def est_logdet_pair_aa(self):
"""logdet shouldn't fail to produce distances for aa seqs"""
aln = LoadSeqs('data/brca1_5.paml', moltype=DNA)
aln = aln.getTranslation()
logdet_calc = LogDetPair(moltype=PROTEIN, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
def est_logdet_pair_dna(self):
"""logdet should produce distances that match MEGA"""
aln = LoadSeqs('data/brca1_5.paml', moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True)
dists = logdet_calc.getPairwiseDistances()
all_expected = {('Human', 'NineBande'): 0.075336929999999996,
('NineBande', 'DogFaced'): 0.0898575452,
('DogFaced', 'Human'): 0.1061747919,
('HowlerMon', 'DogFaced'): 0.0934480008,
('Mouse', 'HowlerMon'): 0.26422862920000001,
('NineBande', 'Human'): 0.075336929999999996,
('HowlerMon', 'NineBande'): 0.062202897899999998,
('DogFaced', 'NineBande'): 0.0898575452,
('DogFaced', 'HowlerMon'): 0.0934480008,
('Human', 'DogFaced'): 0.1061747919,
('Mouse', 'Human'): 0.26539976700000001,
('NineBande', 'HowlerMon'): 0.062202897899999998,
('HowlerMon', 'Human'): 0.036571181899999999,
('DogFaced', 'Mouse'): 0.2652555144,
('HowlerMon', 'Mouse'): 0.26422862920000001,
('Mouse', 'DogFaced'): 0.2652555144,
('NineBande', 'Mouse'): 0.22754789210000001,
('Mouse', 'NineBande'): 0.22754789210000001,
('Human', 'Mouse'): 0.26539976700000001,
('Human', 'HowlerMon'): 0.036571181899999999}
for pair in dists:
got = dists[pair]
expected = all_expected[pair]
self.assertFloatEqual(got, expected)
def test_logdet_pair_aa(self):
"""logdet shouldn't fail to produce distances for aa seqs"""
aln = LoadSeqs('data/brca1_5.paml', moltype=DNA)
aln = aln.getTranslation()
logdet_calc = LogDetPair(moltype=PROTEIN, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
def test_logdet_variance(self):
"""calculate logdet variance consistent with hand calculation"""
data = [
('seq1',
"GGGGGGGGGGGCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGCGGTTTTTTTTTTTTTTTTTT"
),
('seq2',
"TAAAAAAAAAAGGGGGGGGGGGGGGGGGGTTTTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCC"
)
]
aln = LoadSeqs(data=data, moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
self.assertEqual(logdet_calc.Variances[1, 1], None)
index = dict(zip('ACGT', range(4)))
J = numpy.zeros((4, 4))
for p in zip(data[0][1], data[1][1]):
J[index[p[0]], index[p[1]]] += 1
for i in range(4):
if J[i, i] == 0:
J[i, i] += 0.5
J /= J.sum()
M = numpy.linalg.inv(J)
var = 0.
for i in range(4):
for j in range(4):
var += M[j, i]**2 * J[i, j] - 1
var /= 16 * len(data[0][1])
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertFloatEqual(logdet_calc.Variances[1, 1], var, eps=1e-3)
def test_logdet_pair_dna(self):
"""logdet should produce distances that match MEGA"""
aln = LoadSeqs('data/brca1_5.paml', moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
all_expected = {
('Human', 'NineBande'): 0.075336929999999996,
('NineBande', 'DogFaced'): 0.0898575452,
('DogFaced', 'Human'): 0.1061747919,
('HowlerMon', 'DogFaced'): 0.0934480008,
('Mouse', 'HowlerMon'): 0.26422862920000001,
('NineBande', 'Human'): 0.075336929999999996,
('HowlerMon', 'NineBande'): 0.062202897899999998,
('DogFaced', 'NineBande'): 0.0898575452,
('DogFaced', 'HowlerMon'): 0.0934480008,
('Human', 'DogFaced'): 0.1061747919,
('Mouse', 'Human'): 0.26539976700000001,
('NineBande', 'HowlerMon'): 0.062202897899999998,
('HowlerMon', 'Human'): 0.036571181899999999,
('DogFaced', 'Mouse'): 0.2652555144,
('HowlerMon', 'Mouse'): 0.26422862920000001,
('Mouse', 'DogFaced'): 0.2652555144,
('NineBande', 'Mouse'): 0.22754789210000001,
('Mouse', 'NineBande'): 0.22754789210000001,
('Human', 'Mouse'): 0.26539976700000001,
('Human', 'HowlerMon'): 0.036571181899999999
}
for pair in dists:
got = dists[pair]
expected = all_expected[pair]
self.assertFloatEqual(got, expected)
def test_logdet_variance(self):
"""calculate logdet variance consistent with hand calculation"""
data = [('seq1', "GGGGGGGGGGGCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGCGGTTTTTTTTTTTTTTTTTT"),
('seq2', "TAAAAAAAAAAGGGGGGGGGGGGGGGGGGTTTTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCC")]
aln = LoadSeqs(data=data, moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
self.assertEqual(logdet_calc.Variances[1,1], None)
index = dict(zip('ACGT', range(4)))
J = numpy.zeros((4, 4))
for p in zip(data[0][1], data[1][1]):
J[index[p[0]], index[p[1]]] += 1
for i in range(4):
if J[i, i] == 0:
J[i, i] += 0.5
J /= J.sum()
M = numpy.linalg.inv(J)
var = 0.
