FeatureFinderIdentificationAlgorithm.h

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// --------------------------------------------------------------------------
//                   OpenMS -- Open-Source Mass Spectrometry
// --------------------------------------------------------------------------
// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
// ETH Zurich, and Freie Universitaet Berlin 2002-2020.
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// $Maintainer: Timo Sachsenberg $
// $Authors: Hendrik Weisser $
// --------------------------------------------------------------------------
 
#ifndef OPENMS_TRANSFORMATIONS_FEATUREFINDER_FEATUREFINDERIDENTIFICATIONALGORITHM_H
#define OPENMS_TRANSFORMATIONS_FEATUREFINDER_FEATUREFINDERIDENTIFICATIONALGORITHM_H
 
#include <OpenMS/ANALYSIS/TARGETED/TargetedExperiment.h>
#include <OpenMS/ANALYSIS/MAPMATCHING/TransformationDescription.h>
#include <OpenMS/ANALYSIS/OPENSWATH/MRMFeatureFinderScoring.h>
#include <OpenMS/CONCEPT/ProgressLogger.h>
#include <OpenMS/DATASTRUCTURES/DefaultParamHandler.h>
#include <OpenMS/KERNEL/MSExperiment.h>
#include <OpenMS/TRANSFORMATIONS/FEATUREFINDER/FeatureFinderAlgorithmPickedHelperStructs.h>
 
#include <vector>
#include <fstream>
#include <map>
 
namespace OpenMS
{
  class IsotopeDistribution;
 
 
 
class OPENMS_DLLAPI FeatureFinderIdentificationAlgorithm :
  public DefaultParamHandler
{
public:
  FeatureFinderIdentificationAlgorithm(); 
 
  void run(
    std::vector<PeptideIdentification> peptides,
    const std::vector<ProteinIdentification>& proteins,
    std::vector<PeptideIdentification> peptides_ext,
    std::vector<ProteinIdentification> proteins_ext,
    FeatureMap& features,
    const FeatureMap& seeds = FeatureMap()
    );
 
  void runOnCandidates(FeatureMap& features);
 
  PeakMap& getMSData() { return ms_data_; }
  const PeakMap& getMSData() const { return ms_data_; }
 
  PeakMap& getChromatograms() { return chrom_data_; }
  const PeakMap& getChromatograms() const { return chrom_data_; }
 
  ProgressLogger& getProgressLogger() { return prog_log_; }
  const ProgressLogger& getProgressLogger() const { return prog_log_; }
 
  TargetedExperiment& getLibrary() { return library_; }
  const TargetedExperiment& getLibrary() const { return library_; }
 
protected:
  typedef FeatureFinderAlgorithmPickedHelperStructs::MassTrace MassTrace;
  typedef FeatureFinderAlgorithmPickedHelperStructs::MassTraces MassTraces;
 
  typedef std::multimap<double, PeptideIdentification*> RTMap;
  typedef std::map<Int, std::pair<RTMap, RTMap> > ChargeMap;
  typedef std::map<AASequence, ChargeMap> PeptideMap;
  typedef std::map<String, std::pair<RTMap, RTMap> > PeptideRefRTMap;
 
  PeptideMap peptide_map_;
 
  Size n_internal_peps_; 
  Size n_external_peps_; 
 
  Size batch_size_; 
  double rt_window_; 
  double mz_window_; 
  bool mz_window_ppm_; 
 
  double mapping_tolerance_; 
 
  double isotope_pmin_; 
  Size n_isotopes_; 
 
  double rt_quantile_;
 
  double peak_width_;
  double min_peak_width_;
  double signal_to_noise_;
 
  String elution_model_;
 
  // SVM related parameters
  double svm_min_prob_;
  StringList svm_predictor_names_;
  String svm_xval_out_;
  double svm_quality_cutoff;
  Size svm_n_parts_; 
  Size svm_n_samples_; 
 
  // output file (before filtering)
  String candidates_out_;
 
