added TODO list and wiring up use of Config across function calls

vaxrank/cli.py

@@ -41,6 +41,7 @@
     TemplateDataCreator,
 )
 from .patient_info import PatientInfo
+from .config import Config 
 
 logger = logging.getLogger(__name__)
 
@@ -280,13 +281,14 @@ def run_vaxrank_from_parsed_args(args):
         df = isovar_results_to_dataframe(isovar_results)
         df.to_csv(args.output_isovar_csv, index=False)
 
+    config = Config(min_epitope_score=args.min_epitope_score)
     return run_vaxrank(
         isovar_results=isovar_results,
         mhc_predictor=mhc_predictor,
         vaccine_peptide_length=args.vaccine_peptide_length,
         max_vaccine_peptides_per_variant=args.max_vaccine_peptides_per_mutation,
-        min_epitope_score=args.min_epitope_score,
-        num_mutant_epitopes_to_keep=args.num_epitopes_per_vaccine_peptide)
+        num_mutant_epitopes_to_keep=args.num_epitopes_per_vaccine_peptide,
+        config=config)
 
 def ranked_vaccine_peptides_with_metadata_from_parsed_args(args):
     """

vaxrank/core_logic.py

@@ -15,52 +15,55 @@
 
 from numpy import isclose
 
-from .mutant_protein_fragment import MutantProteinFragment
+from isovar import IsovarResult
+from mhctools.base_predictor import BasePredictor
+
+from .config import Config
 from .epitope_logic import slice_epitope_predictions, predict_epitopes
+from .mutant_protein_fragment import MutantProteinFragment
 from .vaccine_peptide import VaccinePeptide
 from .vaxrank_results import VaxrankResults
 
 logger = logging.getLogger(__name__)
 
 def run_vaxrank(
-        isovar_results,
-        mhc_predictor,
-        vaccine_peptide_length=25,
-        max_vaccine_peptides_per_variant=1,
-        num_mutant_epitopes_to_keep=10000,
-        min_epitope_score=0.0):
+        isovar_results : list[IsovarResult],
+        mhc_predictor : BasePredictor,
+        vaccine_peptide_length : int = 25,
+        max_vaccine_peptides_per_variant : int = 1,
+        num_mutant_epitopes_to_keep : int = 10000,
+        config : Config = None):
     """
     Parameters
     ----------
-    isovar_results : list of isovar.IsovarResult
+    isovar_results  
         Each IsovarResult corresponds to one somatic variant and its collection
          of protein sequences determined from RNA.
 
-    mhc_predictor : mhctools.BasePredictor
+    mhc_predictor
         Object with predict_peptides method, used for making pMHC binding
         predictions
 
-    vaccine_peptide_length : int
+    vaccine_peptide_length 
         Length of vaccine SLP to construct
 
-    max_vaccine_peptides_per_variant : int
+    max_vaccine_peptides_per_variant
         Number of vaccine peptides to generate for each mutation.
 
-    num_mutant_epitopes_to_keep : int, optional
+    num_mutant_epitopes_to_keep 
         Number of top-ranking epitopes for each vaccine peptide to include in
         computation.
 
-    min_epitope_score : float, optional
-        Ignore peptides with binding predictions whose normalized score is less
-        than this.
+    config 
+        Configuration options for epitope scoring, using defaults if not provided
     """
     variant_to_vaccine_peptides_dict = create_vaccine_peptides_dict(
         isovar_results=isovar_results,
         mhc_predictor=mhc_predictor,
         vaccine_peptide_length=vaccine_peptide_length,
         max_vaccine_peptides_per_variant=max_vaccine_peptides_per_variant,
         num_mutant_epitopes_to_keep=num_mutant_epitopes_to_keep,
-        min_epitope_score=min_epitope_score)
+        config=config)
     ranked_list = ranked_vaccine_peptides(variant_to_vaccine_peptides_dict)
 
     return VaxrankResults(
@@ -70,35 +73,35 @@ def run_vaxrank(
 
 
 def create_vaccine_peptides_dict(
-        isovar_results,
-        mhc_predictor,
-        vaccine_peptide_length=25,
-        max_vaccine_peptides_per_variant=1,
-        num_mutant_epitopes_to_keep=10 ** 5,
-        min_epitope_score=0.0):
+        isovar_results : list[IsovarResult],
+        mhc_predictor : BasePredictor,
+        vaccine_peptide_length : int = 25,
+        max_vaccine_peptides_per_variant : int = 1,
+        num_mutant_epitopes_to_keep : int = 10 ** 5,
+        config : Config = None):
     """
     Parameters
     ----------
-    isovar_results : list of isovar.IsovarResult
+    isovar_results 
         List with one object per variant optionally containing protein sequences
 
-    mhc_predictor : mhctools.BasePredictor
+    mhc_predictor
         Object with predict_peptides method, used for making pMHC binding
         predictions
 
-    vaccine_peptide_length : int
+    vaccine_peptide_length 
         Length of vaccine SLP to construct
 
-    max_vaccine_peptides_per_variant : int
+    max_vaccine_peptides_per_variant 
         Number of vaccine peptides to generate for each mutation.
 
