def compress_files(*args):
return utils.compress_files(*args)
def run_main(config, config_file, fc_dir, work_dir, run_info_yaml):
_record_sw_versions(config, os.path.join(work_dir, "bcbb_software_versions.txt"))
prog = utils.RecordProgress(work_dir)
to_compress = set()
prog.progress("analysis_start")
align_dir = os.path.join(work_dir, "alignments")
run_module = "bcbio.distributed"
fc_name, fc_date, run_info = get_run_info(fc_dir, config, run_info_yaml)
fastq_dir, galaxy_dir, config_dir = _get_full_paths(get_fastq_dir(fc_dir),
config, config_file)
config_file = os.path.join(config_dir, os.path.basename(config_file))
dirs = {"fastq": fastq_dir, "galaxy": galaxy_dir, "align": align_dir,
"work": work_dir, "flowcell": fc_dir, "config": config_dir}
run_parallel = parallel_runner(run_module, dirs, config, config_file)
run_items = add_multiplex_across_lanes(run_info["details"], dirs["fastq"], fc_name)
lanes = ((info, fc_name, fc_date, dirs, config) for info in run_items)
lane_items = run_parallel("process_lane", lanes)
[to_compress.add(f) for f in lane_items[0][0:2]]
prog.progress("process_lane")
# upload the sequencing report to Google Docs
# will skip this for now and rely on external mechanism for uploading this data
#gdocs_indicator = os.path.join(work_dir, "gdocs_report_complete.txt")
#if not os.path.exists(gdocs_indicator) \
#and queue_report(fc_date, fc_name, os.path.abspath(run_info_yaml), dirs, config, config_file):
# utils.touch_file(gdocs_indicator)
# Remove spiked in controls, contaminants etc.
lane_items = run_parallel("remove_contaminants", lane_items)
[to_compress.add(f) for f in lane_items[0][0:2]]
prog.progress("remove_contaminants")
align_items = run_parallel("process_alignment", lane_items)
[to_compress.add(f) for f in align_items[0]['fastq']]
prog.progress("process_alignment")
# process samples, potentially multiplexed across multiple lanes
samples = organize_samples(align_items, dirs, config_file)
samples = run_parallel("merge_sample", samples)
to_compress.add(samples[0][0]['fastq1'])
to_compress.add(samples[0][0]['fastq2'])
prog.progress("merge_sample")
samples = run_parallel("mark_duplicates_sample", samples)
to_compress.add(samples[0][0]['fastq1'])
to_compress.add(samples[0][0]['fastq2'])
prog.progress("mark_duplicates_sample")
run_parallel("screen_sample_contaminants", samples)
prog.progress("screen_sample_contaminants")
samples = run_parallel("recalibrate_sample", samples)
prog.progress("recalibrate_sample")
samples = parallel_realign_sample(samples, run_parallel)
prog.progress("realign_sample")
samples = parallel_variantcall(samples, run_parallel)
prog.progress("variantcall")
samples = run_parallel("detect_sv", samples)
prog.progress("detect_sv")
samples = run_parallel("process_sample", samples)
prog.progress("process_sample")
samples = run_parallel("generate_bigwig", samples, {"programs": ["ucsc_bigwig"]})
prog.progress("generate_bigwig")
write_project_summary(samples)
write_metrics(run_info, fc_name, fc_date, dirs)
prog.progress("write_metrics")
# Write statusdb metrics
# will skip this for now and rely on external mechanism for uploading this data
#report_to_statusdb(fc_name, fc_date, run_info_yaml, dirs, config)
#Compress all files in to_compress
if config['algorithm'].get('compress_files', True):
(before, after) = utils.compress_files(to_compress)
logger.info("Space used by the files before compressing (in bytes): " \
+ str(before))
logger.info("Space used by the files after compressing (in bytes): " \
+ str(after))
logger.info("Saved space (in bytes): " + str(before - after))
def compress_files(*args):
return utils.compress_files(*args)
def run_main(config, config_file, fc_dir, work_dir, run_info_yaml):
_record_sw_versions(config, os.path.join(work_dir, "bcbb_software_versions.txt"))
prog = RecordProgress(work_dir)
to_compress = set()
prog.progress("analysis_start")
align_dir = os.path.join(work_dir, "alignments")
run_module = "bcbio.distributed"
fc_name, fc_date, run_info = get_run_info(fc_dir, config, run_info_yaml)
fastq_dir, galaxy_dir, config_dir = _get_full_paths(get_fastq_dir(fc_dir), config, config_file)
config_file = os.path.join(config_dir, os.path.basename(config_file))
dirs = {
"fastq": fastq_dir,
"galaxy": galaxy_dir,
"align": align_dir,
"work": work_dir,
"flowcell": fc_dir,
"config": config_dir,
}
run_parallel = parallel_runner(run_module, dirs, config, config_file)
run_items = add_multiplex_across_lanes(run_info["details"], dirs["fastq"], fc_name)
lanes = ((info, fc_name, fc_date, dirs, config) for info in run_items)
lane_items = run_parallel("process_lane", lanes)
[to_compress.add(f) for f in lane_items[0][0:2]]
prog.dummy()
prog.progress("process_lane")
# Remove spiked in controls, contaminants etc.
lane_items = run_parallel("remove_contaminants", lane_items)
[to_compress.add(f) for f in lane_items[0][0:2]]
prog.dummy()
prog.progress("remove_contaminants")
align_items = run_parallel("process_alignment", lane_items)
[to_compress.add(f) for f in align_items[0]["fastq"]]
prog.dummy()
prog.progress("process_alignment")
# process samples, potentially multiplexed across multiple lanes
samples = organize_samples(align_items, dirs, config_file)
samples = run_parallel("merge_sample", samples)
to_compress.add(samples[0][0]["fastq1"])
to_compress.add(samples[0][0]["fastq2"])
prog.dummy()
prog.progress("merge_sample")
samples = run_parallel("mark_duplicates_sample", samples)
to_compress.add(samples[0][0]["fastq1"])
to_compress.add(samples[0][0]["fastq2"])
prog.dummy()
prog.progress("mark_duplicates_sample")
run_parallel("screen_sample_contaminants", samples)
prog.dummy()
prog.progress("screen_sample_contaminants")
samples = run_parallel("recalibrate_sample", samples)
prog.dummy()
prog.progress("recalibrate_sample")
samples = parallel_realign_sample(samples, run_parallel)
prog.dummy()
prog.progress("realign_sample")
samples = parallel_variantcall(samples, run_parallel)
prog.dummy()
prog.progress("variantcall")
samples = run_parallel("detect_sv", samples)
prog.dummy()
prog.progress("detect_sv")
samples = run_parallel("process_sample", samples)
prog.dummy()
prog.progress("process_sample")
samples = run_parallel("generate_bigwig", samples, {"programs": ["ucsc_bigwig"]})
prog.dummy()
prog.progress("generate_bigwig")
write_project_summary(samples)
write_metrics(run_info, fc_name, fc_date, dirs)
prog.dummy()
prog.progress("write_metrics")
# Compress all files in to_compress
if config["algorithm"].get("compress_files", True):
(before, after) = utils.compress_files(to_compress)
logger.info("Space used by the files before compressing (in bytes): " + str(before))
logger.info("Space used by the files after compressing (in bytes): " + str(after))
logger.info("Saved space (in bytes): " + str(before - after))