def main():
"""Start here."""
args = parseArgs(sys.argv[1:])
global experiment
experiment = convert_to_filename(args.experiment)
gbkfile = args.genome
reads = args.input
samples = args.samples
# TODO(Test that disruption is between 0.0 and 1.0 (or absent, default 1.0))
disruption = float(args.disruption)
nobarcodes = args.nobarcodes
global keepall
keepall = args.keepall
# Organism reference files called 'genome.fna' etc
organism = 'genome'
# --- ORGANIZE SAMPLE LIST AND FILE PATHS --- #
pipeline_organize(samples)
# --- DEMULTIPLEX OR MOVE FILES IF ALREADY DEMULTIPLEXED --- #
if nobarcodes:
pipeline_no_demultiplex(reads)
else:
pipeline_demultiplex(reads)
# --- BOWTIE MAPPING --- #
genomeDir = 'results/{experiment}/genome_lookup/'.format(experiment=experiment)
pipeline_mapping(gbkfile, organism, genomeDir, disruption)
# --- ANALYSIS OF RESULTS --- #
pipeline_analysis()
def main():
"""Start here."""
args = parseArgs(sys.argv[1:])
global experiment
experiment = convert_to_filename(args.experiment)
gbkfile = args.genome
reads = args.input
samples = args.samples
disruption = float(args.disruption) #set input disruption value as a float as input can be int
if disruption < 0.0 or disruption > 1.0: #test whether disruption value is from 0.0 to 1.0
disruption = 1.0 #if disruption value is not from 0.0 to 1.0, set disruption to default value of 1.0
print('\n*** WARNING ***'\
'\nDisruption value: {}'
'\nDisruption value must be from 0.0 to 1.0'\
'\nProceeding with default value of 1.0\n'.format(float(args.disruption)))
nobarcodes = args.nobarcodes
global keepall
keepall = args.keepall
# Logging of sample info
global logdata
logdata = {}
# Organism reference files called 'genome.fna' etc
organism = 'genome'
# --- ORGANIZE SAMPLE LIST AND FILE PATHS --- #
pipeline_organize(samples)
# --- DEMULTIPLEX OR MOVE FILES IF ALREADY DEMULTIPLEXED --- #
if nobarcodes:
pipeline_no_demultiplex(reads)
else:
pipeline_demultiplex(reads)
# --- BOWTIE MAPPING --- #
genomeDir = 'results/{experiment}/genome_lookup/'.format(experiment=experiment)
pipeline_mapping(gbkfile, organism, genomeDir, disruption)
# --- ANALYSIS OF RESULTS --- #
pipeline_analysis()
# --- CONFIRM COMPLETION --- #
print('\n===================='\
'\n* Done *'\
'\n====================\n')
def sample_prep(sample_file, barcode_qc):
"""
Return ordered dictionary of sample name and barcode for each sample.
samples = OrderedDict([('name1', {'name': 'name1', 'barcode': 'barcode1'}),
('name2', {'name': 'name2', 'barcode': 'barcode2'})])
ignores comment lines in sample file that begin with #
Exit if duplicate sample names or barcodes are identified.
If barcode_qc=True, exit if duplicate barcodes are identified.
"""
sampleDict = collections.OrderedDict()
with open(sample_file, 'r', newline='') as csvfile:
sampleReader = csv.reader(csvfile, delimiter='\t')
for line in sampleReader:
if not line[0].startswith('#'):
# sample into a string that can be a filename; barcode to uppercase
new_sample = convert_to_filename(line[0])
if new_sample in sampleDict:
sys.stdout.write('Error: redundant sample identifier {}'.format(new_sample))
exit(1)
try:
new_barcode = line[1].upper()
except Exception:
# Of for downstream only if samples are already demultiplexed
new_barcode = ''
else:
if barcode_qc:
if new_barcode == '':
sys.stdout.write('Missing barcode for sample {}'.format(new_sample))
exit(1)
if new_barcode in sampleDict.values():
sys.stdout.write('Error: redundant barcode {}'.format(new_barcode))
exit(1)
sampleDict[new_sample] = {
'name': new_sample,
'barcode': new_barcode
}
return sampleDict