  Size debug_level_;
 
  void updateMembers_() override;
 
  struct RTRegion
  {
    double start, end;
    ChargeMap ids; 
  };
 
  struct FeatureFilterQuality
  {
    bool operator()(const Feature& feature)
    {
      return feature.getOverallQuality() == 0.0;
    }
  } feature_filter_quality_;
 
  struct FeatureFilterPeptides
  {
    bool operator()(const Feature& feature)
    {
      return feature.getPeptideIdentifications().empty();
    }
  } feature_filter_peptides_;
 
  struct PeptideCompare
  {
    bool operator()(const PeptideIdentification& p1,
                    const PeptideIdentification& p2)
    {
      const String& seq1 = p1.getHits()[0].getSequence().toString();
      const String& seq2 = p2.getHits()[0].getSequence().toString();
      if (seq1 == seq2)
      {
        Int charge1 = p1.getHits()[0].getCharge();
        Int charge2 = p2.getHits()[0].getCharge();
        if (charge1 == charge2)
        {
          return p1.getRT() < p2.getRT();
        }
        return charge1 < charge2;
      }
      return seq1 < seq2;
    }
  } peptide_compare_;
 
  struct FeatureCompare
  {
    bool operator()(const Feature& f1, const Feature& f2)
    {
      const String& ref1 = f1.getMetaValue("PeptideRef");
      const String& ref2 = f2.getMetaValue("PeptideRef");
      if (ref1 == ref2)
      {
        return f1.getRT() < f2.getRT();
      }
      return ref1 < ref2;
    }
  } feature_compare_;
 
  PeakMap ms_data_; 
  PeakMap chrom_data_; 
  TargetedExperiment library_; 
 
  std::map<double, std::pair<Size, Size> > svm_probs_internal_;
  std::multiset<double> svm_probs_external_;
  Size n_internal_features_; 
  Size n_external_features_; 
  TransformationDescription trafo_external_; 
  std::map<String, double> isotope_probs_; 
  MRMFeatureFinderScoring feat_finder_; 
 
  ProgressLogger prog_log_;
 
  void generateTransitions_(const String& peptide_id, double mz, Int charge,
                            const IsotopeDistribution& iso_dist);
 
  void addPeptideRT_(TargetedExperiment::Peptide& peptide, double rt) const;
 
  void getRTRegions_(ChargeMap& peptide_data, std::vector<RTRegion>& rt_regions) const;
 
  void annotateFeaturesFinalizeAssay_(
    FeatureMap& features,
    std::map<Size, std::vector<PeptideIdentification*> >& feat_ids,
    RTMap& rt_internal);
 
  void annotateFeatures_(FeatureMap& features, PeptideRefRTMap& ref_rt_map);
 
  void ensureConvexHulls_(Feature& feature);
 
  void postProcess_(FeatureMap& features, bool with_external_ids);
 
  void statistics_(const FeatureMap& features) const;
 
  void createAssayLibrary_(const PeptideMap::iterator& begin, const PeptideMap::iterator& end, PeptideRefRTMap& ref_rt_map);
 
  void addPeptideToMap_(PeptideIdentification& peptide, 
    PeptideMap& peptide_map,
    bool external = false) const;
 
  void checkNumObservations_(Size n_pos, Size n_neg, const String& note = "") const;
 
  void getUnbiasedSample_(const std::multimap<double, std::pair<Size, bool> >& valid_obs,
                          std::map<Size, Int>& training_labels);
 
  void getRandomSample_(std::map<Size, Int>& training_labels);
 
  void classifyFeatures_(FeatureMap& features);
 
  void filterFeaturesFinalizeAssay_(Feature& best_feature, double best_quality,
                                    const double quality_cutoff);
 
  void filterFeatures_(FeatureMap& features, bool classified);
 
  void calculateFDR_(FeatureMap& features);
 
  template <typename It>
  std::vector<std::pair<It,It>>
  chunk_(It range_from, It range_to, const std::ptrdiff_t batch_size)
  {
    /* Aliases, to make the rest of the code more readable. */
    using std::vector;
    using std::pair;
    using std::make_pair;
    using std::distance;
    using diff_t = std::ptrdiff_t;
 
    /* Total item number and batch_size size. */
    const diff_t total {distance(range_from, range_to)};
    const diff_t num {total / batch_size};
 
    vector<pair<It,It>> chunks(num);
 
    It batch_end {range_from};
 
    /* Use the 'generate' algorithm to create batches. */
    std::generate(begin(chunks), end(chunks), [&batch_end, batch_size]()
    {
      It batch_start {batch_end };
 
      std::advance(batch_end, batch_size);
      return make_pair(batch_start, batch_end);
    });
 
    /* The last batch_size's end must always be 'range_to'. */
    if (chunks.empty())
    {
      chunks.emplace_back(range_from, range_to);
    }
    else
    {
      chunks.back().second = range_to;
    }
 
    return chunks;
  }
};
 
} // namespace OpenMS
 
#endif