OpenMS  3.0.0
PosteriorErrorProbabilityModel.h
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31 // $Maintainer: Timo Sachsenberg $
32 // $Authors: David Wojnar $
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34 
35 #pragma once
36 
43 
44 #include <vector>
45 #include <map>
46 
47 namespace OpenMS
48 {
49  class String;
50  class TextFile;
51  class PeptideIdentification;
52  class ProteinIdentification;
53  class PeptideHit;
54  namespace Math
55  {
56 
57 
74  class OPENMS_DLLAPI PosteriorErrorProbabilityModel :
75  public DefaultParamHandler
76  {
77 public:
78 
81 
84 
96  static std::map<String, std::vector<std::vector<double>>> extractAndTransformScores(
97  const std::vector<ProteinIdentification> & protein_ids,
98  const std::vector<PeptideIdentification> & peptide_ids,
99  const bool split_charge,
100  const bool top_hits_only,
101  const bool target_decoy_available,
102  const double fdr_for_targets_smaller);
103 
117  static void updateScores(
118  const PosteriorErrorProbabilityModel & PEP_model,
119  const String & search_engine,
120  const Int charge,
121  const bool prob_correct,
122  const bool split_charge,
123  std::vector<ProteinIdentification> & protein_ids,
124  std::vector<PeptideIdentification> & peptide_ids,
125  bool & unable_to_fit_data,
126  bool & data_might_not_be_well_fit);
127 
136  bool fit(std::vector<double> & search_engine_scores, const String& outlier_handling);
137 
146  bool fitGumbelGauss(std::vector<double>& search_engine_scores, const String& outlier_handling);
147 
155  bool fit(std::vector<double> & search_engine_scores, std::vector<double> & probabilities, const String& outlier_handling);
156 
158  void fillDensities(const std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density);
160  void fillLogDensities(const std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density);
162  void fillLogDensitiesGumbel(const std::vector<double> & x_scores, std::vector<double> & incorrect_density, std::vector<double> & correct_density);
164  double computeLogLikelihood(const std::vector<double> & incorrect_density, const std::vector<double> & correct_density) const;
165 
170  double computeLLAndIncorrectPosteriorsFromLogDensities(
171  const std::vector<double>& incorrect_log_density,
172  const std::vector<double>& correct_log_density,
173  std::vector<double>& incorrect_posterior) const;
174 
181  std::pair<double, double> pos_neg_mean_weighted_posteriors(const std::vector<double> &x_scores,
182  const std::vector<double> &incorrect_posteriors);
183 
190  std::pair<double, double> pos_neg_sigma_weighted_posteriors(const std::vector<double> &x_scores,
191  const std::vector<double> &incorrect_posteriors,
192  const std::pair<double, double>& means);
193 
196  {
197  return correctly_assigned_fit_param_;
198  }
199 
202  {
203  return incorrectly_assigned_fit_param_;
204  }
205 
208  {
209  return incorrectly_assigned_fit_gumbel_param_;
210  }
211 
213  double getNegativePrior() const
214  {
215  return negative_prior_;
216  }
217 
219  static double getGumbel_(double x, const GaussFitter::GaussFitResult & params)
220  {
221  double z = exp((params.x0 - x) / params.sigma);
222  return (z * exp(-1 * z)) / params.sigma;
223  }
224 
229  double computeProbability(double score) const;
230 
232  TextFile initPlots(std::vector<double> & x_scores);
233 
235  const String getGumbelGnuplotFormula(const GaussFitter::GaussFitResult & params) const;
236 
238  const String getGaussGnuplotFormula(const GaussFitter::GaussFitResult & params) const;
239 
241  const String getBothGnuplotFormula(const GaussFitter::GaussFitResult & incorrect, const GaussFitter::GaussFitResult & correct) const;
242 
244  void plotTargetDecoyEstimation(std::vector<double> & target, std::vector<double> & decoy);
245 
247  inline double getSmallestScore() const
248  {
249  return smallest_score_;
250  }
251 
253  void tryGnuplot(const String& gp_file);
254 
255 private:
257  void processOutliers_(std::vector<double>& x_scores, const String& outlier_handling) const;
258 
263  static double transformScore_(const String& engine, const PeptideHit& hit, const String& current_score_type);
264 
269  static double getScore_(const std::vector<String>& requested_score_types, const PeptideHit & hit, const String& actual_score_type);
270 
289  const String (PosteriorErrorProbabilityModel::* getNegativeGnuplotFormula_)(const GaussFitter::GaussFitResult & params) const;
291  const String (PosteriorErrorProbabilityModel::* getPositiveGnuplotFormula_)(const GaussFitter::GaussFitResult & params) const;
292  };
293  }
294 }
295 
DefaultParamHandler.h
GumbelMaxLikelihoodFitter.h
OpenMS::Math::GumbelMaxLikelihoodFitter::GumbelDistributionFitResult
struct to represent the parameters of a gumbel distribution
Definition: GumbelMaxLikelihoodFitter.h:63
DPosition.h
GaussFitter.h
OpenMS::Math::PosteriorErrorProbabilityModel::getIncorrectlyAssignedGumbelFitResult
GumbelMaxLikelihoodFitter::GumbelDistributionFitResult getIncorrectlyAssignedGumbelFitResult() const
returns estimated parameters for correctly assigned sequences. Fit should be used before.
