OpenMS  2.7.0
AbsoluteQuantitation.h
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31 // $Maintainer: Douglas McCloskey, Pasquale Domenico Colaianni $
32 // $Authors: Douglas McCloskey, Pasquale Domenico Colaianni $
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34 
35 #pragma once
36 
37 #include <OpenMS/config.h>
38 
39 //Kernal classes
47 
48 //Analysis classes
52 
53 //Quantitation classes
56 
57 
58 //Standard library
59 #include <cstddef> // for size_t & ptrdiff_t
60 #include <vector>
61 #include <string>
62 
63 namespace OpenMS
64 {
65 
84  class OPENMS_DLLAPI AbsoluteQuantitation :
85  public DefaultParamHandler
86  {
87 
88 public:
92 
96 
103  void setQuantMethods(std::vector<AbsoluteQuantitationMethod>& quant_methods);
104 
105 
109  std::vector<AbsoluteQuantitationMethod> getQuantMethods();
110  std::map<String, AbsoluteQuantitationMethod> getQuantMethodsAsMap();
111 
124  double calculateRatio(const Feature & component_1, const Feature & component_2, const String & feature_name);
125 
142  double calculateBias(const double & actual_concentration, const double & calculated_concentration);
143 
156  Param fitCalibration(const std::vector<AbsoluteQuantitationStandards::featureConcentration> & component_concentrations,
157  const String & feature_name,
158  const String & transformation_model,
159  const Param & transformation_model_params);
160 
174  const std::vector<AbsoluteQuantitationStandards::featureConcentration> & component_concentrations,
175  const String & feature_name,
176  const String & transformation_model,
177  const Param & transformation_model_params,
178  std::vector<double> & biases,
179  double & correlation_coefficient);
180 
197  std::vector<AbsoluteQuantitationStandards::featureConcentration> & component_concentrations,
198  const String & feature_name,
199  const String & transformation_model,
200  const Param & transformation_model_params,
201  Param & optimized_params);
202 
212  void optimizeCalibrationCurves(std::map<String,std::vector<AbsoluteQuantitationStandards::featureConcentration>> & components_concentrations);
213 
224  const String& component_name,
225  std::vector<AbsoluteQuantitationStandards::featureConcentration>& component_concentrations
226  );
227 
242  double applyCalibration(const Feature & component,
243  const Feature & IS_component,
244  const String & feature_name,
245  const String & transformation_model,
246  const Param & transformation_model_params);
247 
262 
263 protected:
274  std::vector<AbsoluteQuantitationStandards::featureConcentration> extractComponents_(
275  const std::vector<AbsoluteQuantitationStandards::featureConcentration> & component_concentrations,
276  const std::vector<size_t>& component_concentrations_indices);
277 
293  const std::vector<AbsoluteQuantitationStandards::featureConcentration>& component_concentrations,
294  const String & feature_name,
295  const String & transformation_model,
296  const Param & transformation_model_params);
297 
313  const std::vector<AbsoluteQuantitationStandards::featureConcentration>& component_concentrations,
314  const String & feature_name,
315  const String & transformation_model,
316  const Param & transformation_model_params);
317 
318 private:
321 
322  size_t min_points_;
323  double max_bias_;
325  size_t max_iters_;
329 
330  // members
332  std::map<String, AbsoluteQuantitationMethod> quant_methods_;
333 
334  };
335 
336 }
337 
AbsoluteQuantitation is a class to support absolute or relative quantitation for targeted or untarget...
Definition: AbsoluteQuantitation.h:86
int jackknifeOutlierCandidate_(const std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations, const String &feature_name, const String &transformation_model, const Param &transformation_model_params)
This function computes a candidate outlier point by iteratively leaving one point out to find the one...
double calculateBias(const double &actual_concentration, const double &calculated_concentration)
This function calculates the bias of the calibration.
size_t max_iters_
Definition: AbsoluteQuantitation.h:325
double applyCalibration(const Feature &component, const Feature &IS_component, const String &feature_name, const String &transformation_model, const Param &transformation_model_params)
This function applies the calibration curve to the component.
double max_bias_
Definition: AbsoluteQuantitation.h:323
size_t min_points_
Definition: AbsoluteQuantitation.h:322
String outlier_detection_method_
Definition: AbsoluteQuantitation.h:326
Param fitCalibration(const std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations, const String &feature_name, const String &transformation_model, const Param &transformation_model_params)
This function fits the calibration points to the model.
String optimization_method_
Definition: AbsoluteQuantitation.h:328
double min_correlation_coefficient_
Definition: AbsoluteQuantitation.h:324
int residualOutlierCandidate_(const std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations, const String &feature_name, const String &transformation_model, const Param &transformation_model_params)
This function computes a candidate outlier point by computing the residuals of all points to the line...
void optimizeSingleCalibrationCurve(const String &component_name, std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations)
This function optimizes the parameters of the calibration for a single component.
std::map< String, AbsoluteQuantitationMethod > getQuantMethodsAsMap()
void setQuantMethods(std::vector< AbsoluteQuantitationMethod > &quant_methods)
quant_method setter. A list of AbsoluteQuantitationMethod classes are given as input and a map is con...
void optimizeCalibrationCurves(std::map< String, std::vector< AbsoluteQuantitationStandards::featureConcentration >> &components_concentrations)
This function optimizes the parameters of the calibration for a all components.
double calculateRatio(const Feature &component_1, const Feature &component_2, const String &feature_name)
This function calculates the ratio between features.
std::vector< AbsoluteQuantitationStandards::featureConcentration > extractComponents_(const std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations, const std::vector< size_t > &component_concentrations_indices)
This function extracts out the components.
void calculateBiasAndR(const std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations, const String &feature_name, const String &transformation_model, const Param &transformation_model_params, std::vector< double > &biases, double &correlation_coefficient)
This function calculates the biases and the correlation coefficient of the calibration points.
void updateMembers_()
Synchronize members with param class.
std::map< String, AbsoluteQuantitationMethod > quant_methods_
map between components and quantitation methods
Definition: AbsoluteQuantitation.h:332
~AbsoluteQuantitation()
Destructor.
void quantifyComponents(FeatureMap &unknowns)
This function applies the calibration curve to all components.
bool use_chauvenet_
Definition: AbsoluteQuantitation.h:327
bool optimizeCalibrationCurveIterative(std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations, const String &feature_name, const String &transformation_model, const Param &transformation_model_params, Param &optimized_params)
This function optimizes the parameters of the calibration for a given component iteratively.
std::vector< AbsoluteQuantitationMethod > getQuantMethods()
quant_method getter. A list of AbsoluteQuantitationMethod classes are returned.
A base class for all classes handling default parameters.
Definition: DefaultParamHandler.h:93
A container for features.
Definition: FeatureMap.h:105
An LC-MS feature.
Definition: Feature.h:72
Management and storage of parameters / INI files.
Definition: Param.h:70
A more convenient string class.
Definition: String.h:61
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:47