AbsoluteQuantitation is a class to support absolute or relative quantitation for targeted or untargeted quantitation workflows (e.g., Isotope Dilution Mass Spectrometry). More...

#include <OpenMS/ANALYSIS/QUANTITATION/AbsoluteQuantitation.h>

Inheritance diagram for AbsoluteQuantitation:

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Collaboration diagram for AbsoluteQuantitation:

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Public Member Functions
	AbsoluteQuantitation ()
	Constructor. More...

	~AbsoluteQuantitation () override
	Destructor. More...

void	setQuantMethods (std::vector< AbsoluteQuantitationMethod > &quant_methods)
	quant_method setter. A list of AbsoluteQuantitationMethod classes are given as input and a map is constructed based on their component_name member. More...

std::vector< AbsoluteQuantitationMethod >	getQuantMethods ()
	quant_method getter. A list of AbsoluteQuantitationMethod classes are returned. More...

std::map< String, AbsoluteQuantitationMethod >	getQuantMethodsAsMap ()

double	calculateRatio (const Feature &component_1, const Feature &component_2, const String &feature_name)
	This function calculates the ratio between features. More...

double	calculateBias (const double &actual_concentration, const double &calculated_concentration)
	This function calculates the bias of the calibration. More...

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. More...

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. More...

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. More...

void	optimizeCalibrationCurves (std::map< String, std::vector< AbsoluteQuantitationStandards::featureConcentration >> &components_concentrations)
	This function optimizes the parameters of the calibration for a all components. More...

void	optimizeSingleCalibrationCurve (const String &component_name, std::vector< AbsoluteQuantitationStandards::featureConcentration > &component_concentrations)
	This function optimizes the parameters of the calibration for a single component. More...

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. More...

void	quantifyComponents (FeatureMap &unknowns)
	This function applies the calibration curve to all components. More...

Public Member Functions inherited from DefaultParamHandler
	DefaultParamHandler (const String &name)
	Constructor with name that is displayed in error messages. More...

	DefaultParamHandler (const DefaultParamHandler &rhs)
	Copy constructor. More...

virtual	~DefaultParamHandler ()
	Destructor. More...

virtual DefaultParamHandler &	operator= (const DefaultParamHandler &rhs)
	Assignment operator. More...

virtual bool	operator== (const DefaultParamHandler &rhs) const
	Equality operator. More...

void	setParameters (const Param &param)
	Sets the parameters. More...

const Param &	getParameters () const
	Non-mutable access to the parameters. More...

const Param &	getDefaults () const
	Non-mutable access to the default parameters. More...

const String &	getName () const
	Non-mutable access to the name. More...

void	setName (const String &name)
	Mutable access to the name. More...

const std::vector< String > &	getSubsections () const
	Non-mutable access to the registered subsections. More...

Protected Member Functions
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. More...

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 which results in the maximum R^2 of a first order linear regression of the remaining ones. More...

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 linear fit and selecting the one with the largest deviation. More...

Protected Member Functions inherited from DefaultParamHandler
void	defaultsToParam_ ()
	Updates the parameters after the defaults have been set in the constructor. More...

Private Member Functions
void	updateMembers_ () override
	Synchronize members with param class. More...

Private Attributes
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_

std::map< String, AbsoluteQuantitationMethod >	quant_methods_
	map between components and quantitation methods More...

Additional Inherited Members
Static Public Member Functions inherited from DefaultParamHandler
static void	writeParametersToMetaValues (const Param &write_this, MetaInfoInterface &write_here, const String &key_prefix="")
	Writes all parameters to meta values. More...

Protected Attributes inherited from DefaultParamHandler
Param	param_
	Container for current parameters. More...

Param	defaults_
	Container for default parameters. This member should be filled in the constructor of derived classes! More...

std::vector< String >	subsections_
	Container for registered subsections. This member should be filled in the constructor of derived classes! More...

String	error_name_
	Name that is displayed in error messages during the parameter checking. More...

bool	check_defaults_
	If this member is set to false no checking if parameters in done;. More...

bool	warn_empty_defaults_
	If this member is set to false no warning is emitted when defaults are empty;. More...

Detailed Description

AbsoluteQuantitation is a class to support absolute or relative quantitation for targeted or untargeted quantitation workflows (e.g., Isotope Dilution Mass Spectrometry).

