This class implements a pair finding algorithm for consensus features. More...

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

Inheritance diagram for StablePairFinder:

Collaboration diagram for StablePairFinder:

Public Types
typedef BaseGroupFinder	Base
	Base class. More...

Public Types inherited from ProgressLogger
enum	LogType { CMD , GUI , NONE }
	Possible log types. More...

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

	~StablePairFinder () override
	Destructor. More...

void	run (const std::vector< ConsensusMap > &input_maps, ConsensusMap &result_map) override
	Run the algorithm. More...

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

	~BaseGroupFinder () override
	Destructor. 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...

Public Member Functions inherited from ProgressLogger
	ProgressLogger ()
	Constructor. More...

virtual	~ProgressLogger ()
	Destructor. More...

	ProgressLogger (const ProgressLogger &other)
	Copy constructor. More...

ProgressLogger &	operator= (const ProgressLogger &other)
	Assignment Operator. More...

void	setLogType (LogType type) const
	Sets the progress log that should be used. The default type is NONE! More...

LogType	getLogType () const
	Returns the type of progress log being used. More...

void	startProgress (SignedSize begin, SignedSize end, const String &label) const
	Initializes the progress display. More...

void	setProgress (SignedSize value) const
	Sets the current progress. More...

void	endProgress () const
	Ends the progress display. More...

void	nextProgress () const
	increment progress by 1 (according to range begin-end) More...

Static Public Member Functions
static BaseGroupFinder *	create ()
	Returns an instance of this class. More...

static const String	getProductName ()
	Returns the name of this module. More...

Static Public Member Functions inherited from BaseGroupFinder
static void	registerChildren ()
	Register all derived classes here. More...

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...

Internal helper classes and enums
enum	{ RT = Peak2D::RT , MZ = Peak2D::MZ }

double	second_nearest_gap_
	The distance to the second nearest neighbors must be by this factor larger than the distance to the matched element itself. More...

bool	use_IDs_
	Only match if peptide IDs are compatible? More...

void	updateMembers_ () override
	This method is used to update extra member variables at the end of the setParameters() method. More...

bool	compatibleIDs_ (const ConsensusFeature &feat1, const ConsensusFeature &feat2) const
	Checks if the peptide IDs of two features are compatible. More...

const AASequence &	getBestHitSequence_ (const PeptideIdentification &peptideIdentification) const
	Returns the highest scoring peptide hit in the the given peptide identification. More...

Additional Inherited Members
Protected Member Functions inherited from BaseGroupFinder
void	checkIds_ (const std::vector< ConsensusMap > &maps) const
	Checks if all file descriptions have disjoint map identifiers. More...

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

Static Protected Member Functions inherited from ProgressLogger
static String	logTypeToFactoryName_ (LogType type)
	Return the name of the factory product used for this log type. 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...

Protected Attributes inherited from ProgressLogger
LogType	type_

time_t	last_invoke_

ProgressLoggerImpl *	current_logger_

Static Protected Attributes inherited from ProgressLogger
static int	recursion_depth_

Detailed Description

This class implements a pair finding algorithm for consensus features.

It offers a method to determine pairs across two consensus maps. The corresponding consensus features must be aligned, but may have small position deviations.

The distance measure is implemented in class FeatureDistance - see there for details.

Additional criteria for pairing

Depending on parameter use_identifications, peptide identifications annotated to the features may have to be compatible (i.e. no annotation or the same annotation) for a pairing to occur.

Stability criterion: The distance to the nearest neighbor must be smaller than the distance to the second-nearest neighbor by a certain factor, see parameter second_nearest_gap. There is a non-trivial relation between this parameter and the maximum allowed difference (in RT or m/z) of the distance measure: If second_nearest_gap is greater than one, lowering max_difference may in fact lead to more - rather than fewer - pairings, because it increases the distance difference between the nearest and the second-nearest neighbor, so that the constraint imposed by second_nearest_gap may be fulfilled more often.

Quality calculation

The quality of a pairing is computed from the distance between the paired elements (nearest neighbors) and the distances to the second-nearest neighbors of both elements, according to the formula:

\[ q_{i,j} = \big( 1 - d_{i,j} \big) \cdot \big( 1 - \frac{g \cdot d_{i,j}}{d_{2,i}} \big) \cdot \big( 1 - \frac{g \cdot d_{i,j}}{d_{2,j}} \big) \cdot \]

\( q_{i,j} \) is the quality of the pairing of elements i and j, \( d_{i,j} \) is the distance between the two, \( d_{2,i} \) and \(d_{2,j} \) are the distances to the second-nearest neighbors of i and j, respectively, and g is the factor defined by parameter second_nearest_gap.

