<gh_stars>10-100
# Copyright (c) 2014-2017. Mount Sinai School of Medicine
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#       http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
Make sure all class I binding predictors give a high IC50 and percentile rank.
"""
import mhctools

mhc_classes = [
    mhctools.NetMHCcons,
    mhctools.NetMHCpan,
    mhctools.NetMHC,
    mhctools.NetMHC3,
    mhctools.NetMHC4,
    mhctools.IedbNetMHCcons,
    mhctools.IedbNetMHCpan,
    mhctools.IedbSMM,
    mhctools.IedbSMM_PMBEC,
]

# Tests assume that a netMHC-3.4 binary exists, and that netMHC is 4.0.
program_name_overrides = {mhctools.NetMHC3: "netMHC-3.4"}

def expect_binder(mhc_model, peptide):
    prediction = mhc_model.predict_peptides([peptide])[0]
    assert prediction.value < 500, "Expected %s to have IC50 < 500nM, got %s" % (
        peptide, prediction)

def make_mhc_model(mhc_class, alleles):
    kwargs = {"alleles": alleles, "default_peptide_lengths": [9]}
    if mhc_class in program_name_overrides:
        kwargs.update({"program_name": program_name_overrides[mhc_class]})
    return mhc_class(**kwargs)

def test_MAGE_epitope():
    # Test the A1 MAGE epitope ESDPIVAQY from
    #   Identification of a Titin-Derived HLA-A1-Presented Peptide
    #   as a Cross-Reactive Target for Engineered MAGE A3-Directed
    #   T Cells
    for mhc_class in mhc_classes:
        mhc_model = make_mhc_model(mhc_class, "HLA-A*01:01")
        yield (expect_binder, mhc_model, "ESDPIVAQY")

def test_HIV_epitope():
    # Test the A2 HIV epitope SLYNTVATL from
    #    The HIV-1 HLA-A2-SLYNTVATL Is a Help-Independent CTL Epitope
    for mhc_class in mhc_classes:
        mhc_model = make_mhc_model(mhc_class, "HLA-A*02:01")
        yield (expect_binder, mhc_model, "SLYNTVATL")

# Copyright (c) 2014-2017. Mount Sinai School of Medicine
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#       http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
Make sure all class I binding predictors give a high IC50 and percentile rank.
"""
import mhctools

mhc_classes = [
    mhctools.NetMHCcons,
    mhctools.NetMHCpan,
    mhctools.NetMHC,
    mhctools.NetMHC3,
    mhctools.NetMHC4,
    mhctools.IedbNetMHCcons,
    mhctools.IedbNetMHCpan,
    mhctools.IedbSMM,
    mhctools.IedbSMM_PMBEC,
]

# Tests assume that a netMHC-3.4 binary exists, and that netMHC is 4.0.
program_name_overrides = {mhctools.NetMHC3: "netMHC-3.4"}

def expect_binder(mhc_model, peptide):
    prediction = mhc_model.predict_peptides([peptide])[0]
    assert prediction.value < 500, "Expected %s to have IC50 < 500nM, got %s" % (
        peptide, prediction)

def make_mhc_model(mhc_class, alleles):
    kwargs = {"alleles": alleles, "default_peptide_lengths": [9]}
    if mhc_class in program_name_overrides:
        kwargs.update({"program_name": program_name_overrides[mhc_class]})
    return mhc_class(**kwargs)

def test_MAGE_epitope():
    # Test the A1 MAGE epitope ESDPIVAQY from
    #   Identification of a Titin-Derived HLA-A1-Presented Peptide
    #   as a Cross-Reactive Target for Engineered MAGE A3-Directed
    #   T Cells
    for mhc_class in mhc_classes:
        mhc_model = make_mhc_model(mhc_class, "HLA-A*01:01")
        yield (expect_binder, mhc_model, "ESDPIVAQY")

def test_HIV_epitope():
    # Test the A2 HIV epitope SLYNTVATL from
    #    The HIV-1 HLA-A2-SLYNTVATL Is a Help-Independent CTL Epitope
    for mhc_class in mhc_classes:
        mhc_model = make_mhc_model(mhc_class, "HLA-A*02:01")
        yield (expect_binder, mhc_model, "SLYNTVATL")
# Copyright (c) 2014-2017. Mount Sinai School of Medicine # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # #       http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. Make sure all class I binding predictors give a high IC50 and percentile rank. # Tests assume that a netMHC-3.4 binary exists, and that netMHC is 4.0. # Test the A1 MAGE epitope ESDPIVAQY from #   Identification of a Titin-Derived HLA-A1-Presented Peptide #   as a Cross-Reactive Target for Engineered MAGE A3-Directed #   T Cells # Test the A2 HIV epitope SLYNTVATL from #    The HIV-1 HLA-A2-SLYNTVATL Is a Help-Independent CTL Epitope