coconut.src package

Subpackages

• coconut.src.Core package
  • Submodules
  • coconut.src.Core.BaseScores module
    • BaseScoresAlign
      • BaseScoresAlign.scoremat
      • BaseScoresAlign.get_scoremat()
      • BaseScoresAlign.read_matrix_file()
  • coconut.src.Core.CoiledCoilAlignClass module
    • CoiledCoilAlign
      • CoiledCoilAlign.BaseAlignmentFile
      • CoiledCoilAlign.constant_score
      • CoiledCoilAlign.fsseq1
      • CoiledCoilAlign.fsseq2
      • CoiledCoilAlign.pc_prot1_file
      • CoiledCoilAlign.pc_prot2_file
      • CoiledCoilAlign.ppath
      • CoiledCoilAlign.PROB_CUTOFF
      • CoiledCoilAlign.prot1
      • CoiledCoilAlign.prot2
      • CoiledCoilAlign.topk
      • CoiledCoilAlign.Filter_OffDiagonal_Segments()
      • CoiledCoilAlign.Write_Topn_Alignments()
      • CoiledCoilAlign.add_alignment_scores_segmentdict()
      • CoiledCoilAlign.add_sequence_at_cterm()
      • CoiledCoilAlign.add_sequence_with_gaps()
      • CoiledCoilAlign.coconut_align()
      • CoiledCoilAlign.create_base_alignment()
      • CoiledCoilAlign.get_hamming_distances()
      • CoiledCoilAlign.get_next_segment_lists()
      • CoiledCoilAlign.get_tracepath_alignments()
      • CoiledCoilAlign.get_tracepath_alignments_fullseq()
      • CoiledCoilAlign.k_shortest_paths()
      • CoiledCoilAlign.load_Coiled_Coil_Segments_full()
      • CoiledCoilAlign.load_paircoil_alignment()
      • CoiledCoilAlign.plot_alignment_segments()
      • CoiledCoilAlign.plot_segments()
      • CoiledCoilAlign.plot_tree()
      • CoiledCoilAlign.plot_tree_simple()
      • CoiledCoilAlign.read_aligned_fasta()
      • CoiledCoilAlign.read_coco_alignment_graph()
      • CoiledCoilAlign.read_coco_alignment_graph_new()
      • CoiledCoilAlign.read_fasta()
      • CoiledCoilAlign.segment_traceback()
      • CoiledCoilAlign.write_alignment()
      • CoiledCoilAlign.write_alignment_with_heptad()
    • DefaultDictNoAdd
  • coconut.src.Core.CoiledCoilClass module
    • CoiledCoil
      • CoiledCoil.CC
      • CoiledCoil.display_CC()
      • CoiledCoil.get_CC()
      • CoiledCoil.get_num_monomers()
      • CoiledCoil.set_CC_orientation()
      • CoiledCoil.set_CC_values()
  • coconut.src.Core.ExtendCCClass module
    • DefaultDictNoAdd
    • ExtendCoiledCoil
      • ExtendCoiledCoil.DistDict
      • ExtendCoiledCoil.DistMat
      • ExtendCoiledCoil.p1_PC
      • ExtendCoiledCoil.p2_PC
      • ExtendCoiledCoil.pc_prot1_file
      • ExtendCoiledCoil.pc_prot2_file
      • ExtendCoiledCoil.phep1
      • ExtendCoiledCoil.phep2
      • ExtendCoiledCoil.ppath
      • ExtendCoiledCoil.PROB_CUTOFF
      • ExtendCoiledCoil.prot1
      • ExtendCoiledCoil.prot1_max
      • ExtendCoiledCoil.prot1_min
      • ExtendCoiledCoil.prot1res
      • ExtendCoiledCoil.prot2
      • ExtendCoiledCoil.prot2_max
      • ExtendCoiledCoil.prot2_min
      • ExtendCoiledCoil.Generate_Alignments_Scores()
      • ExtendCoiledCoil.Sample_Plot_Combine()
      • ExtendCoiledCoil.def_value()
      • ExtendCoiledCoil.extend_segment()
      • ExtendCoiledCoil.get_parallel_diagonal_alignment()
      • ExtendCoiledCoil.load_paircoil_alignment()
      • ExtendCoiledCoil.plot_alignment()
      • ExtendCoiledCoil.plot_individual_cc_scores()
  • coconut.src.Core.InputClass module
    • InputCC
      • InputCC.input_filename
      • InputCC.interface_dict
      • InputCC.num_monomers
      • InputCC.valid_aas
      • InputCC.valid_hep
      • InputCC.check_aa_hep()
      • InputCC.check_aa_seq()
      • InputCC.check_inp_len()
      • InputCC.correct_P_AP_compatibility()
      • InputCC.get_cc_orientation()
      • InputCC.load_CCData()
      • InputCC.print_input_info()
      • InputCC.raise_error()
  • coconut.src.Core.PairCoilClass module
    • DefaultDictNoAdd
    • PairCoilParse
      • PairCoilParse.header
      • PairCoilParse.p1_PC
      • PairCoilParse.pc_prot1_file
      • PairCoilParse.phep1
      • PairCoilParse.phep2
      • PairCoilParse.PROB_CUTOFF
      • PairCoilParse.correct_incorrectly_Indentified_heptad()
      • PairCoilParse.get_heptad_repeats_pairs()
      • PairCoilParse.get_pc_seq()
      • PairCoilParse.hamming_distance()
      • PairCoilParse.load_Pcoil_alignment()
      • PairCoilParse.load_Pcoil_alignment_backup()
      • PairCoilParse.load_paircoil_alignment()
      • PairCoilParse.write_Updated_Paircoil_Probs()
  • coconut.src.Core.ScoringClass module
    • ScoreCC
      • ScoreCC.ALLPROBS