Note that by the definition of the distance measure, \( 0 \leq d_{i,j} \leq 1 \) if i and j are to form a pair. The criteria for pairing further require that \( g \cdot d_{i,j} \leq d_{2,i} \) and \( g \cdot d_{i,j} \leq d_{2,j} \). This ensures that the resulting quality is always between one (best) and zero (worst).

For the final quality q of the consensus feature produced by merging two paired elements (i and j), the existing quality values of the two elements are taken into account. The final quality is a weighted average of the existing qualities ( \( q_i \) and \( q_j \)) and the quality of the pairing ( \( q_{i,j} \), see above):

\[ q = \frac{q_{i,j} + (s_i - 1) \cdot q_i + (s_j - 1) \cdot q_j}{s_i + s_j - 1} \]

The weighting factors \( s_i \) and \( s_j \) are the sizes (i.e. numbers of subelements) of the two consensus features i and j. That way, it is possible to link several feature maps to a growing consensus map in a stepwise fashion (as done by FeatureGroupingAlgorithmUnlabeled), and in the end obtain quality values that incorporate the qualities of all pairings that occurred during the generation of a consensus feature. Note that "missing" elements (if a consensus feature does not contain sub-features from all input maps) are not punished in this definition of quality.

Parameters of this class are:

Name	Type	Default	Restrictions	Description
second_nearest_gap	float	2.0	min: 1.0	Only link features whose distance to the second nearest neighbors (for both sides) is larger by 'second_nearest_gap' than the distance between the matched pair itself.
use_identifications	string	false	true, false	Never link features that are annotated with different peptides (features without ID's always match; only the best hit per peptide identification is considered).
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.

Member Typedef Documentation

◆ Base

typedef BaseGroupFinder Base

Base class.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum

protected

Enumerator
RT
MZ

Constructor & Destructor Documentation

◆ StablePairFinder()

StablePairFinder ( )

Constructor.

◆ ~StablePairFinder()

~StablePairFinder ( )

inlineoverride

Destructor.

Member Function Documentation

◆ compatibleIDs_()

bool compatibleIDs_	(	const ConsensusFeature &	feat1,
		const ConsensusFeature &	feat2
	)		const

protected

Checks if the peptide IDs of two features are compatible.

A feature without identification is always compatible. Otherwise, two features are compatible if the best peptide hits of their identifications have the same sequences.

◆ create()

static BaseGroupFinder* create ( )

inlinestatic

Returns an instance of this class.

◆ getBestHitSequence_()

const AASequence& getBestHitSequence_ ( const PeptideIdentification & peptideIdentification ) const

protected

Returns the highest scoring peptide hit in the the given peptide identification.

Parameters

peptideIdentification The peptideIdentification to scan.

◆ getProductName()

static const String getProductName ( )

inlinestatic

Returns the name of this module.

◆ run()

void run	(	const std::vector< ConsensusMap > &	input_maps,
		ConsensusMap &	result_map
	)

overridevirtual

Run the algorithm.

Note: Exactly two input maps must be provided.

Exceptions

Exception::IllegalArgument is thrown if the input data is not valid.

Implements BaseGroupFinder.

◆ updateMembers_()

void updateMembers_ ( )

overrideprotectedvirtual

This method is used to update extra member variables at the end of the setParameters() method.

Also call it at the end of the derived classes' copy constructor and assignment operator.

The default implementation is empty.

Reimplemented from DefaultParamHandler.

Member Data Documentation

◆ second_nearest_gap_

double second_nearest_gap_

protected

The distance to the second nearest neighbors must be by this factor larger than the distance to the matched element itself.

◆ use_IDs_

bool use_IDs_

protected

Only match if peptide IDs are compatible?

Public Types

Public Member Functions

Static Public Member Functions

Internal helper classes and enums

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ Base

Member Enumeration Documentation

◆ anonymous enum

Constructor & Destructor Documentation

◆ StablePairFinder()

◆ ~StablePairFinder()

Member Function Documentation

◆ compatibleIDs_()

◆ create()

◆ getBestHitSequence_()

◆ getProductName()

◆ run()

◆ updateMembers_()

Member Data Documentation

◆ second_nearest_gap_

◆ use_IDs_