def test_that_constraints_in_records_are_accounted_for():
    sequence = "ATACGTCTCTAG"
    rec = sequence_to_biopython_record(sequence)
    annotate_record(rec, label="@cds")
    from genedom import BUILTIN_STANDARDS

    emma = BUILTIN_STANDARDS["EMMA"]
    p7 = emma.domesticators["p7"]
    result = p7.domesticate(rec)
    seq_after = str(
        result.record_after[len(p7.left_flank):-len(p7.right_flank)].seq)
    assert translate(seq_after) == translate(sequence)
Example #2
0
def test_AvoidRareCodons_as_constraint():
    numpy.random.seed(123)

    sequence = "ATG" "TTT" "ATA" "CCA" "CTT" "TAG"
    problem = DnaOptimizationProblem(
        sequence=sequence,
        constraints=[EnforceTranslation(),
                     AvoidRareCodons(0.11, "e_coli")],
    )
    assert problem.all_constraints_pass()
    assert problem.sequence_edits_as_array().sum() == 4
    assert translate(problem.sequence) == translate(sequence)
def test_EnforceTranslation_bacterial_valine():
    table_name = "Bacterial"
    protein = "LLTMMVTTTTVMVL"
    protein_sequence = reverse_translate(protein, table=table_name)

    for first_codon_before, first_codon_after in [
        ("ATG", "ATG"),  # methionine stays the only methionine codon
        ("GTG", "GTG"),  # valine-start-codon stays the only valine-start-codon
    ]:
        sequence = first_codon_before + protein_sequence
        cds_constraint = EnforceTranslation(
            genetic_table="Bacterial", start_codon="keep"
        )
        problem = DnaOptimizationProblem(
            sequence=sequence,
            constraints=[cds_constraint],
            objectives=[EnforceChanges()],
            logger=None,
        )
        assert problem.constraints[0].translation == "MLLTMMVTTTTVMVL"
        problem.optimize()
        protein_after = translate(
            problem.sequence, table_name, assume_start_codon=True
        )
        assert protein_after == "M" + protein
        assert problem.sequence[:3] == first_codon_after
Example #4
0
def test_AvoidRareCodons_as_constraint_reversed():
    numpy.random.seed(123)

    sequence = "ATG" "TTT" "ATA" "CCA" "CTT" "TAG"
    rev_sequence = reverse_complement(sequence)
    location = (0, len(sequence), -1)
    problem = DnaOptimizationProblem(
        sequence=rev_sequence,
        constraints=[
            EnforceTranslation(location=location),
            AvoidRareCodons(0.11, "e_coli", location=location),
        ],
    )
    assert problem.all_constraints_pass()
    assert problem.sequence_edits_as_array().sum() == 4
    new_sequence = reverse_complement(problem.sequence)
    assert translate(new_sequence) == translate(sequence)
def test_AvoidStopCodons():
    numpy.random.seed(123)
    problem = DnaOptimizationProblem(
        sequence="".join(["ATT", "TAG", "GCC", "TGA", "ATC", "TAA"]),
        constraints=[AvoidStopCodons()],
        logger=None,
    )
    assert not problem.all_constraints_pass()
    problem.resolve_constraints()
    assert problem.all_constraints_pass()
    assert "*" not in translate(problem.sequence)
Example #6
0
def test_maximal_protein_sequence_change():
    np.random.seed(123)
    protein = dc.random_protein_sequence(200)
    sequence = dc.reverse_translate(protein)
    problem = dc.DnaOptimizationProblem(
        sequence=sequence,
        constraints=[dc.EnforceTranslation()],
        objectives=[dc.EnforceChanges()],
    )
    problem.resolve_constraints()
    problem.optimize()
    assert problem.number_of_edits() == 238
    assert dc.translate(problem.sequence) == protein