def testBoundaryChr10(self):
BoundaryCheck.set_chrom('chr10')
b = BoundaryCheck(mb=[1,3])
self.assertTrue(b.valid)
self.assertFalse(b.NoExclusions())
self.assertTrue(b.TestBoundary(10, 1000000, ""))
self.assertTrue(b.TestBoundary(10, 1200000, ""))
self.assertTrue(b.TestBoundary(10, 3000000, ""))
self.assertFalse(b.TestBoundary(10, 3000001, ""))
self.assertFalse(b.TestBoundary(10, 999999, ""))
self.assertFalse(b.TestBoundary(1, 1000500, ""))
def testBoundaryInitBPWithInclusions(self):
BoundaryCheck.chrom = 1
b = BoundaryCheck(bp=[10000, 500000])
b.LoadSNPs(["rs12345", "rs23456"])
self.assertFalse(b.NoExclusions())
self.assertTrue(b.valid)
self.assertEqual(False, b.TestBoundary(1, 500, ""))
self.assertEqual(True, b.TestBoundary(1, 10000, ""))
self.assertEqual(True, b.TestBoundary(1, 500000, ""))
self.assertEqual(True, b.TestBoundary(1, 250000, ""))
self.assertEqual(False, b.TestBoundary(2, 250000, ""))
self.assertEqual(False, b.TestBoundary(10, 10000, ""))
self.assertTrue(b.TestBoundary(1, 1000000, "rs12345"))
self.assertTrue(b.TestBoundary(1, 1200000, "rs23456"))
self.assertFalse(b.TestBoundary(1, 1200011, "rs345678"))
def testTpedAnalysis(self):
# We'll start with the correct phenotype with the genotypes, so we'll use
# a boundary to restrict us to only use the first SNP
BoundaryCheck.chrom = 1
DataParser.boundary = BoundaryCheck()
pheno = PhenoCovar()
dataset = TransposedPedigreeParser(self.tfam_filename, self.tped_filename)
dataset.load_tfam(pheno)
dataset.load_genotypes()
results = [x for x in mv_esteq.RunAnalysis(dataset, pheno)]
self.assertAlmostEqual(0.0034756155, results[0].p_mvtest, places=6)
self.assertAlmostEqual(0.1134684009, results[0].betas[1], places=6)
self.assertAlmostEqual(0.0337649965541, results[0].beta_stderr[1], places=6)
self.assertAlmostEqual(0.0007779211, results[0].beta_pvalues[1], places=6)
self.assertAlmostEqual(-0.0033479839, results[0].betas[3], places=6)
self.assertAlmostEqual(0.0492050029324, results[0].beta_stderr[3], places=6)
self.assertAlmostEqual(0.9457525716, results[0].beta_pvalues[3], places=6)
self.assertAlmostEqual(0.57778118, results[1].p_mvtest, places=6)
self.assertAlmostEqual(0.02798537, results[1].betas[1], places=6)
self.assertAlmostEqual(0.033790691857, results[1].beta_stderr[1], places=6)
self.assertAlmostEqual(0.40755865, results[1].beta_pvalues[1], places=6)
self.assertAlmostEqual(0.03275892, results[1].betas[3], places=6)
self.assertAlmostEqual(0.0475661, results[1].beta_stderr[3], places=6)
self.assertAlmostEqual(0.49101013, results[1].beta_pvalues[3], places=6)
self.assertAlmostEqual(0.44661276, results[2].p_mvtest, places=6)
self.assertAlmostEqual(0.01663975, results[2].betas[1], places=6)
self.assertAlmostEqual(0.03443300, results[2].beta_stderr[1], places=6)
self.assertAlmostEqual(0.62891811, results[2].beta_pvalues[1], places=6)
self.assertAlmostEqual(0.05712017, results[2].betas[3], places=6)
self.assertAlmostEqual(0.04783608, results[2].beta_stderr[3], places=6)
self.assertAlmostEqual(0.232446188, results[2].beta_pvalues[3], places=6)
def setUp(self):
self.allele_1 = list("AAACCCGGGTCGTGTATACC")
self.allele_2 = list("CGTGTATACCAAACCCGGGT")
self.WriteTestFiles()
self.phenotypes = [0.1, 0.4, 1.0, 0.5, 0.9, 1.0, 0.1, 0.4, 1.0, 0.5, 0.9, 1.0]
self.sex = [1,2,1,1,2,2,1,1,2,2,2,1]
self.chrpos_encoding = mach_parser.Parser.chrpos_encoding
self.dosage_ext = mach_parser.Parser.dosage_ext
self.info_ext = mach_parser.Parser.info_ext