Method: A transformation model where y = ratio (analyte/IS) corresponding to peak height or peak area and x = ratio (analyte/IS) corresponding to concentration is used to fit a series of runs with standards of known concentrations that span the detection range of the instrument. The fitted transformation model can then be used to quantify the concentration of an analyte in an unknown sample given the analyte peak height or area, IS peak height or area, and IS concentration.

Terms: component: A protein, peptide, or compound fragment, transition, or whole species that is measured by e.g., LC-MS, LC-MS/MS, GC-MS, GC-MS/MS, LC-MS-TOF, HPLC-UV, HPLC-IR, etc. calibration curve: A series of standards that are used to correlate instrument measurements to actual concentrations

Constructor & Destructor Documentation

◆ AbsoluteQuantitation()

AbsoluteQuantitation ( )

Constructor.

◆ ~AbsoluteQuantitation()

~AbsoluteQuantitation ( )

override

Destructor.

Member Function Documentation

◆ applyCalibration()

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.

Parameters

component	the component to be quantified
IS_component	the internal standard (IS) of the component to be quantified. This can be an empty feature if there is no IS for the component.
feature_name	name of the feature to calculate the absolute concentration.
transformation_model	model used to fit the calibration points
transformation_model_params	parameters used by the transformation_model

Returns: The absolute concentration.

Exceptions

Exception::UnableToFit

◆ calculateBias()

double calculateBias	(	const double &	actual_concentration,
		const double &	calculated_concentration
	)

This function calculates the bias of the calibration.

The bias is defined as the following: |actual_concentration - calculated_concentration|/actual_concentration * 100% This is in contrast to accuracy, which is defined as the following: calculated_concentration/actual_concentration * 100%

Parameters

actual_concentration	the actual concentration of the component
calculated_concentration	the calibration curve back calculated concentration of the component

Returns: The bias.

Exceptions

Exception::UnableToFit

◆ calculateBiasAndR()

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.

Parameters

component_concentrations	list of structures with features and concentrations
feature_name	name of the feature to calculate the absolute concentration.
transformation_model	model used to fit the calibration points
transformation_model_params	parameters used by the transformation_model
biases	Vector of point biases
correlation_coefficient	Pearson's R

Exceptions

None

◆ calculateRatio()

double calculateRatio	(	const Feature &	component_1,
		const Feature &	component_2,
		const String &	feature_name
	)

This function calculates the ratio between features.

Parameters

component_1	component of the numerator
component_2	component of the denominator
feature_name	name of the feature to calculate the ratio on e.g., peak_apex, peak_area

Returns: The ratio.

Exceptions

Exception::UnableToFit

◆ extractComponents_()

std::vector<AbsoluteQuantitationStandards::featureConcentration> extractComponents_	(	const std::vector< AbsoluteQuantitationStandards::featureConcentration > &	component_concentrations,
		const std::vector< size_t > &	component_concentrations_indices
	)

protected

This function extracts out the components.

Parameters

component_concentrations	list of structures with features and concentrations
component_concentrations_indices	indices to extract out

Returns: component_concentrations_sub sublist of structures with features and concentrations.

Exceptions

None

◆ fitCalibration()

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.

Parameters

component_concentrations	list of structures with features and concentrations
feature_name	name of the feature to calculate the absolute concentration.
transformation_model	model used to fit the calibration points
transformation_model_params	parameters used by the transformation_model

Returns: updated Param object

Exceptions

Exception::UnableToFit

◆ getQuantMethods()

std::vector<AbsoluteQuantitationMethod> getQuantMethods ( )

quant_method getter. A list of AbsoluteQuantitationMethod classes are returned.

◆ getQuantMethodsAsMap()

std::map<String, AbsoluteQuantitationMethod> getQuantMethodsAsMap ( )

◆ jackknifeOutlierCandidate_()

int jackknifeOutlierCandidate_	(	const std::vector< AbsoluteQuantitationStandards::featureConcentration > &	component_concentrations,
		const String &	feature_name,
		const String &	transformation_model,
		const Param &	transformation_model_params
	)

protected

This function computes a candidate outlier point by iteratively leaving one point out to find the one which results in the maximum R^2 of a first order linear regression of the remaining ones.

Parameters

component_concentrations	list of structures with features and concentrations
feature_name	name of the feature to calculate the absolute concentration.
transformation_model	model used to fit the calibration points
transformation_model_params	parameters used by the transformation_model

Returns: The position of the candidate outlier point in component_concentrations.

Exceptions

Exception::UnableToFit is thrown if fitting cannot be performed

◆ optimizeCalibrationCurveIterative()

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.

