def complete(args):
"""
Run all modules
"""
assert args.reference, "need the reference genome"
assert args.bams, "no files detected. Add vcf and bam files"
assert args.region, "need region bed file"
data = _prepare_samples(args)
vcf = [d[0]['vcf'] for d in data]
bam = [d[0]['bam'] for d in data]
fastqc = [d[0]['fastqc'] for d in data]
yaml_file = [fn for fn in args.bams if fn.endswith("yaml")]
assert len(vcf) == len(bam), "no paired bam/vcf files found. %s %s" % (vcf, bam)
assert yaml_file, "No bcbio yaml file found."
assert fastqc, "No fastqc files"
cluster = []
if args.scheduler:
cluster = ['-n', args.numcores, '-s', args.scheduler, '-q', args.queue, '-p', args.tag, '-t', args.paralleltype]
if args.resources:
cluster += ['-r'] + args.resources
cluster = map(str, cluster)
print "doing basic-bam"
new_args = ['--run', 'basic-bam', '--out', 'basic-bam'] + bam
new_args = params().parse_args(new_args)
calculate_bam(new_args)
print "doing metrics"
new_args = ['--run', 'metrics', '--out', 'metrics', yaml_file[0]]
new_args = params().parse_args(new_args)
bcbio_metrics(new_args)
print "doing fastqc parsing"
new_args = ['--run', 'fastqc', '--out', 'fastqc'] + fastqc
new_args = params().parse_args(new_args)
merge_fastq(data, new_args)
print "doing stats-coverage"
new_args = ['--run', 'stats-coverage', '--out', 'coverage', '--region', args.region] + bam + cluster
new_args = params().parse_args(new_args)
average_exome_coverage(data, new_args)
print "doing bias-coverage"
new_args = ['--run', 'bias-coverage', '--out', 'bias', '--region', args.region] + bam + cluster
new_args = params().parse_args(new_args)
bias_exome_coverage(data, new_args)
print "doing cg-depth in vcf files"
new_args = ['--run', 'cg-vcf', '--out', 'cg', '--region', args.region, '--reference', args.reference] + bam + vcf + cluster
new_args = params().parse_args(new_args)
calculate_cg_depth_coverage(data, new_args)
print "doing report"
report("report")
def _new_complete(args):
data = _read_final(args.bams[0])
print data
# config = _config(args)
# new_data = []
# for s in data:
# data['name'] = s
# data['config'] = config
# new_data.append(data[s])
assert args.reference, "need the reference genome"
assert args.bams, "no files detected. Add vcf and bam files"
assert args.region, "need region bed file"
vcf_type = data.values()[0]['vcf'].keys()[0]
vcf = [d['vcf'][vcf_type] for d in data.values() if 'vcf' in d]
bam = [d['bam']['ready'] for d in data.values() if 'bam' in d]
fastqc = [d['qc']['fastqc'] for d in data.values() if 'qc' in d]
yaml_file = args.bams[0]
assert len(vcf) == len(bam), "no paired bam/vcf files found. %s %s" % (vcf, bam)
assert yaml_file, "No bcbio yaml file found."
assert fastqc, "No fastqc files"
cluster = []
if args.scheduler:
cluster = ['-n', args.numcores, '-s', args.scheduler, '-q', args.queue, '-p', args.tag, '-t', args.paralleltype]
if args.resources:
cluster += ['-r'] + args.resources
cluster = map(str, cluster)
galaxy = []
if args.galaxy:
galaxy = ['--galaxy', args.galaxy]
print "copy qsignature"
fn = glob.glob(op.join(_get_final_folder(yaml_file)['upload'], "*/mixup_check/qsignature.ma"))
if file_exists(fn[0]) and not file_exists("qsignature.ma"):
shutil.copy(fn[0], "qsignature.ma")
print "doing basic-bam"
new_args = ['--run', 'basic-bam', '--out', 'basic-bam'] + galaxy + bam
new_args = params().parse_args(new_args)
calculate_bam(new_args)
print "doing metrics"
new_args = ['--run', 'metrics', '--out', 'metrics', yaml_file] + galaxy
new_args = params().parse_args(new_args)
bcbio_metrics(new_args)
print "doing fastqc parsing"
new_args = ['--run', 'fastqc', '--out', 'fastqc'] + galaxy + fastqc + bam
new_args = params().parse_args(new_args)
data = _prepare_samples(new_args)
merge_fastq(data, new_args)
print "doing stats-coverage"
new_args = ['--run', 'stats-coverage', '--out', 'coverage', '--region', args.region] + galaxy + bam + cluster
new_args = params().parse_args(new_args)
data = _prepare_samples(new_args)
average_exome_coverage(data, new_args)
print "doing bias-coverage"
new_args = ['--run', 'bias-coverage', '--out', 'bias', '--region', args.region, '--n_sample', str(args.n_sample)] + galaxy + bam + cluster
new_args = params().parse_args(new_args)
data = _prepare_samples(new_args)
bias_exome_coverage(data, new_args)
print "doing cg-depth in vcf files"
new_args = ['--run', 'cg-vcf', '--out', 'cg', '--region', args.region, '--reference', args.reference] + galaxy + bam + vcf + cluster
new_args = params().parse_args(new_args)
data = _prepare_samples(new_args)
calculate_cg_depth_coverage(data, new_args)
print "doing report"
report("report")
if __name__ == "__main__":
parser = params()
args = parser.parse_args()
if args.run == "stats-coverage":
data = _prepare_samples(args)
average_exome_coverage(data, args)
elif args.run == "bias-coverage":
data = _prepare_samples(args)
bias_exome_coverage(data, args)
elif args.run == "tstv":
calculate_tstv(args)
elif args.run == "basic-bam":
calculate_bam(args)
elif args.run == "metrics":
bcbio_metrics(args)
elif args.run == "cg-vcf":
data = _prepare_samples(args)
calculate_cg_depth_coverage(data, args)
elif args.run == "plot":
save_multiple_regions_coverage(args.bams, args.out, args.region)
elif args.run == "fastqc":
data = _prepare_samples(args)
merge_fastq(data, args)
elif args.run == "report":
report(args)
elif args.run == "complete":
complete(args)
elif args.run == "final":