self.chrom = BoundaryCheck.chrom
self.boundary = DataParser.boundary
DataParser.boundary = BoundaryCheck()
self.min_maf = DataParser.min_maf
self.max_maf = DataParser.max_maf
self.snp_miss_tol = DataParser.snp_miss_tol
self.ind_miss_tol = DataParser.ind_miss_tol
DataParser.ind_exclusions = []
self.sex_as_covar = PhenoCovar.sex_as_covariate
self.has_sex = DataParser.has_sex
self.has_pheno = DataParser.has_pheno
self.has_parents = DataParser.has_parents
self.has_fid = DataParser.has_fid
self.has_liability = DataParser.has_liability
self.encoding = mach_parser.encoding
self.compression = DataParser.compressed_pedigree
DataParser.compressed_pedigree = True
#self.chunk_stride = mach_parser.chunk_stride
self.standardizer = libgwas.standardizer.get_standardizer()
libgwas.standardizer.set_standardizer(libgwas.standardizer.NoStandardization)
def testBoundariedMiddle(self):
BoundaryCheck.chrom = 4
DataParser.boundary = BoundaryCheck(bp=[30734, 33528])
impute_parser.encoding = impute_parser.Encoding.Recessive
PhenoCovar.sex_as_covariate = True
pc = PhenoCovar()
parser = impute_parser.Parser(self.fam_file,
[self.gen_file, self.gen_file2],
chroms=[3, 4])
parser.load_family_details(pc)
parser.load_genotypes()
idx = 0
dropped = 0
for snp in parser:
while self.positions[idx] < 30734 or self.positions[idx] > 33528:
idx += 1
dropped += 1
self.assertEqual(self.positions[idx], snp.pos)
for i in range(0, len(self.recessive_encoding[idx])):
self.assertAlmostEqual(self.recessive_encoding[idx][i],
snp.genotype_data[i],
places=3)
idx += 1
self.assertEqual(12, dropped)
def testBedAnalysisCov(self):
PhenoCovar.sex_as_covariate = True
DataParser.boundary = BoundaryCheck()
pheno = PhenoCovar()
ped_parser = bed_parser.Parser(self.nonmissing_fam,
self.nonmissing_bim,
self.nonmissing_bed)
ped_parser.load_fam(pheno)
ped_parser.load_bim(map3=False)
ped_parser.load_genotypes()
results = [x for x in mv_esteq.RunAnalysis(ped_parser, pheno)]
self.assertAlmostEqual(0.0034238, results[0].p_mvtest, places=6)
self.assertAlmostEqual(0.0143949, results[0].lmpv, places=6)
self.assertAlmostEqual(0.58495059, results[1].p_mvtest, places=6)
self.assertAlmostEqual(0.65786, results[1].lmpv, places=5)
self.assertAlmostEqual(0.45178985, results[2].p_mvtest, places=6)
self.assertAlmostEqual(0.83956, results[2].lmpv, places=5)
self.assertAlmostEqual(0.133661, results[3].p_mvtest, places=6)
self.assertAlmostEqual(0.82169, results[3].lmpv, places=5)
self.assertAlmostEqual(0.541391, results[4].p_mvtest, places=6)
self.assertAlmostEqual(0.83595, results[4].lmpv, places=5)
self.assertAlmostEqual(0.035665, results[5].p_mvtest, places=6)
self.assertAlmostEqual(0.94900, results[5].lmpv, places=5)
self.assertAlmostEqual(0.784660, results[6].p_mvtest, places=6)
self.assertAlmostEqual(0.59324, results[6].lmpv, places=5)
self.assertAlmostEqual(0.2137434, results[7].p_mvtest, places=6)
self.assertAlmostEqual(0.18069, results[7].lmpv, places=5)
self.assertAlmostEqual(0.8160148, results[8].p_mvtest, places=6)
self.assertAlmostEqual(0.79734, results[8].lmpv, places=5)
def setUp(self):
self.allele_1 = list("AAACCCGGGTCGTGTATACC")
self.allele_2 = list("CGTGTATACCAAACCCGGGT")
self.WriteTestFiles()
self.phenotypes = [
0.1, 0.4, 1.0, 0.5, 0.9, 1.0, 0.1, 0.4, 1.0, 0.5, 0.9, 1.0
]
self.sex = [1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1]
self.gen_ext = impute_parser.Parser.gen_ext
self.chrom = BoundaryCheck.chrom
self.boundary = DataParser.boundary
