35 #ifndef OPENMS_ANALYSIS_OPENSWATH_CONFIDENCESCORING_H 36 #define OPENMS_ANALYSIS_OPENSWATH_CONFIDENCESCORING_H 41 #include <boost/bimap.hpp> 42 #include <boost/bimap/multiset_of.hpp> 43 #include <boost/random/uniform_int.hpp> 44 #include <boost/random/mersenne_twister.hpp> 45 #include <boost/random/variate_generator.hpp> 65 generator_(), rand_gen_(generator_,
boost::uniform_int<>())
67 if (!test_mode_) rand_gen_.engine().seed(time(0));
75 typedef boost::bimap<double, boost::bimaps::multiset_of<double> >
85 double operator()(
double diff_rt,
double dist_int)
87 double lm = intercept + rt_coef * diff_rt * diff_rt +
89 return 1.0 / (1.0 + exp(-lm));
99 double operator()(
double rt)
101 return (rt - min_rt) / (max_rt - min_rt) * 100;
121 boost::variate_generator<boost::mt19937&, boost::uniform_int<> >
rand_gen_;
124 void chooseDecoys_();
131 const String& cv_accession =
"MS:1000896");
135 void extractIntensities_(
BimapType& intensity_map,
Size n_transitions,
142 double feature_rt,
DoubleList& feature_intensities,
143 const std::set<String>& transition_ids = std::set<String>());
146 void scoreFeature_(
Feature& feature);
153 n_decoys_ = n_decoys;
154 n_transitions_ = n_transitions;
155 rt_trafo_ = rt_trafo;
160 glm_.intercept = intercept;
161 glm_.rt_coef = rt_coef;
162 glm_.int_coef = int_coef;
184 "There need to be at least 2 assays in the library for ConfidenceScoring.");
187 if (n_assays - 1 < n_decoys_)
189 LOG_WARN <<
"Warning: Parameter 'decoys' (" << n_decoys_
190 <<
") is higher than the number of unrelated assays in the " 191 <<
"library (" << n_assays - 1 <<
"). " 192 <<
"Using all unrelated assays as decoys." << std::endl;
194 if (n_assays - 1 <= n_decoys_) n_decoys_ = 0;
196 decoy_index_.resize(n_assays);
197 for (
Size i = 0; i < n_assays; ++i) decoy_index_[i] = boost::numeric_cast<Int>(i);
200 LOG_DEBUG <<
"Building transition map..." << std::endl;
204 transition_map_[ref].push_back(boost::numeric_cast<Int>(i));
207 LOG_DEBUG <<
"Determining retention time range..." << std::endl;
208 rt_norm_.min_rt = std::numeric_limits<double>::infinity();
209 rt_norm_.max_rt = -std::numeric_limits<double>::infinity();
210 for (std::vector<TargetedExperiment::Peptide>::const_iterator it =
214 double current_rt = getAssayRT_(*it);
215 if (current_rt == -1.0)
continue;
216 rt_norm_.min_rt = std::min(rt_norm_.min_rt, current_rt);
217 rt_norm_.max_rt = std::max(rt_norm_.max_rt, current_rt);
221 LOG_DEBUG <<
"Scoring features..." << std::endl;
222 startProgress(0, features.size(),
"scoring features");
225 feat_it != features.end(); ++feat_it)
227 LOG_DEBUG <<
"Feature " << feat_it - features.begin() + 1
228 <<
" (ID '" << feat_it->
getUniqueId() <<
"')"<< std::endl;
229 scoreFeature_(*feat_it);
230 setProgress(feat_it - features.begin());
240 #endif // OPENMS_ANALYSIS_OPENSWATH_CONFIDENCESCORING double min_rt
Definition: ConfidenceScoring.h:96
A more convenient string class.
Definition: String.h:57
void initializeGlm(double intercept, double rt_coef, double int_coef)
Definition: ConfidenceScoring.h:158
virtual ~ConfidenceScoring()
Definition: ConfidenceScoring.h:70
std::vector< double > DoubleList
Vector of double precision real types.
Definition: ListUtils.h:66
A container for features.
Definition: FeatureMap.h:93
void scoreMap(FeatureMap &features)
Score a feature map -> make sure the class is properly initialized.
Definition: ConfidenceScoring.h:177
std::vector< Int > IntList
Vector of signed integers.
Definition: ListUtils.h:59
Map< String, IntList > transition_map_
Definition: ConfidenceScoring.h:111
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:47
#define LOG_DEBUG
Macro for general debugging information.
Definition: LogStream.h:459
#define LOG_WARN
Macro if a warning, a piece of information which should be read by the user, should be logged...
Definition: LogStream.h:451
TargetedExperiment library_
Definition: ConfidenceScoring.h:105
TransformationDescription rt_trafo_
RT transformation to map measured RTs to assay RTs.
Definition: ConfidenceScoring.h:116
boost::mt19937 generator_
Definition: ConfidenceScoring.h:118
double int_coef
Definition: ConfidenceScoring.h:83
A method or algorithm argument contains illegal values.
Definition: Exception.h:634
boost::bimap< double, boost::bimaps::multiset_of< double > > BimapType
Mapping: Q3 m/z <-> transition intensity (maybe not unique!)
Definition: ConfidenceScoring.h:76
ConfidenceScoring(bool test_mode_=false)
Constructor.
Definition: ConfidenceScoring.h:64
const std::vector< ReactionMonitoringTransition > & getTransitions() const
returns the transition list
Base::iterator Iterator
Definition: FeatureMap.h:136
double max_rt
Definition: ConfidenceScoring.h:97
IntList decoy_index_
Definition: ConfidenceScoring.h:107
An LC-MS feature.
Definition: Feature.h:70
void initialize(TargetedExperiment library, Size n_decoys, Size n_transitions, TransformationDescription rt_trafo)
Definition: ConfidenceScoring.h:150
Definition: ConfidenceScoring.h:58
double intercept
Definition: ConfidenceScoring.h:81
double rt_coef
Definition: ConfidenceScoring.h:82
Size n_decoys_
Definition: ConfidenceScoring.h:109
Size n_transitions_
Definition: ConfidenceScoring.h:113
Base class for all classes that want to report their progress.
Definition: ProgressLogger.h:55
This class stores an prediction of an SRM/MRM transition.
Definition: TargetedExperiment.h:53
boost::variate_generator< boost::mt19937 &, boost::uniform_int<> > rand_gen_
Random number generator (must be initialized in init. list of c'tor!)
Definition: ConfidenceScoring.h:121
const std::vector< Peptide > & getPeptides() const
Map class based on the STL map (containing several convenience functions)
Definition: Map.h:51
UInt64 getUniqueId() const
Non-mutable access to unique id - returns the unique id.
Definition: UniqueIdInterface.h:110
Definition: TargetedExperimentHelper.h:211