old_contents: # Copyright (c) 2016. 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.
  
  from __future__ import print_function
  
  import numpy as np
  import pandas as pd
  
  from varcode import EffectCollection
  from varcode.effects import Substitution
  
  def snv_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_variants = cohort.load_variants(
          patients=[cohort.patient_from_id(patient_id)], **kwargs)
      if patient_id in patient_variants:
          return len(patient_variants[patient_id])
      return np.nan
  
  def nonsynonymous_snv_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_nonsynonymous_effects = cohort.load_effects(
          only_nonsynonymous=True, patients=[cohort.patient_from_id(patient_id)], **kwargs)
      if patient_id in patient_nonsynonymous_effects:
          return len(patient_nonsynonymous_effects[patient_id])
      return np.nan
  
  def missense_snv_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_missense_effects = cohort.load_effects(
          only_nonsynonymous=True, 
          patients=[cohort.patient_from_id(patient_id)], 
          filter_fn=lambda effect, variant_metadata: type(effect) == Substitution,
          **kwargs)
      if patient_id in patient_missense_effects:
          return len(patient_missense_effects[patient_id])
      return np.nan
  
  def neoantigen_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_neoantigens = cohort.load_neoantigens(patients=[cohort.patient_from_id(patient_id)], **kwargs)
      return len(patient_neoantigens[patient_neoantigens["patient_id"] == patient_id])
  
  def expressed_neoantigen_count(row, cohort, **kwargs):
      return neoantigen_count(row, cohort, only_expressed=True)
  
new_contents: # Copyright (c) 2016. 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.
  
  from __future__ import print_function
  
  import numpy as np
  from varcode.effects import Substitution
  
  def snv_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_variants = cohort.load_variants(
          patients=[cohort.patient_from_id(patient_id)], **kwargs)
      if patient_id in patient_variants:
          return len(patient_variants[patient_id])
      return np.nan
  
  def nonsynonymous_snv_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_nonsynonymous_effects = cohort.load_effects(
          only_nonsynonymous=True, patients=[cohort.patient_from_id(patient_id)], **kwargs)
      if patient_id in patient_nonsynonymous_effects:
          return len(patient_nonsynonymous_effects[patient_id])
      return np.nan
  
  def missense_snv_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_missense_effects = cohort.load_effects(
          only_nonsynonymous=True, 
          patients=[cohort.patient_from_id(patient_id)], 
          filter_fn=lambda effect, variant_metadata: type(effect) == Substitution,
          **kwargs)
      if patient_id in patient_missense_effects:
          return len(patient_missense_effects[patient_id])
      return np.nan
  
  def neoantigen_count(row, cohort, **kwargs):
      patient_id = row["patient_id"]
      patient_neoantigens = cohort.load_neoantigens(patients=[cohort.patient_from_id(patient_id)], **kwargs)
      return len(patient_neoantigens[patient_neoantigens["patient_id"] == patient_id])
  
  def expressed_neoantigen_count(row, cohort, **kwargs):
      return neoantigen_count(row, cohort, only_expressed=True)
  
subject: remove unused imports