DataParser.boundary = BoundaryCheck()
self.min_maf = DataParser.min_maf
self.max_maf = DataParser.max_maf
self.snp_miss_tol = DataParser.snp_miss_tol
self.ind_miss_tol = DataParser.ind_miss_tol
DataParser.ind_exclusions = []
self.sex_as_covar = PhenoCovar.sex_as_covariate
self.has_sex = DataParser.has_sex
self.has_pheno = DataParser.has_pheno
self.has_parents = DataParser.has_parents
self.has_fid = DataParser.has_fid
self.has_liability = DataParser.has_liability
self.encoding = impute_parser.encoding
self.compression = DataParser.compressed_pedigree
DataParser.compressed_pedigree = True
self.parser_info_thresh = impute_parser.Parser.info_threshold
impute_parser.Parser.info_threshold = 0.0
def testPedBoundaryTPed(self):
pc = PhenoCovar()
ped_parser = TransposedPedigreeParser(self.tfam_filename,
self.tped_filename)
DataParser.boundary = BoundaryCheck()
BoundaryCheck.chrom = 2
ped_parser.load_tfam(pc)
ped_parser.load_genotypes()
pedigree = [x.split() for x in open(self.tped_filename).readlines()]
index = 4
loci = ped_parser.get_loci()
for snp in loci:
self.assertEqual(int(pedigree[index][0]), snp.chr)
self.assertEqual(int(pedigree[index][3]), snp.pos)
self.assertAlmostEqual(self.hetero_freq_tped[index],
snp.hetero_freq,
places=4)
index += 1
self.assertEqual(3, ped_parser.locus_count)
index = 4
for snp in ped_parser:
self.assertEqual(int(pedigree[index][0]), snp.chr)
self.assertEqual(int(pedigree[index][3]), snp.pos)
self.assertEqual(pedigree[index][1], snp.rsid)
self.assertEqual(self.genotypes[index], list(snp.genotype_data))
index += 1
self.assertEqual(7, index)
def setUp(self):
self.WriteTestFiles()
self.ped = get_lines(self.ped_filename)
self.phenotypes = [
0.1, 0.4, 1.0, 0.5, 0.9, 1.0, 0.1, 0.4, 1.0, 0.5, 0.9, 1.0
]
self.sex = [1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1]
self.chrom = BoundaryCheck.chrom
self.boundary = DataParser.boundary
DataParser.boundary = BoundaryCheck()
self.min_maf = DataParser.min_maf
self.max_maf = DataParser.max_maf
self.snp_miss_tol = DataParser.snp_miss_tol
self.ind_miss_tol = DataParser.ind_miss_tol
DataParser.ind_exclusions = []
DataParser.ind_inclusions = []
self.sex_as_covar = PhenoCovar.sex_as_covariate
self.has_sex = DataParser.has_sex
self.has_pheno = DataParser.has_pheno
self.has_parents = DataParser.has_parents
self.has_fid = DataParser.has_fid
self.has_liability = DataParser.has_liability
self.sex_as_covariate = PhenoCovar.sex_as_covariate
self.standardizer = libgwas.standardizer.get_standardizer()
libgwas.standardizer.set_standardizer(
libgwas.standardizer.NoStandardization)
def setUp(self):
self.WriteTestFiles()
self.phenotypes = [
0.1, 0.4, 1.0, 0.5, 0.9, 1.0, 0.1, 0.4, 1.0, 0.5, 0.9, 1.0
]
self.sex = [1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1]
self.chrom = BoundaryCheck.chrom
self.boundary = DataParser.boundary
self.min_maf = DataParser.min_maf
self.max_maf = DataParser.max_maf
self.snp_miss_tol = DataParser.snp_miss_tol
self.ind_miss_tol = DataParser.ind_miss_tol
self.sex_as_covar = PhenoCovar.sex_as_covariate
self.has_sex = DataParser.has_sex
self.has_pheno = DataParser.has_pheno
self.has_parents = DataParser.has_parents
self.has_fid = DataParser.has_fid
self.has_liability = DataParser.has_liability
# the faked pheno/covariate non-missing
self.non_missing = numpy.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1]) == 1
DataParser.boundary = BoundaryCheck()
def testBoundary(self):
pc = PhenoCovar()
