "Bcl format : %s" % illumina_run.bcl_extension
# Set platform in metadata
ap.metadata['platform'] = illumina_run.platform
# Bases mask
if bases_mask is not None:
ap.params['bases_mask'] = bases_mask
bases_mask = ap.params.bases_mask
print "Bases mask setting : %s" % bases_mask
if protocol not in (
'10x_chromium_sc',
'10x_chromium_sc_atac',
):
if bases_mask == "auto":
print "Determining bases mask from RunInfo.xml"
bases_mask = get_bases_mask(illumina_run.runinfo_xml,
sample_sheet)
if not bases_mask_is_valid(bases_mask):
raise Exception("Invalid bases mask: '%s'" % bases_mask)
# Do fastq generation according to protocol
if protocol == 'icell8':
# ICell8 data
# Update bcl2fastq settings appropriately
print "Updating read trimming and masking for ICell8"
minimum_trimmed_read_length = 21
mask_short_adapter_reads = 0
# Reset the default bases mask
bases_mask = IlluminaData.IlluminaRunInfo(
illumina_run.runinfo_xml).bases_mask
bases_mask = get_icell8_bases_mask(bases_mask,
sample_sheet=sample_sheet)
if not bases_mask_is_valid(bases_mask):
raise Exception("Invalid bases mask: '%s'" % bases_mask)
# Switch to standard protocol
protocol = 'standard'
if protocol == 'standard':
# Standard protocol
try:
exit_code = bcl_to_fastq(
ap,
unaligned_dir=ap.params.unaligned_dir,
sample_sheet=sample_sheet,
primary_data_dir=primary_data_dir,
require_bcl2fastq=require_bcl2fastq_version,
bases_mask=bases_mask,
ignore_missing_bcl=ignore_missing_bcl,
ignore_missing_stats=ignore_missing_stats,
no_lane_splitting=no_lane_splitting,
minimum_trimmed_read_length=minimum_trimmed_read_length,
mask_short_adapter_reads=mask_short_adapter_reads,
nprocessors=nprocessors,
runner=runner)
except Exception as ex:
raise Exception("Bcl2fastq stage failed: '%s'" % ex)
elif protocol == '10x_chromium_sc':
# 10xGenomics Chromium SC
if bases_mask == 'auto':
bases_mask = None
try:
# Check we have cellranger
cellranger = find_program('cellranger')
if not cellranger:
raise Exception("No cellranger package found")
cellranger_software_info = cellranger_info(cellranger)
print "Using cellranger %s: %s" % \
(cellranger_software_info[-1],
cellranger)
# Check we have bcl2fastq
bcl2fastq = find_program('bcl2fastq')
if not bcl2fastq:
raise Exception("No bcl2fastq package found")
bcl2fastq = available_bcl2fastq_versions(
paths=(os.path.dirname(bcl2fastq), ), reqs='>=2.17')
if not bcl2fastq:
raise Exception("No appropriate bcl2fastq software "
"located")
bcl2fastq = bcl2fastq[0]
bcl2fastq_info = bcl_to_fastq_info(bcl2fastq)
print "Using bcl2fastq %s: %s" % (bcl2fastq_info[-1],
bcl2fastq)
# Store info on bcl2fastq package
ap.metadata['bcl2fastq_software'] = bcl2fastq_info
# Store info on cellranger package
ap.metadata['cellranger_software'] = cellranger_software_info
# Put a copy of sample sheet in the log directory
shutil.copy(sample_sheet, ap.log_dir)
# Determine output directory absolute path
output_dir = ap.params.unaligned_dir
if not os.path.isabs(output_dir):
output_dir = os.path.join(ap.analysis_dir, output_dir)
# Run cellranger mkfastq
exit_code = run_cellranger_mkfastq(
sample_sheet=sample_sheet,
primary_data_dir=primary_data_dir,
output_dir=output_dir,
lanes=(None if lanes is None else ','.join(
[str(l) for l in lanes])),
bases_mask=bases_mask,
cellranger_exe=cellranger,
cellranger_jobmode=cellranger_jobmode,
cellranger_maxjobs=cellranger_maxjobs,
cellranger_mempercore=cellranger_mempercore,
cellranger_jobinterval=cellranger_jobinterval,
cellranger_localcores=cellranger_localcores,
cellranger_localmem=cellranger_localmem,
working_dir=ap.analysis_dir,
log_dir=ap.log_dir)
except Exception as ex:
raise Exception("'cellranger mkfastq' stage failed: "
"'%s'" % ex)
# Turn off barcode analysis
analyse_barcodes = False
elif protocol == '10x_chromium_sc_atac':
# 10xGenomics Chromium scATAC-seq
exit_code = bcl_to_fastq_10x_chromium_sc_atac(
