def test_run(self):
"""sliding, no matching"""
a = gelscore.Sequence('GYPMGGYPMGGYPMGGYPMGGYPMG')
b = gelscore.Sequence('AAAAA')
fac = slide.SequenceCompositionComparatorFactory()
scb = fac.make(b, 'sequence')
sw = slide.SequenceWindow(a, 5)
res = sw.slide(scb)
self.assertAlmostEqual(sum(res.scores), 0.0)
def test_run(self):
gs1 = gelscore.Sequence('AAAA')
gs2 = gelscore.Sequence('DDDD')
comp1 = gelscore.SequenceComposition(gs1)
comp2 = gelscore.SequenceComposition(gs2)
comp3 = gelscore.SequenceComposition(gs1, weights=[1,0,0,0])
self.assertAlmostEqual(comp1.dot(comp2),0.0)
self.assertAlmostEqual(comp1.dot(comp3),1.0)
self.assertAlmostEqual(np.linalg.norm(comp1.vector), 1)
def test_run(self):
"""straight comparison"""
a = gelscore.Sequence('AAAAA')
b = gelscore.Sequence('AAAAA')
c = gelscore.Sequence('LAAAA')
fac = slide.SequenceCompositionComparatorFactory()
ac = fac.make(a, 'sequence')
bc = fac.make(b, 'sequence')
cc = fac.make(c, 'sequence')
self.assertTrue(ac.compare(bc) > ac.compare(cc))
def test_run(self):
"""composition comparison"""
a = gelscore.Sequence('GYPMGGYPMGGYPMGGYPMGGYPMG')
b = gelscore.Sequence('GYPMG')
fac = slide.SequenceCompositionComparatorFactory()
sca = fac.make(a, 'sequence')
scb = fac.make(b, 'sequence')
self.assertAlmostEqual(sca.compare(sca), 1.0) # Equal to self
self.assertAlmostEqual(sca.compare(scb), 1.0)
self.assertAlmostEqual(scb.compare(sca), 1.0)
def test_run(self):
"""sliding, no matching"""
a = gelscore.Sequence(
'QLAQQIQARNQMRYQQATAAAAAAAAGMPGQFMPPMFYGVMPPRGVPFNGPNPQQMNPMGGMPKNGMPPQFRNGPVYGVPPQGGFPRNANDNNQFYQ'
)
b = gelscore.Sequence('MPQNGRA')
fac = slide.SequenceCompositionComparatorFactory()
scb = fac.make(b, 'sequence')
sw = slide.SequenceWindow(a, len(b))
ress = sw.slide(scb)
for (xi, res) in enumerate(ress.results()):
self.assertTrue(a[res.position - 1] == a[xi])
self.assertTrue(res.score >= 0.0)
def test_run(self):
gs = gelscore.Sequence('ACDEFGHIKLMNPQRSTVWY')
gs1 = gelscore.ContiguousRegion(gs, 0, 5)
gs2 = gelscore.ContiguousRegion(gs, 15, 20)
[left, right] = gs1.difference(gs2)
self.assertTrue(str(left) == str(gs1))
self.assertTrue(str(right) == str(gs2))
def test_run(self):
gs = gelscore.Sequence('RGGGNGRGGRGRGGPMGRGGYGGGGSGGGGRGGFPSGGGGGGGQQRAGDWKCPNPTCENMNFSWRNECNQCKAPKPDGPGGGPGGSHMGGN')
dist = gelscore.SimilarityWeight(sim_add=1.0)
rf = gelscore.NormalizedCutRegionFinder(dist, min_region_size=6, score_threshold=0.1)
res = rf.find(gs)
#printRegions(res)
self.assertTrue(len(res) == 3)
def test_run(self):
gs = gelscore.Sequence('MASNDYTQQATQSYGAYPTQPGQGYSQQSSQPYGQQSYSGYSQSTDTSGYGQSSYSSYGQSQNTGYGTQSTPQGYGSTGGYGSSQSSQSSYGQQSSYPGYGQQPAPSSTSGSYGSSSQSSSYGQPQSGSYSQQPSYGGQQQSYGQQQSYNPPQGYGQQNQYNSSSGGGGGGGGGGNYGQDQSSMSSGGGSGGGYGNQDQSGGGGSGGYGQQDRGGRGRGGSGGGGGGGGGGYNRSSGGYEPRGRGGGRGGRGGMGGSDRGGFNKFGGPRDQGSRHDSEQDNSDNNTIFVQGLGENVTIESVADYFKQIGIIKTNKKTGQPMINLYTDRETGKLKGEATVSFDDPPSAKAAIDWFDGKEFSGNPIKVSFATRRADFNRGGGNGRGGRGRGGPMGRGGYGGGGSGGGGRGGFPSGGGGGGGQQRAGDWKCPNPTCENMNFSWRNECNQCKAPKPDGPGGGPGGSHMGGNYGDDRRGGRGGYDRGGYRGRGGDRGGFRGGRGGGDRGGFGPGKMDSRGEHRQDRRERPY')