DataParser.boundary = BoundaryCheck()
BoundaryCheck.chrom = 2
parser = Parser(self.nonmissing, data_field='GT')
parser.init_subjects(pc)
parser.load_genotypes()
index = 4
for snp in parser:
snp_filter = numpy.ones(snp.missing_genotypes.shape[0]) == 1
try:
genodata = snp.get_genotype_data(snp_filter)
self.assertEqual(int(self.nonmissing_mapdata[index][0]),
snp.chr)
self.assertEqual(int(self.nonmissing_mapdata[index][1]),
snp.pos)
self.assertEqual(self.nonmissing_mapdata[index][2], snp.rsid)
self.assertEqual(self.genotypes[index],
list(genodata.genotypes))
except TooMuchMissing as e:
pass
except InvalidFrequency as e:
pass
index += 1
self.assertEqual(7, index)
def testBedAnalysis(self):
# We'll start with the correct phenotype with the genotypes, so we'll use
# a boundary to restrict us to only use the first SNP
BoundaryCheck.chrom = 1
DataParser.boundary = BoundaryCheck()
pheno = PhenoCovar()
ped_parser = bed_parser.Parser(self.nonmissing_fam,
self.nonmissing_bim,
self.nonmissing_bed)
ped_parser.load_fam(pheno)
ped_parser.load_bim(map3=False)
ped_parser.load_genotypes()
results = [x for x in mv_esteq.RunAnalysis(ped_parser, pheno)]
self.assertAlmostEqual(0.00347562, results[0].p_mvtest, places=6)
self.assertAlmostEqual(0.00085539, results[0].lmpv, places=6)
self.assertAlmostEqual(0.5777812, results[1].p_mvtest, places=6)
self.assertAlmostEqual(0.42212155, results[1].lmpv, places=6)
self.assertAlmostEqual(0.44661276, results[2].p_mvtest, places=6)
self.assertAlmostEqual(0.61386344, results[2].lmpv, places=6)
self.assertAlmostEqual(0.13555597, results[3].p_mvtest, places=6)
self.assertAlmostEqual(0.59682217, results[3].lmpv, places=6)
self.assertAlmostEqual(0.54029842, results[4].p_mvtest, places=6)
self.assertAlmostEqual(0.60475964, results[4].lmpv, places=6)
self.assertAlmostEqual(0.03547514, results[5].p_mvtest, places=6)
self.assertAlmostEqual(0.86663730, results[5].lmpv, places=6)
self.assertAlmostEqual(0.79249216, results[6].p_mvtest, places=6)
self.assertAlmostEqual(0.67678089, results[6].lmpv, places=6)
self.assertAlmostEqual(0.20973300, results[7].p_mvtest, places=6)
self.assertAlmostEqual(0.14431260, results[7].lmpv, places=6)
self.assertAlmostEqual(0.81471528, results[8].p_mvtest, places=6)
self.assertAlmostEqual(0.56378497, results[8].lmpv, places=6)
def testTpedBounded(self):
BoundaryCheck.chrom = 1
DataParser.boundary = BoundaryCheck(bp=[2000,3000])
pheno = PhenoCovar()
dataset = TransposedPedigreeParser(self.tfam_filename, self.tped_filename)
dataset.load_tfam(pheno)
dataset.load_genotypes()
results = [x for x in mv_esteq.RunAnalysis(dataset, pheno)]
self.assertEqual(1, results[0].chr)
self.assertEqual(2000, results[0].pos)
self.assertAlmostEqual(0.57778118, results[0].p_mvtest, places=6)
self.assertAlmostEqual(0.02798537, results[0].betas[1], places=6)
self.assertAlmostEqual(0.033790691857, results[0].beta_stderr[1], places=6)
self.assertAlmostEqual(0.40755865, results[0].beta_pvalues[1], places=6)
self.assertAlmostEqual(0.03275892, results[0].betas[3], places=6)
self.assertAlmostEqual(0.0475661, results[0].beta_stderr[3], places=6)
self.assertAlmostEqual(0.49101013, results[0].beta_pvalues[3], places=6)
self.assertAlmostEqual(0.44661276, results[1].p_mvtest, places=6)
self.assertAlmostEqual(0.01663975, results[1].betas[1], places=6)
self.assertAlmostEqual(0.03443300, results[1].beta_stderr[1], places=6)
self.assertAlmostEqual(0.62891811, results[1].beta_pvalues[1], places=6)
