AbsoluteQuantitation.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.
//
// This software is released under a three-clause BSD license:
//  * Redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
//  * Redistributions in binary form must reproduce the above copyright
//    notice, this list of conditions and the following disclaimer in the
//    documentation and/or other materials provided with the distribution.
//  * Neither the name of any author or any participating institution
//    may be used to endorse or promote products derived from this software
//    without specific prior written permission.
// For a full list of authors, refer to the file AUTHORS.
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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// --------------------------------------------------------------------------
// $Maintainer: Douglas McCloskey, Pasquale Domenico Colaianni $
// $Authors: Douglas McCloskey, Pasquale Domenico Colaianni $
// --------------------------------------------------------------------------
 
#pragma once
 
#include <OpenMS/config.h>
 
//Kernal classes
#include <OpenMS/DATASTRUCTURES/DefaultParamHandler.h>
#include <OpenMS/KERNEL/StandardTypes.h>
#include <OpenMS/KERNEL/MSExperiment.h>
#include <OpenMS/KERNEL/MSChromatogram.h>
#include <OpenMS/KERNEL/FeatureMap.h>
#include <OpenMS/KERNEL/MRMTransitionGroup.h>
#include <OpenMS/KERNEL/MRMFeature.h>
 
//Analysis classes
#include <OpenMS/ANALYSIS/MAPMATCHING/TransformationDescription.h>
#include <OpenMS/ANALYSIS/MAPMATCHING/TransformationModel.h>
#include <OpenMS/ANALYSIS/TARGETED/TargetedExperiment.h>
 
//Quantitation classes
#include <OpenMS/METADATA/AbsoluteQuantitationStandards.h>
#include <OpenMS/ANALYSIS/QUANTITATION/AbsoluteQuantitationMethod.h>
 
 
//Standard library
#include <cstddef> // for size_t & ptrdiff_t
#include <vector>
#include <string>
 
namespace OpenMS
{
 
  class OPENMS_DLLAPI AbsoluteQuantitation :
    public DefaultParamHandler
  {
 
public:    
    AbsoluteQuantitation();
 
    ~AbsoluteQuantitation();
 
    void setQuantMethods(std::vector<AbsoluteQuantitationMethod>& quant_methods);
 
 
    std::vector<AbsoluteQuantitationMethod> getQuantMethods();
    std::map<String, AbsoluteQuantitationMethod> getQuantMethodsAsMap();
 
    double calculateRatio(const Feature & component_1, const Feature & component_2, const String & feature_name);
                   
    double calculateBias(const double & actual_concentration, const double & calculated_concentration);
            
    Param fitCalibration(const std::vector<AbsoluteQuantitationStandards::featureConcentration> & component_concentrations,
      const String & feature_name,
      const String & transformation_model,
      const Param & transformation_model_params);
      
    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);
      
    bool optimizeCalibrationCurveIterative(
      std::vector<AbsoluteQuantitationStandards::featureConcentration> & component_concentrations,
      const String & feature_name,
      const String & transformation_model,
      const Param & transformation_model_params,
      Param & optimized_params);
        
    void optimizeCalibrationCurves(std::map<String,std::vector<AbsoluteQuantitationStandards::featureConcentration>> & components_concentrations);    
 
    void optimizeSingleCalibrationCurve(
      const String& component_name,
      std::vector<AbsoluteQuantitationStandards::featureConcentration>& component_concentrations
    );
 
    double applyCalibration(const Feature & component,
      const Feature & IS_component,
      const String & feature_name,
      const String & transformation_model,
      const Param & transformation_model_params);     
      
    void quantifyComponents(FeatureMap& unknowns);    
 
protected:
    std::vector<AbsoluteQuantitationStandards::featureConcentration> extractComponents_(
      const std::vector<AbsoluteQuantitationStandards::featureConcentration> & component_concentrations,
      const std::vector<size_t>& component_concentrations_indices);
  
    int jackknifeOutlierCandidate_(
      const std::vector<AbsoluteQuantitationStandards::featureConcentration>& component_concentrations,
      const String & feature_name,
      const String & transformation_model,
      const Param & transformation_model_params);
 
    int residualOutlierCandidate_(
      const std::vector<AbsoluteQuantitationStandards::featureConcentration>& component_concentrations,
      const String & feature_name,
      const String & transformation_model,
      const Param & transformation_model_params);
     
private:  
    void updateMembers_();
    
    size_t min_points_;
    double max_bias_;
    double min_correlation_coefficient_; 
    size_t max_iters_;
    String outlier_detection_method_;
    bool use_chauvenet_;
    String optimization_method_;
    
    // members
    std::map<String, AbsoluteQuantitationMethod> quant_methods_;
 
  };
 
}