for i in range(4):
for j in range(4):
var += M[j, i]**2 * J[i, j] - 1
var /= 16 * len(data[0][1])
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertFloatEqual(logdet_calc.Variances[1,1], var, eps=1e-3)
def est_logdet_tk_adjustment(self):
"""logdet using tamura kumar differs from classic"""
aln = LoadSeqs('data/brca1_5.paml', moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
tk = logdet_calc.getPairwiseDistances()
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
not_tk = logdet_calc.getPairwiseDistances()
self.assertNotEqual(tk, not_tk)
def test_logdet_tk_adjustment(self):
"""logdet using tamura kumar differs from classic"""
aln = LoadSeqs('data/brca1_5.paml', moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
tk = logdet_calc.getPairwiseDistances()
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
not_tk = logdet_calc.getPairwiseDistances()
self.assertNotEqual(tk, not_tk)
def test_logdet_variance(self):
"""calculate logdet variance consistent with hand calculation"""
data = [('seq1', "GGGGGGGGGGGCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGCGGTTTTTTTTTTTTTTTTTT"),
('seq2', "TAAAAAAAAAAGGGGGGGGGGGGGGGGGGTTTTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCC")]
aln = LoadSeqs(data=data, moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
self.assertFloatEqual(logdet_calc.Variances[1,1], 0.5267, eps=1e-3)
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertFloatEqual(logdet_calc.Variances[1,1], 0.4797, eps=1e-3)
def est_logdet_for_determinant_lte_zero(self):
"""returns distance of None if the determinant is <= 0"""
data = dict(seq1="AGGGGGGGGGGCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGCGGTTTTTTTTTTTTTTTTTT",
seq2="TAAAAAAAAAAGGGGGGGGGGGGGGGGGGTTTTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCC")
aln = LoadSeqs(data=data, moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is None)
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is None)
def test_logdet_missing_states(self):
"""should calculate logdet measurement with missing states"""
data = [('seq1', "GGGGGGGGGGGCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGCGGTTTTTTTTTTTTTTTTTT"),
('seq2', "TAAAAAAAAAAGGGGGGGGGGGGGGGGGGTTTTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCC")]
aln = LoadSeqs(data=data, moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is not None)
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is not None)
def test_paralinear_pair_dna(self):
"""calculate paralinear distance consistent with logdet distance"""
data = [('seq1', 'TAATTCATTGGGACGTCGAATCCGGCAGTCCTGCCGCAAAAGCTTCCGGAATCGAATTTTGGCA'),
('seq2', 'AAAAAAAAAAAAAAAACCCCCCCCCCCCCCCCTTTTTTTTTTTTTTTTGGGGGGGGGGGGGGGG')]
aln = LoadSeqs(data=data, moltype=DNA)
paralinear_calc = ParalinearPair(moltype=DNA, alignment=aln)
paralinear_calc.run(show_progress=False)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(show_progress=False)
self.assertFloatEqual(logdet_calc.Dists[1,1],
paralinear_calc.Dists[1,1], eps=1e-3)
self.assertFloatEqual(paralinear_calc.Variances[1,1],
logdet_calc.Variances[1,1], eps=1e-3)
def test_logdet_for_determinant_lte_zero(self):
"""returns distance of None if the determinant is <= 0"""
data = dict(
seq1=
"AGGGGGGGGGGCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGCGGTTTTTTTTTTTTTTTTTT",
seq2=
"TAAAAAAAAAAGGGGGGGGGGGGGGGGGGTTTTTTTTTTTTTTTTTTCCCCCCCCCCCCCCCCC")
aln = LoadSeqs(data=data, moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is None)
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is None)
def test_logdet_missing_states(self):
"""should calculate logdet measurement with missing states"""
data = [
('seq1',
"GGGGGGGGGGGCCCCCCCCCCCCCCCCCGGGGGGGGGGGGGGGCGGTTTTTTTTTTTTTTTTTT"
),
('seq2',
"TAAAAAAAAAAGGGGGGGGGGGGGGGGGGTTTTTNTTTTTTTTTTTTCCCCCCCCCCCCCCCCC"
)
]
aln = LoadSeqs(data=data, moltype=DNA)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(use_tk_adjustment=True, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is not None)
logdet_calc.run(use_tk_adjustment=False, show_progress=False)
dists = logdet_calc.getPairwiseDistances()
self.assertTrue(dists.values()[0] is not None)
def test_paralinear_pair_dna(self):
"""calculate paralinear distance consistent with logdet distance"""
data = [
('seq1',
'TAATTCATTGGGACGTCGAATCCGGCAGTCCTGCCGCAAAAGCTTCCGGAATCGAATTTTGGCA'
),
('seq2',
'AAAAAAAAAAAAAAAACCCCCCCCCCCCCCCCTTTTTTTTTTTTTTTTGGGGGGGGGGGGGGGG'
)
]
aln = LoadSeqs(data=data, moltype=DNA)
paralinear_calc = ParalinearPair(moltype=DNA, alignment=aln)
paralinear_calc.run(show_progress=False)
logdet_calc = LogDetPair(moltype=DNA, alignment=aln)
logdet_calc.run(show_progress=False)
self.assertFloatEqual(logdet_calc.Dists[1, 1],
paralinear_calc.Dists[1, 1],
eps=1e-3)
self.assertFloatEqual(paralinear_calc.Variances[1, 1],
logdet_calc.Variances[1, 1],
eps=1e-3)