self.assertAlmostEqual(0.05712017, results[1].betas[3], places=6)
self.assertAlmostEqual(0.04783608, results[1].beta_stderr[3], places=6)
self.assertAlmostEqual(0.232446188, results[1].beta_pvalues[3], places=6)
def testBoundaryX(self):
BoundaryCheck.set_chrom('X')
b = BoundaryCheck()
self.assertEqual(23, BoundaryCheck.chrom)
self.assertEqual('X', BoundaryCheck.chrom_name)
self.assertTrue(b.TestBoundary('x', 100, "rs100"))
self.assertTrue(b.TestBoundary('X', 1000, "rs1000"))
self.assertTrue(b.TestBoundary(23, 1000, "rs1000"))
self.assertFalse(b.TestBoundary('Y', 100, "rs100"))
def testBoundaryInitKB(self):
BoundaryCheck.chrom = 5
b = BoundaryCheck(kb=[20, 50])
self.assertFalse(b.NoExclusions())
self.assertEqual(True, b.valid)
self.assertEqual(False, b.TestBoundary(5, 15000, ""))
self.assertEqual(True, b.TestBoundary(5, 20000, ""))
self.assertEqual(True, b.TestBoundary(5, 30000, ""))
self.assertEqual(True, b.TestBoundary(5, 50000, ""))
self.assertEqual(False, b.TestBoundary(5, 50001, ""))
self.assertEqual(False, b.TestBoundary(1, 25000, ""))
self.assertEqual(False, b.TestBoundary(10, 20000, ""))
def testBoundaryExceedPos(self):
BoundaryCheck.chrom = 10
b = BoundaryCheck(mb=[1,3])
self.assertTrue(b.valid)
self.assertFalse(b.NoExclusions())
self.assertFalse(b.TestBoundary(10, 100, ""))
self.assertFalse(b.beyond_upper_bound)
self.assertTrue(b.TestBoundary(10, 1000000, ""))
self.assertFalse(b.beyond_upper_bound)
self.assertTrue(b.TestBoundary(10, 1200000, ""))
self.assertFalse(b.beyond_upper_bound)
self.assertTrue(b.TestBoundary(10, 3000000, ""))
self.assertFalse(b.beyond_upper_bound)
self.assertFalse(b.TestBoundary(10, 3000001, ""))
self.assertTrue(b.beyond_upper_bound)
self.assertFalse(b.TestBoundary(10, 999999, ""))
self.assertFalse(b.beyond_upper_bound)
def testMapFileWithRegionAndSnpExclusion(self):
BoundaryCheck.chrom = 2
DataParser.boundary = BoundaryCheck(bp=[0, 10000])
ped_parser = PedigreeParser(self.map_filename, self.ped_filename)
ped_parser.load_mapfile()
self.assertEqual(2, len(ped_parser.markers))
self.assertEqual(7, len(ped_parser.snp_mask[:, 0]))
self.assertEqual(2, ped_parser.locus_count)
# Masks are filters, so we should have 7 entries, but 4 will be 1
self.assertEqual(5, numpy.sum(ped_parser.snp_mask[:, 0]))
self.assertEqual(0, ped_parser.snp_mask[4, 1])
self.assertEqual(0, ped_parser.snp_mask[5, 0])
def setUp(self):
self.missing = "tests/bedfiles/ped_missing"
self.missing_bed = resource_filename("libgwas",
"%s.bed" % (self.missing))
self.missing_bim = resource_filename("libgwas",
"%s.bim" % (self.missing))
self.missing_fam = resource_filename("libgwas",
"%s.fam" % (self.missing))
self.genotypes = [[0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0],
[1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1],
[0, 2, 1, 1, 0, 0, 0, 2, 1, 1, 0, 0],
[0, 1, 2, 1, 1, 0, 0, 1, 2, 1, 1, 0],
[1, 2, 0, 1, 0, 0, 1, 2, 0, 1, 0, 0],
[1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0]]
self.nonmissing = "tests/bedfiles/ped_nomiss"
self.nonmissing_bed = resource_filename("libgwas",
"%s.bed" % (self.nonmissing))
self.nonmissing_bim = resource_filename("libgwas",
"%s.bim" % (self.nonmissing))
self.nonmissing_fam = resource_filename("libgwas",
"%s.fam" % (self.nonmissing))
self.genotypes_w_missing = [[0, 1],
[1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1],
[0, 1, 1, 0, 0, 0, 2, 1, 1, 0, 0],
[0, 2, 1, 1, 0, 0, 1, 2, 1, 1, 0],
[1, 0, 1, 0, 0, 1, 2, 0, 1, 0, 0],