#gs = gelscore.Sequence('AAAAAAAAAAAAAYYGSGSGSGSGSAAAAAAAAA')
dist = gelscore.SimilarityWeight(sim_add=1.0)
rf = gelscore.NormalizedCutRegionFinder(dist, min_region_size=10, score_threshold=0.025)
res = rf.find(gs)
#printRegions(res)
self.assertTrue(len(res) >= 7)
def test_run(self):
gs = gelscore.Sequence('GGGGGGGGGGGGGGGGGGGGGGGGGGGGGG')
n = len(gs)
#dist = gelscore.SimilarityDistanceWeight(sim_add=1.0, sd=10.0)
sim = gelscore.SimilarityWeight(sim_add=1.0)
W = sim.weights(gs)
score = sim.score(W)
self.assertAlmostEqual(score, 1.0)
def test_run(self):
gs = gelscore.Sequence('AAAAAAAAAAAAGGGGGGGGGGG')
dist = gelscore.SimilarityWeight(sim_add=1.0)
max_regions = 4
comp = gelscore.SequenceCompositionSimilarity()
rf = gelscore.NormalizedCutRegionFinder(dist, min_region_size=6, score_threshold=0.9, max_regions=max_regions)
res = rf.find(gs)
self.assertTrue(len(res) < max_regions)
self.assertTrue(len(res) == 2)
def test_run(self):
# DAD: this is not a passing test right now, doesn't split into 3
gs = gelscore.Sequence('GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGACDEFGHIKLMNPQRSTVWYGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG')
dist = gelscore.SimilarityWeight(sim_add=1.0)
max_regions = 16
rf = gelscore.NormalizedCutRegionFinder(dist, min_region_size=6, score_threshold=0.01, max_regions=max_regions)
res = rf.find(gs)
printRegions(res)
self.assertTrue(len(res) == 3)
def test_run(self):
gs = gelscore.Sequence('ACDEFGHIKLMNPQRSTVWY')
gs1 = gelscore.ContiguousRegion(gs, 0, 10)
gs2 = gelscore.ContiguousRegion(gs, 5, 15)
#print gs1.composition
#print gs2.composition
gs3 = gs1.intersection(gs2)
#print gs3
self.assertTrue(str(gs3) == 'GHIKL')
def test_run(self):
gs = gelscore.Sequence('MSEAQETHVEQLPESVVDAPVEEQHQEPPQAPDAPQEPQVPQESAPQESAPQEPPAPQEQNDVPPPSNAPIYEGEESHSVQDYQEAHQHHQPPEPQPYYPPPPPGEHMHGRPPMHHRQEGELSNTRLFVRPFPLDVQESELNEIFGPFGPMKEVKILNGFAFVEFEEAESAAKAIEEVHGKSFANQPLEVVYSKLPAKRYRITMKNLPEGCSWQDLKDLARENSLETTFSSVNTRDFDGTGALEFPSEEILVEALERLNNIEFRGSVITVERDDNPPPIRRSNRGGFRGRGGFRGGFRGGFRGGFSRGGFGGPRGGFGGPRGGYGGYSRGGYGGYSRGGYGGSRGGYDSPRGGYDSPRGGYSRGGYGGPRNDYGPPRGSYGGSRGGYDGPRGDYGPPRDAYRTRDAPRERSPTR')
gs1 = gelscore.ContiguousRegion(gs, 74, 106)
gs2 = gelscore.ContiguousRegion(gs, 88, 111)
#print gs1.composition
#print gs2.composition
gs3 = gs1.intersection(gs2)
#print gs3.start
self.assertTrue(gs3.start==88)
self.assertTrue(gs3.end==106)
def test_run(self):
gs = gelscore.Sequence('GGGGGGGGGGGGGGGGGGGGGGGGGGGGGG')
#dist = gelscore.SimilarityDistanceWeight(sim_add=1.0, sd=10.0)
dist = gelscore.SimilarityWeight(sim_add=1.0)
max_regions = 16
rf = gelscore.NormalizedCutRegionFinder(dist, min_region_size=6, score_threshold=0.3, max_regions=max_regions)
res = rf.find(gs)
#for r in res:
# print r.region.start, r.region.end, r.score, r.norm_score, r.region
self.assertTrue(len(res) == 1)
def test_run(self):
"""iterating"""
a = gelscore.Sequence('ACDEFGHIKLAAAAAAAAAAAMNPQRSTVWY')
