def test_mhc_predictor_error():
genome = EnsemblRelease(species="mouse")
wdr13_transcript = genome.transcripts_by_name("Wdr13-001")[0]
protein_fragment = MutantProteinFragment(
variant=Variant('X', '8125624', 'C', 'A'),
gene_name='Wdr13',
amino_acids='KLQGHSAPVLDVIVNCDESLLASSD',
mutant_amino_acid_start_offset=12,
mutant_amino_acid_end_offset=13,
n_overlapping_reads=71,
n_alt_reads=25,
n_ref_reads=46,
n_alt_reads_supporting_protein_sequence=2,
supporting_reference_transcripts=[wdr13_transcript])
# throws an error for each prediction, make sure vaxrank doesn't fall down
class FakeMHCPredictor:
def predict_subsequences(self, x):
raise ValueError('I throw an error in your general direction')
epitope_predictions = predict_epitopes(mhc_predictor=FakeMHCPredictor(),
protein_fragment=protein_fragment,
genome=genome)
eq_(0, len(epitope_predictions))
def test_mhc_predictor_error():
genome = EnsemblRelease(species="mouse")
wdr13_transcript = genome.transcripts_by_name("Wdr13-001")[0]
protein_fragment = MutantProteinFragment(
variant=Variant('X', '8125624', 'C', 'A'),
gene_name='Wdr13',
amino_acids='KLQGHSAPVLDVIVNCDESLLASSD',
mutant_amino_acid_start_offset=12,
mutant_amino_acid_end_offset=13,
n_overlapping_reads=71,
n_alt_reads=25,
n_ref_reads=46,
n_alt_reads_supporting_protein_sequence=2,
supporting_reference_transcripts=[wdr13_transcript])
# throws an error for each prediction, make sure vaxrank doesn't fall down
class FakeMHCPredictor:
def predict_subsequences(self, x):
raise ValueError('I throw an error in your general direction')
epitope_predictions = predict_epitopes(
mhc_predictor=FakeMHCPredictor(),
protein_fragment=protein_fragment,
genome=genome)
eq_(0, len(epitope_predictions))
def test_reference_peptide_logic():
genome = EnsemblRelease(species="mouse")
wdr13_transcript = genome.transcripts_by_name("Wdr13-001")[0]
protein_fragment = MutantProteinFragment(
variant=Variant('X', '8125624', 'C', 'A'),
gene_name='Wdr13',
amino_acids='KLQGHSAPVLDVIVNCDESLLASSD',
mutant_amino_acid_start_offset=12,
mutant_amino_acid_end_offset=13,
n_overlapping_reads=71,
n_alt_reads=25,
n_ref_reads=46,
n_alt_reads_supporting_protein_sequence=2,
supporting_reference_transcripts=[wdr13_transcript])
epitope_predictions = predict_epitopes(
mhc_predictor=RandomBindingPredictor(["H-2-Kb"]),
protein_fragment=protein_fragment,
genome=genome)
# occurs in protein ENSMUSP00000033506
prediction_occurs_in_reference = epitope_predictions[('NCDESLLAS',
'H-2-Kb')]
prediction_does_not_occur_in_reference = epitope_predictions[('LDVIVNCDE',
'H-2-Kb')]
ok_(prediction_occurs_in_reference.occurs_in_reference)
ok_(not prediction_does_not_occur_in_reference.occurs_in_reference)
# construct a simple vaccine peptide having these two predictions, which makes it easy to check
# for mutant/WT scores from single contributors
vaccine_peptide = VaccinePeptide(protein_fragment, [
prediction_occurs_in_reference, prediction_does_not_occur_in_reference
])
eq_(prediction_occurs_in_reference.logistic_epitope_score(),
vaccine_peptide.wildtype_epitope_score)
eq_(prediction_does_not_occur_in_reference.logistic_epitope_score(),
vaccine_peptide.mutant_epitope_score)
def test_reference_peptide_logic():
genome = EnsemblRelease(species="mouse")
wdr13_transcript = genome.transcripts_by_name("Wdr13-001")[0]
protein_fragment = MutantProteinFragment(
variant=Variant('X', '8125624', 'C', 'A'),
gene_name='Wdr13',
amino_acids='KLQGHSAPVLDVIVNCDESLLASSD',
mutant_amino_acid_start_offset=12,
mutant_amino_acid_end_offset=13,
n_overlapping_reads=71,
n_alt_reads=25,
n_ref_reads=46,
n_alt_reads_supporting_protein_sequence=2,
supporting_reference_transcripts=[wdr13_transcript])
epitope_predictions = predict_epitopes(
mhc_predictor=RandomBindingPredictor(["H-2-Kb"]),
protein_fragment=protein_fragment,
genome=genome)
# occurs in protein ENSMUSP00000033506
prediction_occurs_in_reference = epitope_predictions[('NCDESLLAS', 'H-2-Kb')]
prediction_does_not_occur_in_reference = epitope_predictions[('LDVIVNCDE', 'H-2-Kb')]
ok_(prediction_occurs_in_reference.occurs_in_reference)
ok_(not prediction_does_not_occur_in_reference.occurs_in_reference)
# construct a simple vaccine peptide having these two predictions, which makes it easy to check
# for mutant/WT scores from single contributors
vaccine_peptide = VaccinePeptide(
protein_fragment,
[prediction_occurs_in_reference, prediction_does_not_occur_in_reference])
eq_(prediction_occurs_in_reference.logistic_epitope_score(),
vaccine_peptide.wildtype_epitope_score)
eq_(prediction_does_not_occur_in_reference.logistic_epitope_score(),
vaccine_peptide.mutant_epitope_score)