[1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0]]
self.nonmissing_mapdata = libgwas.get_lines(self.nonmissing_bim,
split=True)
self.missing_mapdata = libgwas.get_lines(self.missing_bim, split=True)
self.phenotypes = [
0.1, 0.4, 1.0, 0.5, 0.9, 1.0, 0.1, 0.4, 1.0, 0.5, 0.9, 1.0
]
self.sex = [1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1]
self.chrom = BoundaryCheck.chrom
self.boundary = DataParser.boundary
self.min_maf = DataParser.min_maf
self.max_maf = DataParser.max_maf
self.snp_miss_tol = DataParser.snp_miss_tol
self.ind_miss_tol = DataParser.ind_miss_tol
self.sex_as_covar = PhenoCovar.sex_as_covariate
self.has_sex = DataParser.has_sex
self.has_pheno = DataParser.has_pheno
self.has_parents = DataParser.has_parents
self.has_fid = DataParser.has_fid
self.has_liability = DataParser.has_liability
DataParser.boundary = BoundaryCheck()
def testBoundaryInitBP(self):
BoundaryCheck.chrom = 1
b = BoundaryCheck(bp=[10000, 500000])
self.assertFalse(b.NoExclusions())
self.assertTrue(b.valid)
self.assertEqual(False, b.TestBoundary(1, 500, ""))
self.assertEqual(True, b.TestBoundary(1, 10000, ""))
self.assertEqual(True, b.TestBoundary(1, 500000, ""))
self.assertEqual(True, b.TestBoundary(1, 250000, ""))
self.assertEqual(False, b.TestBoundary(2, 250000, ""))
self.assertEqual(False, b.TestBoundary(10, 10000, ""))
def testBoundaryInitMB(self):
BoundaryCheck.chrom = 10
b = BoundaryCheck(mb=[1,3])
self.assertTrue(b.valid)
self.assertFalse(b.NoExclusions())
self.assertTrue(b.TestBoundary(10, 1000000, ""))
self.assertTrue(b.TestBoundary(10, 1200000, ""))
self.assertTrue(b.TestBoundary(10, 3000000, ""))
self.assertFalse(b.TestBoundary(10, 3000001, ""))
self.assertFalse(b.TestBoundary(10, 999999, ""))
self.assertFalse(b.TestBoundary(1, 1000500, ""))
def testDefaultBoundaryInitialization(self):
# By default, it will identify as invalid, since it didn't find any boundaries
# This is just for simplifying command line parsing
BoundaryCheck.chrom = -1
b = BoundaryCheck()
self.assertEqual(True, b.valid)
# At this point, this should any valid chromosome/position combination
self.assertTrue(b.TestBoundary(1, 100, ""))
self.assertTrue(b.TestBoundary(10, 1000000, ""))
self.assertTrue(b.TestBoundary(25, 10000, ""))
self.assertTrue(b.TestBoundary('Y', 1400, ""))
self.assertFalse(b.TestBoundary('FF', 35, ""))
self.assertFalse(b.TestBoundary(28, 10000, ""))
# We should test that our short circuit functionality works
self.assertTrue(b.NoExclusions())
def testBoundedMiddle(self):
mach_parser.Parser.chrpos_encoding = True
BoundaryCheck.chrom = 2
DataParser.boundary = BoundaryCheck(bp=[1020, 1137])
PhenoCovar.sex_as_covariate = True
pc = PhenoCovar()
parser = mach_parser.Parser([self.gen_file, self.gen_file2])
parser.load_family_details(pc)
parser.load_genotypes()
idx = 8
for snp in parser:
self.assertEqual(self.positions[idx], snp.pos)
for i in range(0, len(self.dosage_encoding[idx])):
self.assertAlmostEqual(self.dosage_encoding[idx][i], snp.genotype_data[i], places=3)
idx += 1
self.assertEqual(13, idx)
def testPedBoundary(self):
pc = PhenoCovar()
ped_parser = PedigreeParser(self.map_filename, self.ped_filename)
DataParser.boundary = BoundaryCheck()
BoundaryCheck.chrom = 2
ped_parser.load_mapfile()
ped_parser.load_genotypes(pc)
pedigree = get_lines(self.map_filename, split=True)
index = 4
for snp in ped_parser:
self.assertEqual(int(pedigree[index][0]), snp.chr)
self.assertEqual(int(pedigree[index][3]), snp.pos)