      • ScoreCC.ALLSCORES
      • ScoreCC.AP_Prior_Prob
      • ScoreCC.AP_Prior_Prob_dimer
      • ScoreCC.branching_dict
      • ScoreCC.D_PREDS
      • ScoreCC.D_PROBS
      • ScoreCC.D_PROBS_mean
      • ScoreCC.Distributions
      • ScoreCC.P_Prior_Prob
      • ScoreCC.P_Prior_Prob_dimer
      • ScoreCC.Generate_CC_Bayesian_Scores()
      • ScoreCC.Generate_CC_RF_Scores()
      • ScoreCC.Generate_CC_Scores_Bayes()
      • ScoreCC.Generate_CC_Scores_RF()
      • ScoreCC.Get_Prediction_Probs()
      • ScoreCC.Get_Predictions()
      • ScoreCC.Predict_CC_Stability()
      • ScoreCC.Score_Coiled_coil()
      • ScoreCC.Write_Bayesian_Probabilities()
      • ScoreCC.Write_Raw_Scores()
      • ScoreCC.calculate_prior_probabilities()
      • ScoreCC.find_score_ada_ada()
      • ScoreCC.find_score_ada_dad()
      • ScoreCC.find_score_dad_ada()
      • ScoreCC.find_score_dad_dad()
      • ScoreCC.get_BS()
      • ScoreCC.get_Distributions()
      • ScoreCC.load_prior_probabilities()
      • ScoreCC.score_dimer_RF()
      • ScoreCC.score_dimer_bayesian()
  • coconut.src.Core.SlidingWindowsClass module
    • DefaultDictNoAdd
    • SlidingWindows
      • SlidingWindows.pc_prot1_file
      • SlidingWindows.pc_prot2_file
      • SlidingWindows.PROB_CUTOFF
      • SlidingWindows.prot1_seq
      • SlidingWindows.prot2_seq
      • SlidingWindows.sw_file_a
      • SlidingWindows.sw_file_d
      • SlidingWindows.swlen
      • SlidingWindows.swlen_d
      • SlidingWindows.Get_Sliding_Windows()
      • SlidingWindows.Write_CC_InputFile()
      • SlidingWindows.check_heptad_repeat()
      • SlidingWindows.load_paircoil_alignment()
  • coconut.src.Core.ml_prediction module
    • load_dataset()
    • pred_round()
    • train_RF_models()
    • train_RF_models_plot()
    • train_bayesian_models()
  • coconut.src.Core.predict_cc module
    • predict_coiled_coil()
  • coconut.src.Core.read_CC_properties module
    • check_heptad_repeat()
    • generate_AA_pairs_antiparallel_dimers()
    • generate_AA_pairs_frequency()
    • generate_AA_pairs_parallel_dimers()
    • generate_Hex_pairs_antiparallel_dimers()
    • generate_Hex_pairs_dimers()
    • generate_Hex_pairs_parallel_dimers()
    • max_normalize_dicts()
    • shifting_align_dimer()
    • total_normalize_dicts()
    • write_unique_hexpairs()
  • coconut.src.Core.read_frequency_scores module
    • load_AA_Frequency_scores()
    • load_AA_Frequency_scores_logs()
  • coconut.src.Core.test_model_database module
    • test_model()
  • coconut.src.Core.train_models module
    • bin_values()
    • calculate_feature_values()
    • check_distribution_pval()
    • check_heptad_repeat()
    • dump_frequency_models()
    • filter_dimer()
    • generate_dodec_pairs()
    • get_BS()
    • get_kerneldensity()
    • load_training_data()
    • load_training_data_singlefile()
    • read_cc_file()
    • read_dodec_pairs()
    • train_kde_models()
    • write_dict()
  • Module contents
• coconut.src.Models package
  • Submodules
  • coconut.src.Models.ModelClass module
    • Models
      • Models.Hexscores
      • Models.RF_Models
      • Models.RF_PaddingSize
      • Models.scoring_dicts
      • Models.get_KDE_Models()
      • Models.get_RF_Models()
      • Models.get_padding_size()
      • Models.get_scoring_dicts()
      • Models.load_AA_distributions()
      • Models.load_RF_models()
      • Models.load_kde_models()
      • Models.plot_KDE_Models()
  • Module contents

Submodules

coconut.src.CoconutClass module

class coconut.src.CoconutClass.COCONUT

Bases: object

Summary

plot_dimer_length_distribution(Distributions)

Summary

Parameters

Distributions (TYPE) – Description

Returns

Description

Return type

TYPE

plot_pairwise_distributions(Res_stats)

Summary

Parameters

Res_stats (TYPE) – Description

Returns

Description

Return type

TYPE

predict_coiled_coil()

Summary

Returns

Description

Return type

TYPE

prediction_example()

Summary

Returns

Description

Return type

TYPE

test_coconut_models()

Summary

Returns

Description

Return type

TYPE

train_coconut_models()

Summary

Returns

Description

Return type

TYPE

class coconut.src.CoconutClass.MidpointNormalize(vmin=None, vmax=None, vcenter=None, clip=False)

Bases: Normalize

Summary

vcenter

Description

Type

TYPE

inverse(value)

Summary

Parameters

value (TYPE) – Description

Returns

Description

Return type

TYPE

Module contents