added known epitope tests

mhcflurry/predictor_base.py

@@ -15,6 +15,7 @@
 from collections import defaultdict
 
 import numpy as np
+from six import string_types
 
 from .peptide_encoding import fixed_length_index_encoding
 from .amino_acid import (
@@ -114,6 +115,10 @@ class PredictorBase(object):
         amino acid characters. The prediction for a single peptide will be
         the average of expanded 9mers.
         """
+        if isinstance(peptides, string_types):
+            raise TypeError("Input must be a list of peptides, not %s : %s" % (
+                peptides, type(peptides)))
+
         input_matrix, original_peptide_indices = self.encode_peptides(peptides)
         # non-9mer peptides get multiple predictions, which are then combined
         # with the combine_fn argument

test/test_known_class1_epitopes.py

 
-def test_known_class1_epitopes():
-    pass
+from mhcflurry import Class1BindingPredictor
+
+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
+    model = Class1BindingPredictor.from_allele_name("HLA-A*01:01")
+    ic50s = model.predict_peptides_ic50(["ESDPIVAQY"])
+    print(ic50s)
+    assert len(ic50s) == 1
+    ic50 = ic50s[0]
+    assert ic50 <= 500
+
+def test_HIV_epitope():
+    # Test the A2 HIV epitope SLYNTVATL from
+    #    The HIV-1 HLA-A2-SLYNTVATL Is a Help-Independent CTL Epitope
+    model = Class1BindingPredictor.from_allele_name("HLA-A*02:01")
+    ic50s = model.predict_peptides_ic50(["SLYNTVATL"])
+    print(ic50s)
+    assert len(ic50s) == 1
+    ic50 = ic50s[0]
+    assert ic50 <= 500
+
+
+if __name__ == "__main__":
+    test_MAGE_epitope()
+    test_HIV_epitope()