def test_EnforceRegionsCompatibility():
# Two enzymes, BsmBI(CGTCTC) is GC-rich, EcoRI(GAATTC) is GC-poor, which
# enzyme will be chosen and inserted in the sequence depends on the other
# constraint on GC content
numpy.random.seed(123)
def compatibility_condition(location1, location2, problem):
seq1 = location1.extract_sequence(problem.sequence)
seq2 = location2.extract_sequence(problem.sequence)
return sequences_differences(seq1, seq2) >= 2
locations = [(0, 4), (50, 54), (100, 104), (150, 154)]
problem = DnaOptimizationProblem(
sequence=random_dna_sequence(200, seed=123),
constraints=[
EnforceRegionsCompatibility(
locations=locations,
compatibility_condition=compatibility_condition,
condition_label="2bp difference",
),
EnforceGCContent(mini=0.4, maxi=0.6, window=40),
],
logger=None,
)
assert not any([e.passes for e in problem.constraints_evaluations()])
problem.resolve_constraints()
assert problem.all_constraints_pass()
seq = problem.sequence
assert [
sequences_differences(seq[s1:e1], seq[s2:e2]) >= 2
for (s1, e1), (s2, e2) in itertools.combinations(locations, 2)
]
def test_avoid_hairpins_on_extremities():
# see https://github.com/Edinburgh-Genome-Foundry/DnaChisel/issues/37
problem = DnaOptimizationProblem(
sequence="attcaatgggggggggggggggggggggggggtagccta",
constraints=[AvoidHairpins(stem_size=3, hairpin_window=8)])
evaluation = problem.constraints_evaluations().evaluations[0]
assert str(evaluation.locations) == "[0-6, 32-39]"
problem.resolve_constraints()
assert problem.all_constraints_pass()
def test_AvoidPattern_with_jaspar_motifs():
stringio = StringIO(JASPAR_CONTENT)
motif_patterns = MotifPssmPattern.list_from_file(stringio,
file_format="jaspar",
relative_threshold=0.9)
problem = DnaOptimizationProblem(
sequence="GGGGGGGGGGTGCGTGATTAAAGGGGG",
constraints=[AvoidPattern(p) for p in motif_patterns],
)
assert 2 == len(problem.constraints_evaluations().all_locations())
problem.resolve_constraints()
assert problem.all_constraints_pass()
def test_avoid_matches_with_phage():
PHAGE_TAXID = "697289"
collection = GenomeCollection()
index = collection.get_taxid_bowtie_index_path(PHAGE_TAXID, version="1")
problem = DnaOptimizationProblem(
sequence=random_dna_sequence(30, seed=123),
constraints=[AvoidMatches(bowtie_index=index, match_length=10)],
logger=None,
)
all_breaches = problem.constraints_evaluations().all_locations()
assert len(all_breaches) == 5
problem.resolve_constraints()
assert problem.all_constraints_pass()
def compute_forbidden_patterns_locations(self, record):
"""Return an array where ``arr[i] == 1`` means that i is surrounded by
a user-forbidden pattern."""
pattern_constraints = [
AvoidPattern(homopolymer_pattern(c, 5)) for c in 'ATGC'
]
kmer_constraints = [
AvoidPattern(repeated_kmers(k, n))
for k, n in [(4, 2), (3, 3), (2, 4)]
]
problem = DnaOptimizationProblem(sequence=record,
constraints=pattern_constraints +
kmer_constraints)
constraints_breaches = group_overlapping_segments([
(f.location.start, f.location.end)
for ev in problem.constraints_evaluations()
for f in ev.locations_to_biopython_features() if not ev.passes
])
return segments_to_array(constraints_breaches, len(record))
