fatmacankara commited on
Commit
60c9dfd
·
1 Parent(s): 7838db7

Update code/alphafold_featureVector.py

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  1. code/alphafold_featureVector.py +14 -11
code/alphafold_featureVector.py CHANGED
@@ -29,6 +29,8 @@ from process_input import clean_data
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  from alphafold_model import *
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  def getModelInfo(uniprotID, varPos, wt, models_we_need, path_to_output_files ):
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  modelInfo = {}
 
 
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  for mod in models_we_need:
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  try:
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  pdb_path = hf_hub_download(repo_id="HuBioDataLab/AlphafoldStructures", filename=f"AF-{uniprotID}-F{mod}-model_v4.pdb.gz",repo_type = 'dataset')
@@ -201,19 +203,20 @@ def alphafold(input_set, mode, impute):
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  models_for_protein = [val for key, val in model_count.items() if uniprotID in key.split(';')] # We have this many models for the protein.
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  which_model_mutation = which_model(int(varPos)) # List of models in which the mutation can be found.
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  models_for_all_annotations = {}
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- for annot in annotation_list: # Bu noktada hepsinin tek tek yazilmasi lazim
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  models_for_annotations = {} # Recording which position is found in which model file.
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- for annot_position in ast.literal_eval(data.at[i, annot]):
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- if str(annot_position) != 'nan' and annot_position != '':
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- models_for_that_position = which_model(int(annot_position))
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- else:
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- models_for_that_position = {}
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- for key, val in models_for_that_position.items():
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- if key not in models_for_annotations.keys():
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- models_for_annotations[key] = [val]
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  else:
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- models_for_annotations[key] += [val]
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- models_for_all_annotations[annot] = models_for_annotations
 
 
 
 
 
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  # print('models_for_annotations', models_for_annotations)
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  new_dict = {}
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  for key, val in models_for_all_annotations.items():
 
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  from alphafold_model import *
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  def getModelInfo(uniprotID, varPos, wt, models_we_need, path_to_output_files ):
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  modelInfo = {}
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+ st.write(uniprotID)
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+ st.write(f"AF-{uniprotID}-F{mod}-model_v4.pdb.gz")
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  for mod in models_we_need:
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  try:
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  pdb_path = hf_hub_download(repo_id="HuBioDataLab/AlphafoldStructures", filename=f"AF-{uniprotID}-F{mod}-model_v4.pdb.gz",repo_type = 'dataset')
 
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  models_for_protein = [val for key, val in model_count.items() if uniprotID in key.split(';')] # We have this many models for the protein.
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  which_model_mutation = which_model(int(varPos)) # List of models in which the mutation can be found.
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  models_for_all_annotations = {}
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+ for annot in annotation_list: # Needs annots written one by one
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  models_for_annotations = {} # Recording which position is found in which model file.
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+ if data.at[i, annot] != 'hit':
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+ for annot_position in ast.literal_eval(data.at[i, annot]):
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+ if str(annot_position) != 'nan' and annot_position != '':
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+ models_for_that_position = which_model(int(annot_position))
 
 
 
 
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  else:
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+ models_for_that_position = {}
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+ for key, val in models_for_that_position.items():
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+ if key not in models_for_annotations.keys():
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+ models_for_annotations[key] = [val]
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+ else:
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+ models_for_annotations[key] += [val]
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+ models_for_all_annotations[annot] = models_for_annotations
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  # print('models_for_annotations', models_for_annotations)
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  new_dict = {}
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  for key, val in models_for_all_annotations.items():