Parameters

component_concentrations	list of structures with features and concentrations. The optimal points will be returned.
feature_name	name of the feature to calculate the absolute concentration.
transformation_model	model used to fit the calibration points
transformation_model_params	parameters used by the transformation_model
optimized_params	optimized parameters

Returns: true if a a fit was found, false otherwise

Exceptions

Exception::UnableToFit

◆ optimizeCalibrationCurves()

void optimizeCalibrationCurves ( std::map< String, std::vector< AbsoluteQuantitationStandards::featureConcentration >> & components_concentrations )

This function optimizes the parameters of the calibration for a all components.

Parameters

components_concentrations An AbsoluteQuantitationStandards::components_to_concentrations type. Note that the method will update the list of featureConcentrations in place. The resulting components_concentrations will reflect the optimal set of points for downstream QC/QA.

◆ optimizeSingleCalibrationCurve()

void optimizeSingleCalibrationCurve	(	const String &	component_name,
		std::vector< AbsoluteQuantitationStandards::featureConcentration > &	component_concentrations
	)

This function optimizes the parameters of the calibration for a single component.

Note: This method is provided primarily to ease Python bindings. C++ users are encouraged to use `optimizeCalibrationCurves()`.

Parameters

[in]	component_name
[in,out]	component_concentrations	The method will update the argument in place. The resulting value will reflect the optimal set of points for downstream QC/QA.

◆ quantifyComponents()

void quantifyComponents ( FeatureMap & unknowns )

This function applies the calibration curve to all components.

An additional annotation for metaValue of "calculated_concentration" and "concentration_units" corresponding to the absolute concentration as back-calculated from the fitted calibration curve model and parameters will be added to each sub-feature. It is assumed that all duplicate components have been removed. If not, the function will quantify all components, but the first internal standard found will be used to calculate the ratio for the calculation.

Parameters

unknowns A FeatureMap to quantify.

◆ residualOutlierCandidate_()

int residualOutlierCandidate_	(	const std::vector< AbsoluteQuantitationStandards::featureConcentration > &	component_concentrations,
		const String &	feature_name,
		const String &	transformation_model,
		const Param &	transformation_model_params
	)

protected

This function computes a candidate outlier point by computing the residuals of all points to the linear fit and selecting the one with the largest deviation.

Parameters

component_concentrations	list of structures with features and concentrations
feature_name	name of the feature to calculate the absolute concentration.
transformation_model	model used to fit the calibration points
transformation_model_params	parameters used by the transformation_model

Returns: The position of the candidate outlier point in component_concentrations.

Exceptions

Exception::UnableToFit is thrown if fitting cannot be performed

◆ setQuantMethods()

void setQuantMethods ( std::vector< AbsoluteQuantitationMethod > & quant_methods )

quant_method setter. A list of AbsoluteQuantitationMethod classes are given as input and a map is constructed based on their component_name member.

Parameters

quant_methods A list of AbsoluteQuantitationMethod classes

◆ updateMembers_()

void updateMembers_ ( )

overrideprivatevirtual

Synchronize members with param class.

Reimplemented from DefaultParamHandler.

Member Data Documentation

◆ max_bias_

double max_bias_

private

◆ max_iters_

size_t max_iters_

private

◆ min_correlation_coefficient_

double min_correlation_coefficient_

private

◆ min_points_

size_t min_points_

private

◆ optimization_method_

String optimization_method_

private

◆ outlier_detection_method_

String outlier_detection_method_

private

◆ quant_methods_

std::map<String, AbsoluteQuantitationMethod> quant_methods_

private

map between components and quantitation methods

◆ use_chauvenet_

bool use_chauvenet_

private

Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ AbsoluteQuantitation()

◆ ~AbsoluteQuantitation()

Member Function Documentation

◆ applyCalibration()

◆ calculateBias()

◆ calculateBiasAndR()

◆ calculateRatio()

◆ extractComponents_()

◆ fitCalibration()

◆ getQuantMethods()

◆ getQuantMethodsAsMap()

◆ jackknifeOutlierCandidate_()

◆ optimizeCalibrationCurveIterative()

◆ optimizeCalibrationCurves()

◆ optimizeSingleCalibrationCurve()

◆ quantifyComponents()

◆ residualOutlierCandidate_()

◆ setQuantMethods()

◆ updateMembers_()

Member Data Documentation

◆ max_bias_

◆ max_iters_

◆ min_correlation_coefficient_

◆ min_points_

◆ optimization_method_

◆ outlier_detection_method_

◆ quant_methods_

◆ use_chauvenet_