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_change_as_objectives_basics():
numpy.random.seed(123)
results = []
for boost in (0, 0.1, 0.2, 1):
sequence = random_dna_sequence(1000, seed=123)
problem = DnaOptimizationProblem(
sequence=sequence,
objectives=[
EnforceGCContent(
mini=0.45, maxi=0.55,
window=80).copy_with_changes(locations_span=300),
AvoidChanges(boost=boost).as_passive_objective()
])
problem.optimize()
differences = sequences_differences(problem.sequence,
problem.sequence_before)
results.append(differences)
assert results[0] > 40
assert (results[0] > results[1] > results[2] > results[3])
assert results[-1] == 0
def compatibility_condition(location1, location2, problem):
seq1 = location1.extract_sequence(problem.sequence)
seq2 = location2.extract_sequence(problem.sequence)
return sequences_differences(seq1, seq2) >= 2
"""Example of use of the AvoidChanges as an objective to minimize modifications
of a sequence."""
from dnachisel import (DnaOptimizationProblem, random_dna_sequence,
AvoidPattern, AvoidChanges, sequences_differences,
EnforceGCContent)
# Note: we are not providing a location for AvoidChanges: it applies globally
for boost in (0, 0.1, 1, 10.0):
sequence = random_dna_sequence(1000, seed=123)
problem = DnaOptimizationProblem(
sequence=sequence,
objectives=[
EnforceGCContent(mini=0.45, maxi=0.55, window=80),
AvoidChanges(boost=boost).as_passive_objective()
])
problem.optimize()
differences = sequences_differences(problem.sequence,
problem.sequence_before)
print("%d nucleotides modified for boost=%.1f" % (differences, boost))