self.assertEqual(pedigree[index][1], snp.rsid)
self.assertEqual(self.genotypes[index], list(snp.genotype_data))
index += 1
self.assertEqual(7, index)
def setUp(self):
self.missing = "bedfiles/analysis"
self.missing_bed = resource_filename("tests",
"%s.bed" % (self.missing))
self.missing_bim = resource_filename("tests",
"%s.bim" % (self.missing))
self.missing_fam = resource_filename("tests",
"%s.fam" % (self.missing))
self.genotypes = [[2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 2],
[1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1],
[2, 0, 1, 1, 2, 2, 2, 0, 1, 1, 2, 2],
[2, 1, 0, 1, 1, 2, 2, 1, 0, 1, 1, 2],
[1, 0, 2, 1, 2, 2, 1, 0, 2, 1, 2, 2],
[1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2],
[2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 2, 2]]
self.nonmissing = "bedfiles/analysis"
self.nonmissing_bed = resource_filename("tests",
"%s.bed" % (self.nonmissing))
self.nonmissing_bim = resource_filename("tests",
"%s.bim" % (self.nonmissing))
self.nonmissing_fam = resource_filename("tests",
"%s.fam" % (self.nonmissing))
self.genotypes_w_missing = [[
2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1
], [1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1],
[2, -1, 1, 1, 2, 2, 2, 0, 1, 1, 2, 2],
[2, -1, 0, 1, 1, 2, 2, 1, 0, 1, 1, 2],
[1, -1, 2, 1, 2, 2, 1, 0, 2, 1, 2, 2],
[1, -1, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2],
[2, -1, 1, 2, 2, 2, 2, 1, 1, 2, 2, 2]]
self.chrom = BoundaryCheck.chrom
self.boundary = DataParser.boundary
self.min_maf = DataParser.min_maf
self.max_maf = DataParser.max_maf
self.snp_miss_tol = DataParser.snp_miss_tol
self.ind_miss_tol = DataParser.ind_miss_tol
self.sex_as_covar = PhenoCovar.sex_as_covariate
self.standardizer = libgwas.standardizer.get_standardizer()
libgwas.standardizer.set_standardizer(
libgwas.standardizer.NoStandardization)
DataParser.boundary = BoundaryCheck()
def testBedBounded(self):
BoundaryCheck.chrom = 1
DataParser.boundary = BoundaryCheck(bp=[2000, 3000])
pheno = PhenoCovar()
ped_parser = bed_parser.Parser(self.nonmissing_fam,
self.nonmissing_bim,
self.nonmissing_bed)
ped_parser.load_fam(pheno)
ped_parser.load_bim(map3=False)
ped_parser.load_genotypes()
results = [x for x in mv_esteq.RunAnalysis(ped_parser, pheno)]
self.assertEqual(1, results[0].chr)
self.assertEqual(2000, results[0].pos)
self.assertAlmostEqual(0.5777811, results[0].p_mvtest, places=6)
self.assertAlmostEqual(0.4221215, results[0].lmpv, places=6)
self.assertAlmostEqual(0.4466128, results[1].p_mvtest, places=6)
self.assertAlmostEqual(0.6138634, results[1].lmpv, places=6)
def testBoundariedUpper(self):
BoundaryCheck.chrom = 3
DataParser.boundary = BoundaryCheck(bp=[21000, 50000])
impute_parser.encoding = impute_parser.Encoding.Recessive
PhenoCovar.sex_as_covariate = True
pc = PhenoCovar()
parser = impute_parser.Parser(self.fam_file,
[self.gen_file, self.gen_file2],
chroms=[3, 4])
parser.load_family_details(pc)
parser.load_genotypes()
idx = 6
for snp in parser:
self.assertEqual(self.positions[idx], snp.pos)
for i in range(0, len(self.recessive_encoding[idx])):
self.assertAlmostEqual(self.recessive_encoding[idx][i],
snp.genotype_data[i],
places=3)
idx += 1
def testPedBoundaryTPed(self):
pc = PhenoCovar()
ped_parser = TransposedPedigreeParser(self.tfam_filename,
self.tped_filename)
DataParser.boundary = BoundaryCheck()
BoundaryCheck.chrom = 2
ped_parser.load_tfam(pc)
ped_parser.load_genotypes()