ap,
output_dir=ap.params.unaligned_dir,
sample_sheet=sample_sheet,
primary_data_dir=primary_data_dir,
lanes=lanes,
bases_mask=bases_mask,
cellranger_jobmode=cellranger_jobmode,
cellranger_maxjobs=cellranger_maxjobs,
cellranger_mempercore=cellranger_mempercore,
cellranger_jobinterval=cellranger_jobinterval,
cellranger_localcores=cellranger_localcores,
cellranger_localmem=cellranger_localmem,
log_dir=ap.log_dir)
# Turn off barcode analysis
analyse_barcodes = False
else:
# Unknown protocol
raise Exception("Unknown protocol '%s'" % protocol)
# Check the outputs
if exit_code != 0:
raise Exception("Fastq generation finished with error: "
"exit code %d" % exit_code)
if not verify_fastq_generation(
ap, lanes=lanes, include_sample_dir=verify_include_sample_dir):
# Check failed
logger.error("Failed to verify output Fastqs against "
"sample sheet")
# Try to load the data from unaligned dir
try:
illumina_data = IlluminaData.IlluminaData(
ap.analysis_dir, unaligned_dir=ap.params.unaligned_dir)
except IlluminaData.IlluminaDataError as ex:
raise Exception("Unable to load data from %s: %s" %
(ap.params.unaligned_dir, ex))
# Generate a list of missing Fastqs
missing_fastqs = IlluminaData.list_missing_fastqs(
illumina_data,
sample_sheet,
include_sample_dir=verify_include_sample_dir)
assert (len(missing_fastqs) > 0)
missing_fastqs_file = os.path.join(ap.log_dir,
"missing_fastqs.log")
print "Writing list of missing Fastq files to %s" % \
missing_fastqs_file
with open(missing_fastqs_file, 'w') as fp:
for fq in missing_fastqs:
fp.write("%s\n" % fq)
# Create empty FASTQs
if create_empty_fastqs is None:
try:
create_empty_fastqs = \
ap.settings.platform[ap.metadata.platform].\
create_empty_fastqs
except (KeyError, AttributeError):
pass
if create_empty_fastqs is None:
create_empty_fastqs = \
ap.settings.bcl2fastq.create_empty_fastqs
if create_empty_fastqs:
logger.warning("Making 'empty' placeholder Fastqs")
for fq in missing_fastqs:
fastq = os.path.join(ap.analysis_dir,
ap.params.unaligned_dir, fq)
print "-- %s" % fastq
if not os.path.exists(os.path.dirname(fastq)):
mkdirs(os.path.dirname(fastq))
with gzip.GzipFile(filename=fastq, mode='wb') as fp:
fp.write('')
else:
raise Exception("Fastq generation failed to produce "
"expected outputs")
# Generate statistics
if generate_stats:
fastq_statistics(ap,
stats_file=stats_file,
per_lane_stats_file=per_lane_stats_file,
unaligned_dir=ap.params.unaligned_dir,
nprocessors=nprocessors,
runner=runner)
# Run barcode analysis
if analyse_barcodes:
# Determine output directory
if barcode_analysis_dir is not None:
ap.params['barcode_analysis_dir'] = barcode_analysis_dir
elif ap.params.barcode_analysis_dir is None:
ap.params['barcode_analysis_dir'] = 'barcode_analysis'
barcode_analysis_dir = ap.params.barcode_analysis_dir
if not os.path.isabs(barcode_analysis_dir):
barcode_analysis_dir = os.path.join(ap.params.analysis_dir,
barcode_analysis_dir)
# Report title
title = "Barcode analysis for %s" % ap.metadata.run_name
# Log file
log_file = os.path.join(ap.log_dir, "analyse_barcodes.log")
# Set up runner
if runner is None:
runner = ap.settings.general.default_runner
runner.set_log_dir(ap.log_dir)
# Get scheduler parameters
max_jobs = ap.settings.general.max_concurrent_jobs
poll_interval = ap.settings.general.poll_interval
# Create and run barcode analysis pipeline
barcode_analysis = AnalyseBarcodes(
os.path.join(ap.params.analysis_dir, ap.params.unaligned_dir))
barcode_analysis.run(barcode_analysis_dir,
title=title,
lanes=lanes,
sample_sheet=sample_sheet,
log_file=log_file,
runner=runner,
max_jobs=max_jobs,
poll_interval=poll_interval,
verbose=False)
# Make a 'projects.info' metadata file
if lanes:
ap.update_project_metadata_file()
else:
ap.make_project_metadata_file()
# Remove primary data
if remove_primary_data:
remove_primary_data(ap)
