def test__03_prediction_06(self):
print('test pred 6')
expected = '06B'
refs_dir = os.path.join(data_dir,'serotype_object')
cd_cluster = os.path.join(data_dir,'test_serotype_2_cluster.tsv')
fw_read = os.path.join(data_dir,'06B_1.fq.gz')
bw_read = os.path.join(data_dir,'06B_2.fq.gz')
prefix = os.path.join(data_dir,'06B_1')
cluster = 'cluster'
assemblie_file = os.path.join(prefix,'assemblies.fa')
s = serotyping.Serotyping(refs_dir,fw_read, bw_read, prefix,'--noclean')
s.cluster_serotype_dict = {
'cluster' : ['06A','06B','06C','06D','06E'],
'NT' : ['NT'],
'cluster_1' : ['07A','07F']
}
s.best_serotype = '06A'
s.cluster_count = {
'cluster': 5,
'NT': 1,
'cluster_1': 2
}
s._prediction(assemblie_file,cluster)
self.assertEqual(expected,s.sero)
shutil.rmtree(prefix)
def test_06F(self):
expected = '06F'
refs_dir = os.path.join(data_dir,'serotype_object')
cd_cluster = os.path.join(data_dir,'test_serotype_2_cluster.tsv')
fw_read = os.path.join(data_dir,'09V','09V_1.fq.gz')
bw_read = os.path.join(data_dir,'09V','09V_2.fq.gz')
prefix = os.path.join(data_dir,'06F')
kmer_size = '51'
cluster = 'cluster'
assemblie_file = os.path.join(data_dir,'06F','assemblies.fa')
s = serotyping.Serotyping(refs_dir, fw_read, bw_read, prefix,'--noclean')
s.cluster_serotype_dict = {
'cluster' : ['06A','06B','06C','06D','06E','06F','06G'],
'NT' : ['NT'],
'cluster_1' : ['07A','07F'],
'cluster_2':['11A','11B','11C','11D','11F'] }
s.best_serotype = '06A'
s.cluster_count = {
'cluster': 7,
'NT': 1,
'cluster_1': 2,
'cluster_2': 3
}
s._prediction(assemblie_file,cluster)
self.assertEqual(expected,s.sero)
def test_07C(self):
expected = '07C'
refs_dir = os.path.join(data_dir,'serotype_object')
cd_cluster = os.path.join(data_dir,'test_serotype_2_cluster.tsv')
fw_read = os.path.join(data_dir,'09V','09V_1.fq.gz')
bw_read = os.path.join(data_dir,'09V','09V_2.fq.gz')
prefix = os.path.join(data_dir,'ERR1439287')
kmer_size = '51'
cluster = 'cluster_1'
assemblie_file = os.path.join(data_dir,'ERR1439287','assemblies.fa')
s = serotyping.Serotyping(refs_dir, fw_read, bw_read, prefix,'--noclean')
s.cluster_serotype_dict = {
'cluster' : ['06A','06B','06C','06D','06E'],
'NT' : ['NT'],
'cluster_1' : ['07B','07C','40'],
'cluster_2':['33A','33F','37'] }
s.best_serotype = '07C'
s.cluster_count = {
'cluster': 5,
'NT': 1,
'cluster_1': 3,
'cluster_2': 3
}
s._prediction(assemblie_file,cluster)
self.assertEqual(expected,s.sero)
def test_mixed_sample_15B_C(self):
expected = '15B/15C'
refs_dir = os.path.join(data_dir,'serotype_object')
cd_cluster = os.path.join(data_dir,'test_serotype_2_cluster.tsv')
fw_read = os.path.join(data_dir,'15B_C','15B_C_1.fq')
bw_read = os.path.join(data_dir,'15B_C','15B_C_2.fq')
prefix = os.path.join(data_dir,'15B_C')
cluster = 'cluster_3'
assemblie_file = os.path.join(data_dir,'15B_C','assemblies.fa')
s = serotyping.Serotyping(refs_dir, fw_read, bw_read, prefix,'--noclean')
s.cluster_serotype_dict = {
'cluster' : ['06A','06B','06C','06D','06E'],
'NT' : ['NT'],
'cluster_1' : ['07A','07F'],
'cluster_2':['10A','10B'],
'cluster_3':['15A','15B','15C','15F']
}
s.best_serotype = '15C'
s.cluster_count = {
'cluster': 5,
'NT': 1,
'cluster_1': 2,
'cluster_2': 2,
'cluster_3': 4
}
s._prediction(assemblie_file,cluster)
self.assertEqual(expected,s.sero)
def full_run_09V(self):
expected = '09V'
refs_dir = os.path.join(data_dir,'serotype_object')
fw_read = os.path.join(data_dir,'09V','09V_1.fq.gz')
bw_read = os.path.join(data_dir,'09V','09V_2.fq.gz')
prefix = os.path.join('09V')
s = serotyping.Serotyping(refs_dir, fw_read, bw_read, prefix,'--noclean')
s.run()
self.assertEqual(expected,s.sero)
def test_run_kmc(self):
expected = '06A'
refs_dir = os.path.join(data_dir,'serotype_object')
cd_cluster = os.path.join(data_dir,'test_serotype_2_cluster.tsv')
fw_read = os.path.join(data_dir,'06B_1.fq.gz')
bw_read = os.path.join(data_dir,'06B_2.fq.gz')
meta_data = os.path.join(data_dir,'expected_pneumocat_meta.tsv')
prefix = '06B_1'
kmer_size = '51'
kmer_db = 'kmer_db'
ariba_cluster_db = 'ariba_db'
reference_fasta =os.path.join(data_dir,'serotype_object','reference.fasta')
s = serotyping.Serotyping( refs_dir,fw_read, bw_read, prefix,'--noclean')
s._run_kmc()
self.assertEqual(expected,s.best_serotype)
def test_01_run_ariba_on_cluster(self):
print('test ariba')
refs_dir = os.path.join(data_dir,'serotype_object')
cd_cluster = os.path.join(data_dir,'test_serotype_2_cluster.tsv')
fw_read = os.path.join(data_dir,'06B_1.fq.gz')
bw_read = os.path.join(data_dir,'06B_2.fq.gz')
meta_data = os.path.join(data_dir,'expected_pneumocat_meta.tsv')
prefix = os.path.join(data_dir,'06B_1')
reference_fasta =os.path.join(data_dir,'serotype_object','reference.fasta')
cluster = 'cluster'
s = serotyping.Serotyping( refs_dir,fw_read, bw_read, prefix,'--noclean')
s.cluster_serotype_dict = {
'cluster' : ['06A','06B','06C','06D','06E'],
'NT' : ['NT'],
'cluster_1' : ['07A','07F']
}
s._run_ariba_on_cluster(cluster)
def run(options):
if (options.read1 == options.read2):
print(
'Same file provided for forwards and reverse reads. Cannot continue',
file=sys.stderr)
sys.exit(1)
if (options.read1.rsplit('_', 1)[0] != options.read2.rsplit('_', 1)[0]):
print(
'Names for forwards and reverse reads does not match. Cannot continue',
file=sys.stderr)
sys.exit(1)
sero = serotyping.Serotyping(options.databases,
options.read1,
options.read2,
options.prefix,
clean=(not options.noclean))
cov = options.coverage
sero.run()