-    num_mutant_epitopes_to_keep : int, optional
+    num_mutant_epitopes_to_keep 
         Number of top-ranking epitopes for each vaccine peptide to include in
         computation.
 
-    min_epitope_score : float, optional
-        Ignore peptides with binding predictions whose normalized score is less
-        than this.
+    config 
+        Configuration options for epitope scoring, using defaults if not provided
+   
 
     Returns
     -------
@@ -114,33 +117,33 @@ def create_vaccine_peptides_dict(
             vaccine_peptide_length=vaccine_peptide_length,
             max_vaccine_peptides_per_variant=max_vaccine_peptides_per_variant,
             num_mutant_epitopes_to_keep=num_mutant_epitopes_to_keep,
-            min_epitope_score=min_epitope_score)
+            config=config)
 
         if any(x.contains_mutant_epitopes() for x in vaccine_peptides):
             vaccine_peptides_dict[variant] = vaccine_peptides
 
     return vaccine_peptides_dict
 
 def vaccine_peptides_for_variant(
-        isovar_result,
-        mhc_predictor,
-        vaccine_peptide_length,
-        max_vaccine_peptides_per_variant,
-        num_mutant_epitopes_to_keep=None,
-        min_epitope_score=0.0):
+        isovar_result : IsovarResult,
+        mhc_predictor : BasePredictor,
+        vaccine_peptide_length : int,
+        max_vaccine_peptides_per_variant : int,
+        num_mutant_epitopes_to_keep : int = None,
+        config : Config = None):
     """
     Parameters
     ----------
-    isovar_result : isovar.IsovarResult
+    isovar_result
 
-    mhc_predictor : mhctools.BasePredictor
+    mhc_predictor 
         Object with predict_peptides method, used for making pMHC binding
         predictions
 
-    vaccine_peptide_length : int
+    vaccine_peptide_length 
         Length of vaccine SLP to construct
 
-    max_vaccine_peptides_per_variant : int
+    max_vaccine_peptides_per_variant 
         Number of vaccine peptides to generate for each mutation.
 
     num_mutant_epitopes_to_keep : int, optional
@@ -172,7 +175,7 @@ def vaccine_peptides_for_variant(
     epitope_predictions = predict_epitopes(
         mhc_predictor=mhc_predictor,
         protein_fragment=long_protein_fragment,
-        min_epitope_score=min_epitope_score,
+        config=config,
         genome=variant.ensembl).values()
 
     candidate_vaccine_peptides = []

vaxrank/epitope_logic.py

@@ -17,7 +17,7 @@
 
 
 from pyensembl import Genome
-from mhctools import BasePredictor
+from mhctools.base_predictor import BasePredictor
 
 
 from .config import Config 

vaxrank/epitope_prediction.py

@@ -15,6 +15,30 @@
 
 
 class EpitopePrediction(Serializable):
+    # TODO: 
+    #   - rename to CandidateEpitope
+    #   - add groups of predictions: 
+    #      * mhc_affinity_ic50
+    #      * mhc_affinity_score
+    #      * mhc_affinity_percentile_rank
+    #      * mhc_stability_hours
+    #      * mhc_stability_score
+    #      * mhc_stability_percentile_rank
+    #      * antigen_processing_score
+    #      * antigen_processing_percentile_rank
+    #      * pmhc_presentation_score
+    #      * pmhc_presentation_percentile_rank
+    #      * immunogenicity_score
+    #      * immunogenicity_percentile_rank
+    #  - also change wt_peptide_sequence to:
+    #      * closest_reference_peptide_sequence_in_any_protein 
+    #      * closest_reference_peptide_sequence_in_same_protein
+    #  - and calculate:
+    #      * edit_distance_to_closest_reference_peptide_in_any_protein
+    #      * edit_distance_to_closest_reference_peptide_in_same_protein
+    #      * edit_distance_to_closest_reference_peptide_in_any_protein_PMBEC
+    #      * edit_distance_to_closest_reference_peptide_in_same_protein_PMBEC
+    #  - how to avoid duplicating every prediction for MT vs. WT-any vs. WT-same?
     def __init__(
             self,
             allele,