FeatureGroupingAlgorithmQT Class Reference

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

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

Inheritance diagram for FeatureGroupingAlgorithmQT:

Public Member Functions
	FeatureGroupingAlgorithmQT ()
	Default constructor. More...
virtual	~FeatureGroupingAlgorithmQT ()
	Destructor. More...
virtual void	group (const std::vector< FeatureMap > &maps, ConsensusMap &out)
	Applies the algorithm to feature maps. More...
virtual void	group (const std::vector< ConsensusMap > &maps, ConsensusMap &out)
	Applies the algorithm to consensus maps. More...
Public Member Functions inherited from FeatureGroupingAlgorithm
	FeatureGroupingAlgorithm ()
	Default constructor. More...
virtual	~FeatureGroupingAlgorithm ()
	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...
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...

Static Public Member Functions
static FeatureGroupingAlgorithm *	create ()
	Creates a new instance of this class (for Factory) More...
static String	getProductName ()
	Returns the product name (for the Factory) More...
Static Public Member Functions inherited from FeatureGroupingAlgorithm
static void	registerChildren ()
	Register all derived classes in this method. 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
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, e.g. using one of the MapAlignmentAlgorithms), 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 )
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
distance_RT:max_difference	float	100	min: 0	Never pair features with a larger RT distance (in seconds).
distance_RT:exponent	float	1	min: 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	min: 0	Final RT distances are weighted by this factor
distance_MZ:max_difference	float	0.3	min: 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	min: 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	min: 0	Final m/z distances are weighted by this factor
distance_intensity:exponent	float	1	min: 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	min: 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()

virtual ~FeatureGroupingAlgorithmQT ( )

virtual

Destructor.

FeatureGroupingAlgorithmQT() [2/2]

FeatureGroupingAlgorithmQT ( const FeatureGroupingAlgorithmQT &  )

private

Copy constructor intentionally not implemented -> private.

Member Function Documentation

create()

static FeatureGroupingAlgorithm* create ( )

inlinestatic

Creates a new instance of this class (for Factory)

getProductName()

static String getProductName ( )

inlinestatic

Returns the product name (for the Factory)

group() [1/2]

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

virtual

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() [2/2]

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

virtual

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_()

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.