Definition: PosteriorErrorProbabilityModel.h:207
OpenMS::Math::GaussFitter::GaussFitResult
struct of parameters of a Gaussian distribution
Definition: GaussFitter.h:65
OpenMS::String
A more convenient string class.
Definition: String.h:58
GumbelDistributionFitter.h
OpenMS::TextFile
This class provides some basic file handling methods for text files.
Definition: TextFile.h:46
OpenMS::Math::PosteriorErrorProbabilityModel::incorrectly_assigned_fit_param_
GaussFitter::GaussFitResult incorrectly_assigned_fit_param_
stores parameters for incorrectly assigned sequences. If gumbel fit was used, A can be ignored....
Definition: PosteriorErrorProbabilityModel.h:276
OpenMS::Math::PosteriorErrorProbabilityModel::correctly_assigned_fit_param_
GaussFitter::GaussFitResult correctly_assigned_fit_param_
stores gauss parameters
Definition: PosteriorErrorProbabilityModel.h:279
ListUtils.h
OpenMS::Math::PosteriorErrorProbabilityModel::max_correctly_
double max_correctly_
peak of the gauss distribution (correctly assigned sequences)
Definition: PosteriorErrorProbabilityModel.h:285
OpenMS::DefaultParamHandler
A base class for all classes handling default parameters.
Definition: DefaultParamHandler.h:92
OpenMS::Int
int Int
Signed integer type.
Definition: Types.h:102
OpenMS
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:47
OpenMS::Math::PosteriorErrorProbabilityModel::getNegativePrior
double getNegativePrior() const
returns the estimated negative prior probability.
Definition: PosteriorErrorProbabilityModel.h:213
OpenMS::Math::GaussFitter::GaussFitResult::sigma
double sigma
parameter sigma of Gaussian distribution (width)
Definition: GaussFitter.h:80
OpenMS::Math::PosteriorErrorProbabilityModel::getCorrectlyAssignedFitResult
GaussFitter::GaussFitResult getCorrectlyAssignedFitResult() const
returns estimated parameters for correctly assigned sequences. Fit should be used before.
Definition: PosteriorErrorProbabilityModel.h:195
OpenMS::Math::GaussFitter::GaussFitResult::x0
double x0
parameter x0 of Gaussian distribution (center position)
Definition: GaussFitter.h:77
OpenMS::Math::PosteriorErrorProbabilityModel::negative_prior_
double negative_prior_
stores final prior probability for negative peptides
Definition: PosteriorErrorProbabilityModel.h:281
OpenMS::Math::PosteriorErrorProbabilityModel::max_incorrectly_
double max_incorrectly_
peak of the incorrectly assigned sequences distribution
Definition: PosteriorErrorProbabilityModel.h:283
OpenMS::Math::PosteriorErrorProbabilityModel::smallest_score_
double smallest_score_
smallest score which was used for fitting the model
Definition: PosteriorErrorProbabilityModel.h:287
OpenMS::Math::PosteriorErrorProbabilityModel::incorrectly_assigned_fit_gumbel_param_
GumbelMaxLikelihoodFitter::GumbelDistributionFitResult incorrectly_assigned_fit_gumbel_param_
Definition: PosteriorErrorProbabilityModel.h:277
OpenMS::Math::PosteriorErrorProbabilityModel
Implements a mixture model of the inverse gumbel and the gauss distribution or a gaussian mixture.
Definition: PosteriorErrorProbabilityModel.h:74
OpenMS::Math::PosteriorErrorProbabilityModel::getGumbel_
static double getGumbel_(double x, const GaussFitter::GaussFitResult &params)
computes the gumbel density at position x with parameters params.
Definition: PosteriorErrorProbabilityModel.h:219
OpenMS::Math::PosteriorErrorProbabilityModel::getSmallestScore
double getSmallestScore() const
returns the smallest score used in the last fit
Definition: PosteriorErrorProbabilityModel.h:247
OpenMS::Math::PosteriorErrorProbabilityModel::getIncorrectlyAssignedFitResult
GaussFitter::GaussFitResult getIncorrectlyAssignedFitResult() const
returns estimated parameters for correctly assigned sequences. Fit should be used before.
Definition: PosteriorErrorProbabilityModel.h:201
OpenMS::PeptideHit
Representation of a peptide hit.
Definition: PeptideHit.h:55