def testSamples(self):
self.assertEqual(len(self.VCF.samples), 526)
self.assertEqual(self.VCF.info[0][1],'1')
self.assertEqual(self.VCF.gformat[0],'GT')
self.assertEqual(self.VCF.novel[0],'Y_2649856_A')
self.assertEqual('NA19088' in VCF.list_samples_with_alternate_allele(self.VCF,'rs11575897')
, True)
self.assertEqual(len(VCF.list_samples_with_alternate_allele(self.VCF,'rs11575897')),99)
self.assertEqual(self.VCF.hardyweinberg('rs11575897'), False)
def test_sample_summary(self):
self.assertEqual(len(self.VCF.samples), 526)
# Y chromosome shouldn't have any homozygous
#self.assertFalse(any(self.VCF.geno == 2))
print(any(self.VCF.geno == 2))
self.assertEqual(self.VCF.info[0][1], '1' )
self.assertEqual(self.VCF.gformat[0],'GT')
self.assertEqual(self.VCF.novel[0],'Y_2649856_A')
self.assertEqual('NA19088' in VCF.list_samples_with_alternate_allele(self.VCF,'rs11575897')
, True)
self.assertEqual(len(VCF.list_samples_with_alternate_allele(self.VCF,'rs11575897')),99)
def test_sample_summary(self):
self.assertEqual(len(self.VCF.samples), 526)
# Y chromosome shouldn't have any homozygous
#self.assertFalse(any(self.VCF.geno == 2))
print(any(self.VCF.geno == 2))
self.assertEqual(self.VCF.info[0][1], '1')
self.assertEqual(self.VCF.gformat[0], 'GT')
self.assertEqual(self.VCF.novel[0], 'Y_2649856_A')
self.assertEqual(
'NA19088'
in VCF.list_samples_with_alternate_allele(self.VCF,
'rs11575897'), True)
self.assertEqual(
len(VCF.list_samples_with_alternate_allele(self.VCF,
'rs11575897')), 99)
class TestLoadingVCF(unittest.TestCase):
""" Testing loading VCF files into pandas
"""
def setUp(self):
self.filename = './data/chrY.test.vcf'
self.VCF = VCF(self.filename)
def testSamples(self):
self.assertEqual(len(self.VCF.samples), 526)
self.assertEqual(self.VCF.info[0][1],'1')
self.assertEqual(self.VCF.gformat[0],'GT')
self.assertEqual(self.VCF.novel[0],'Y_2649856_A')
self.assertEqual('NA19088' in VCF.list_samples_with_alternate_allele(self.VCF,'rs11575897')
, True)
self.assertEqual(len(VCF.list_samples_with_alternate_allele(self.VCF,'rs11575897')),99)
self.assertEqual(self.VCF.hardyweinberg('rs11575897'), False)
def testInfo(self):
pass
def main():
""" Main loop that iterates over the desired loci to calculate Aellic
Imbalance
"""
#################################################################
# Argument and Options Parsing
#################################################################
p = optparse.OptionParser(__doc__)
p.add_option("-C",
"--chrom",
dest="Chrom",
help=("Chromosome to"
"restrict counting alleles on"))
p.add_option("-o",
"--output",
dest="filename",
help="write \
report to FILE")
p.add_option("-a",
"--annot",
dest="annot",
help="Annotation file\
for SNPs")
p.add_option("-G", "--genotype", dest="G", action='store', help=\
"Use imputed/genotypes if available, should be in VCF file format",
default=None)
p.add_option("-v",
"--vcf_file",
action="store_true",
dest="inputisvcffile",
help="the input is a VCF file",
default=False)
p.add_option("-q",
"--quality_threshold",
type="int",
dest="qual",
help="base quality threshold to take allele counts from")
p.add_option("-P", "--variant_positions", action="store", help="")
p.add_option("-p",
"--pileup",
action="store_true",
dest="p",
help="Input files are pileup files")
p.add_option("-D", "--debug", action="store_true", dest="D", help="debug")
p.add_option("-c",
"--count-threshold",
action="store",
type="int",
dest="c",
help="Set the count threshold for making AEI calls")
'''
p.add_option("-A", "--auto_parse", action="store_true", dest="auto",
help="Autoparse readgroups, if set to false will assume a\
single sample in each file")
'''
options, args = p.parse_args()
if options.qual: pass
else: options.qual = 20
bam_inputs = open(args[1], 'rU')
sample_to_file = {}
for line in bam_inputs:
line = line.split("\t")
sample_to_file[line[0]] = line[1].rstrip("\n").rstrip("/n")
file_to_sample = {v: k for k, v in sample_to_file.items()}
debug = 1
if 'vcf' in args[0]:
vcf = VCF(args[0])
chrm = vcf.vcf['#CHROM']
pos = vcf.vcf['POS']
#geno = vcf.geno
geno = pd.DataFrame(np.zeros((len(pos), len(sample_to_file))),
columns=pd.Index(sample_to_file.keys()))
elif options.annot:
# This is the annotation file that I actually use
# for the paper
chrom = 18
print('Right annotation file')
rsIDs = []
pos = []
try:
file_a = pysam.Tabixfile(args[0])
except IOError:
os.exit()
# :TODO fix this
# Currently counts at all SNPs
a_iter = file_a.fetch(str(chrom))
chrm = []
'''
base_path = '/proj/GenomicsHD/Atrial_RNASeq/'
s_ann = pd.read_pickle(base_path + 'ref/snp_annot/' + str(chrom) +\
'.pkl')
'''
debug = 0
for i in a_iter:
i = i.split("\t")
if not int(i[-5]) == 0:
rsIDs.append(i[3])
chrm.append('chr' + str(i[0]))
pos.append(int(i[1]))
'''
debug += 1
if debug > 200:
break
'''
geno = pd.DataFrame(np.zeros((len(rsIDs), len(sample_to_file))),
index=pd.Index(rsIDs),
columns=pd.Index(sample_to_file.keys()))
#print(s_ann.head())
pos = np.asarray(pos, dtype=np.uint32)
# Probably inefficient to pass in one array
chrm = np.asarray(chrm)
print('Chrom length')
print(len(chrm))
print(len(pos))
print(pos[-1])
# A tab delimited file mapping sample names to bams #############
if options.c:
count_threshold = options.c
else:
count_threshold = 20
multi_tuples = []
subset_geno = geno.ix[:, sample_to_file.keys()].copy()
subset_geno.rename(columns=sample_to_file, inplace=True)
for i in subset_geno.columns:
multi_tuples.append(i)
multi_tuples.append(i)
multi_tuples.append(i)
multi_tuples.append(i)
multi = zip(multi_tuples, [0, 1, 2, 3] * subset_geno.shape[1])
multi_index = pd.MultiIndex.from_tuples(multi, names=['sample', 'alleles'])
counts_matrix = pd.DataFrame(np.zeros(
(subset_geno.shape[0], len(subset_geno.columns) * 4), dtype=np.uint32),
index=subset_geno.index,
columns=multi_index)
c_m = aei_count_samples(subset_geno.values, subset_geno.columns.values,
counts_matrix.values, np.asarray(chrm), pos)
c_m = pd.DataFrame(c_m, index=subset_geno.index, columns=multi_index)
c_m.to_pickle(options.filename)
def setUp(self):
path = os.path.dirname(os.path.abspath(__file__))
self.filename = path + '/data/chrY.test.vcf'
self.VCF = VCF(self.filename)
def setUp(self):
self.filename = './data/chrY.test.vcf'
self.VCF = VCF(self.filename)
