A feature grouping algorithm for unlabeled data. More...

#include <OpenMS/ANALYSIS/MAPMATCHING/FeatureGroupingAlgorithmQT.h>

Inheritance diagram for FeatureGroupingAlgorithmQT:

Collaboration diagram for FeatureGroupingAlgorithmQT:

Public Member Functions
	FeatureGroupingAlgorithmQT ()
	Default constructor. More...

	~FeatureGroupingAlgorithmQT () override
	Destructor. More...

void	group (const std::vector< FeatureMap > &maps, ConsensusMap &out) override
	Applies the algorithm to feature maps. More...

void	group (const std::vector< ConsensusMap > &maps, ConsensusMap &out) override
	Applies the algorithm to consensus maps. More...

Public Member Functions inherited from FeatureGroupingAlgorithm
	FeatureGroupingAlgorithm ()
	Default constructor. More...

	~FeatureGroupingAlgorithm () override
	Destructor. More...

void	transferSubelements (const std::vector< ConsensusMap > &maps, ConsensusMap &out) const
	Transfers subelements (grouped features) from input consensus maps to the result consensus map. 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...

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...

Private Member Functions
	FeatureGroupingAlgorithmQT (const FeatureGroupingAlgorithmQT &)
	Copy constructor intentionally not implemented -> private. More...

FeatureGroupingAlgorithmQT &	operator= (const FeatureGroupingAlgorithmQT &)
	Assignment operator intentionally not implemented -> private. More...

template<typename MapType >
void	group_ (const std::vector< MapType > &maps, ConsensusMap &out)
	Applies the algorithm to feature or consensus maps. 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 Member Functions inherited from FeatureGroupingAlgorithm
template<class MapType >
void	postprocess_ (const std::vector< MapType > &maps, ConsensusMap &out)

Protected Member Functions inherited from DefaultParamHandler
virtual void	updateMembers_ ()
	This method is used to update extra member variables at the end of the setParameters() method. More...

void	defaultsToParam_ ()
	Updates the parameters after the defaults have been set in the constructor. 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

A feature grouping algorithm for unlabeled data.

The algorithm takes a number of feature or consensus maps and searches for corresponding (consensus) features across different maps. The maps have to be aligned (i.e. retention time distortions corrected, using one of the map-alignment algorithms, e.g. MapAlignmentAlgorithmKD), but small deviations are tolerated.

This particular algorithm accumulates the features from all input maps, then applies a variant of QT clustering to find groups of corresponding features. For more details, see QTClusterFinder.

Parameters of this class are:

Name	Type	Default	Restrictions	Description
use_identifications	string	false	true, false	Never link features that are annotated with different peptides (only the best hit per peptide identification is taken into account).
nr_partitions	int	100	min: 1	How many partitions in m/z space should be used for the algorithm (more partitions means faster runtime and more memory efficient execution).
min_nr_diffs_per_bin	int	50	min: 5	If IDs are used: How many differences from matching IDs should be used to calculate a linking tolerance for unIDed features in an RT region. RT regions will be extended until that number is reached.
min_IDscore_forTolCalc	float	1.0		If IDs are used: What is the minimum score of an ID to assume a reliable match for tolerance calculation. Check your current score type!
noID_penalty	float	0.0	min: 0.0 max: 1.0	If IDs are used: For the normalized distances, how high should the penalty for missing IDs be? 0 = no bias, 1 = IDs inside the max tolerances always preferred (even if much further away).
ignore_charge	string	false	true, false	false [default]: pairing requires equal charge state (or at least one unknown charge '0'); true: Pairing irrespective of charge state
ignore_adduct	string	true	true, false	true [default]: pairing requires equal adducts (or at least one without adduct annotation); true: Pairing irrespective of adducts
distance_RT:max_difference	float	100.0	min: 0.0	Never pair features with a larger RT distance (in seconds).
distance_RT:exponent	float	1.0	min: 0.0	Normalized RT differences ([0-1], relative to 'max_difference') are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)
distance_RT:weight	float	1.0	min: 0.0	Final RT distances are weighted by this factor
distance_MZ:max_difference	float	0.3	min: 0.0	Never pair features with larger m/z distance (unit defined by 'unit')
distance_MZ:unit	string	Da	Da, ppm	Unit of the 'max_difference' parameter
distance_MZ:exponent	float	2.0	min: 0.0	Normalized ([0-1], relative to 'max_difference') m/z differences are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)
distance_MZ:weight	float	1.0	min: 0.0	Final m/z distances are weighted by this factor
distance_intensity:exponent	float	1.0	min: 0.0	Differences in relative intensity ([0-1]) are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)
distance_intensity:weight	float	0.0	min: 0.0	Final intensity distances are weighted by this factor
distance_intensity:log_transform	string	disabled	enabled, disabled	Log-transform intensities? If disabled, d = \|int_f2 - int_f1\| / int_max. If enabled, d = \|log(int_f2 + 1) - log(int_f1 + 1)\| / log(int_max + 1))

Note:

If a section name is documented, the documentation is displayed as tooltip.
Advanced parameter names are italic.

Constructor & Destructor Documentation

◆ FeatureGroupingAlgorithmQT() [1/2]

FeatureGroupingAlgorithmQT ( )

Default constructor.

◆ ~FeatureGroupingAlgorithmQT()

~FeatureGroupingAlgorithmQT ( )

override

Destructor.

◆ FeatureGroupingAlgorithmQT() [2/2]

FeatureGroupingAlgorithmQT ( const FeatureGroupingAlgorithmQT & )

private

Copy constructor intentionally not implemented -> private.

Member Function Documentation

◆ group() [1/2]

void group	(	const std::vector< ConsensusMap > &	maps,
		ConsensusMap &	out
	)

overridevirtual

Applies the algorithm to consensus maps.

Precondition: The data ranges of the input maps have to be up-to-date (use ConsensusMap::updateRanges).

Exceptions

IllegalArgument is thrown if less than two input maps are given.

Reimplemented from FeatureGroupingAlgorithm.

◆ group() [2/2]

void group	(	const std::vector< FeatureMap > &	maps,
		ConsensusMap &	out
	)

overridevirtual

Applies the algorithm to feature maps.

Precondition: The data ranges of the input maps have to be up-to-date (use FeatureMap::updateRanges).

Exceptions

IllegalArgument is thrown if less than two input maps are given.

Implements FeatureGroupingAlgorithm.

◆ group_()

void group_	(	const std::vector< MapType > &	maps,
		ConsensusMap &	out
	)

private

Applies the algorithm to feature or consensus maps.

Precondition: The data ranges of the input maps have to be up-to-date (use MapType::updateRanges).

Exceptions

IllegalArgument is thrown if less than two input maps are given.

◆ operator=()

FeatureGroupingAlgorithmQT& operator= ( const FeatureGroupingAlgorithmQT & )

private

Assignment operator intentionally not implemented -> private.

Public Member Functions

Private Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ FeatureGroupingAlgorithmQT() [1/2]

◆ ~FeatureGroupingAlgorithmQT()

◆ FeatureGroupingAlgorithmQT() [2/2]

Member Function Documentation

◆ group() [1/2]

◆ group() [2/2]

◆ group_()

◆ operator=()