pedigree = get_lines(self.tped_filename, split=True)
index = 4
loci = ped_parser.get_loci()
for snp in loci:
self.assertEqual(int(pedigree[index][0]), snp.chr)
self.assertEqual(int(pedigree[index][3]), snp.pos)
index += 1
self.assertEqual(3, ped_parser.locus_count)
index = 4
for snp in ped_parser:
snp_filter = numpy.ones(snp.missing_genotypes.shape[0]) == 1
try:
genodata = snp.get_genotype_data(snp_filter)
self.assertEqual(int(pedigree[index][0]), snp.chr)
self.assertEqual(int(pedigree[index][3]), snp.pos)
self.assertEqual(pedigree[index][1], snp.rsid)
self.assertAlmostEqual(self.hetero_freq_tped[index],
genodata.hetero_freq,
places=4)
self.assertEqual(self.genotypes[index],
list(genodata.genotypes))
except TooMuchMissing as e:
pass
except InvalidFrequency as e:
pass
index += 1
self.assertEqual(7, index)
def testTPedAnalysisCov(self):
PhenoCovar.sex_as_covariate = True
DataParser.boundary = BoundaryCheck()
pheno = PhenoCovar()
dataset = TransposedPedigreeParser(self.tfam_filename, self.tped_filename)
dataset.load_tfam(pheno)
dataset.load_genotypes()
#pheno.standardize_variables()
results = [x for x in mv_esteq.RunAnalysis(dataset, pheno)]
self.assertAlmostEqual(0.00342380, results[0].p_mvtest, places=6)
self.assertAlmostEqual(0.11362883, results[0].betas[1], places=6)
self.assertAlmostEqual(0.0337610, results[0].beta_stderr[1], places=6)
self.assertAlmostEqual(0.00076356, results[0].beta_pvalues[1], places=6)
self.assertAlmostEqual(0.01911090, results[0].betas[3], places=6)
self.assertAlmostEqual(0.10143178, results[0].beta_stderr[3], places=6)
self.assertAlmostEqual(0.8505542, results[0].beta_pvalues[3], places=6)
self.assertAlmostEqual(0.584950593047, results[1].p_mvtest, places=6)
self.assertAlmostEqual(0.0276543736525, results[1].betas[1], places=6)
self.assertAlmostEqual(0.03383588, results[1].beta_stderr[1], places=6)
self.assertAlmostEqual(0.413751829881, results[1].beta_pvalues[1], places=6)
def testPedBoundaryBed(self):
pc = PhenoCovar()
DataParser.boundary = BoundaryCheck()
BoundaryCheck.chrom = 2
ped_parser = bed_parser.Parser(self.nonmissing_fam,
self.nonmissing_bim,
self.nonmissing_bed)
ped_parser.load_fam(pc)
ped_parser.load_bim(map3=False)
ped_parser.load_genotypes()
pedigree = self.nonmissing_mapdata
index = 4
valid_loci = 0
for snp in ped_parser:
for y in pc:
(pheno, covars,
nonmissing) = y.get_variables(snp.missing_genotypes)
try:
genodata = snp.get_genotype_data(nonmissing)
self.assertEqual(int(pedigree[index][0]), snp.chr)
self.assertEqual(int(pedigree[index][3]), snp.pos)
self.assertEqual(pedigree[index][1], snp.rsid)
self.assertEqual(self.genotypes[index],
list(genodata.genotypes))
valid_loci += 1
except TooMuchMissing as e:
pass
except InvalidFrequency as e:
pass
index += 1
self.assertEqual(3, valid_loci)
self.assertEqual(7, index)
def testBoundaryInitBPWithExclusions(self):
BoundaryCheck.chrom = 1
b = BoundaryCheck(bp=[10000, 500000])
b.LoadExclusions(["rs12345", "rs234567", "rs345678"])
self.assertFalse(b.NoExclusions())
self.assertTrue(b.valid)
self.assertFalse(b.TestBoundary(1, 500, ""))
self.assertTrue(b.TestBoundary(1, 10000, ""))
self.assertFalse(b.TestBoundary(1, 10010, "rs12345"))
self.assertTrue(b.TestBoundary(1, 24000, "rs9876"))
self.assertFalse(b.TestBoundary(1, 25000, "rs234567"))
self.assertTrue(b.TestBoundary(1, 250000, ""))
self.assertTrue(b.TestBoundary(1, 500000, ""))
self.assertFalse(b.TestBoundary(2, 250000, ""))
self.assertFalse(b.TestBoundary(10, 10000, ""))