#b = gelscore.Sequence('AAAAA')
winsize = 5
sw = slide.SequenceWindow(a, winsize)
xi = 0
while sw.isValid():
seq = sw.currentSequence()
#print seq, str(a[xi:(xi+winsize)])
self.assertTrue(str(seq) == str(a[xi:(xi + winsize)]))
sw.next()
xi += 1
def test_run(self):
gs = gelscore.Sequence('GGGGGGGGGGAAAAAAAAAAPPPPPPPPPP')
sim = gelscore.SimilarityWeight(sim_add=1.0)
rf = gelscore.NormalizedCutRegionFinder(sim, min_region_size=5, score_threshold=0.8)
D = sim.weights(gs)
#print D
#print D.sum()
#print D[1,:].sum()
#print D[:,1].sum()
res = rf.find(gs)
#print ""
#for r in res:
# print r.score, r.norm_score, r.region
self.assertTrue(len(res) == 3)
def test_run(self):
gs = gelscore.Sequence('AAAAAAAAAAAAAAAAA')
eq = gelscore.EntropyQuant()
res = eq.quant(gs,20)
self.assertAlmostEqual(res, 0.0)
def test_run(self):
"""searching"""
a = gelscore.Sequence('ACDEFGHIKLAAAAAAAAAAAMNPQRSTVWY')
sw = slide.SequenceWindow(a, 5)
res = sw.search()
self.assertTrue(str(res.currentSequence()) == 'AAAAA')
def test_run(self):
gs = gelscore.Sequence('ACDEFGHIKLMNPQRSTVWY')
gs1 = gelscore.ContiguousRegion(gs, 0, 5)
gs2 = gelscore.ContiguousRegion(gs, 5, 10)
gs3 = gs1.merge(gs2)
def test_run(self):
gs = gelscore.Sequence('ACDEFGHIKLMNPQRSTVWY')
gs1 = gelscore.ContiguousRegion(gs, 0, 5)
gs2 = gelscore.ContiguousRegion(gs, 15, 20)
inter = gs1.intersection(gs2)
self.assertTrue(inter is None)
def test_run(self):
gs = gelscore.Sequence('ACDEFGHIKLMNPQRSTVWY')
eq = gelscore.EntropyQuant()
res = eq.quant(gs,20)
self.assertAlmostEqual(res,1.0)
def test_run(self):
gs = gelscore.Sequence('ACDEFGHIKLMNPQRSTVWY')
gs1 = gelscore.ContiguousRegion(gs)
gs1.trimright(2)
self.assertTrue(gs1[-1] == 'V')
def test_run(self):
gs = gelscore.Sequence('ACDEFGHIKLMNPQRSTVWY')
n = 0
for (i,a) in enumerate(gs):
n += 1
self.assertTrue(n == len(gs))
dout = util.DelimitedOutput()
dout.addHeader('orf', 'S. cerevisiae systematic name', 's')
dout.addHeader('n.above', 'Number of windows with score >= threshold', 'd')
dout.addHeader(
'max.score',
'Maximum score (1 - chi-squared histogram distance on normalized aa-composition histograms)',
'f')
dout.addHeader(
'max.position',
'1-based sequence position of window (start of window) having the maximum score',
'd')
dout.describeHeader(data_outs)
dout.writeHeader(data_outs)
for orf in query_keys:
seq = gelscore.Sequence(prot_dict[orf])
sw = slide.SequenceWindow(seq, options.window_size)
# Slide window and collect results
slideres = sw.slide(comparator)
# Anything interesting?
n_above = 0
max_score = 0.0
max_pos = None
for res in slideres.results():
if res.score > max_score:
max_score = res.score
max_pos = res.position
if res.score >= options.score_threshold:
n_above += 1
# Write out results
# Find stretches of sequence that are above threshold in score
def test_run(self):
"""window larger than sequence"""
a = gelscore.Sequence(
'MLSLIFYLRFPSYIRG') # Actual protein sequence YJR151W-A
sw = slide.SequenceWindow(a, 20)
