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QTClusterFinder Class Reference

A variant of QT clustering for the detection of feature groups. More...

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

Inheritance diagram for QTClusterFinder:
BaseGroupFinder DefaultParamHandler ProgressLogger

Public Member Functions

 QTClusterFinder ()
 Constructor. More...
 
virtual ~QTClusterFinder ()
 Destructor. More...
 
void run (const std::vector< ConsensusMap > &input_maps, ConsensusMap &result_map)
 Runs the algorithm on consensus maps. More...
 
void run (const std::vector< FeatureMap > &input_maps, ConsensusMap &result_map)
 Runs the algorithm on feature maps. More...
 
- Public Member Functions inherited from BaseGroupFinder
 BaseGroupFinder ()
 Default constructor. More...
 
virtual ~BaseGroupFinder ()
 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...
 
virtual DefaultParamHandleroperator= (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 ParamgetParameters () const
 Non-mutable access to the parameters. More...
 
const ParamgetDefaults () const
 Non-mutable access to the default parameters. More...
 
const StringgetName () 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...
 
 ~ProgressLogger ()
 Destructor. More...
 
 ProgressLogger (const ProgressLogger &other)
 Copy constructor. More...
 
ProgressLoggeroperator= (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...
 

Static Public Member Functions

static const String getProductName ()
 Returns the name of the product. More...
 
static BaseGroupFindercreate ()
 Returns an instance of this class. More...
 
- Static Public Member Functions inherited from BaseGroupFinder
static void registerChildren ()
 Register all derived classes here. More...
 

Protected Types

enum  { RT = Peak2D::RT, MZ = Peak2D::MZ }
 

Private Types

typedef OpenMSBoost::unordered_map< std::pair< OpenMS::GridFeature *, OpenMS::GridFeature * >, doublePairDistances
 Distances between pairs of grid features. More...
 
typedef OpenMSBoost::unordered_map< OpenMS::GridFeature *, std::vector< QTCluster * > > ElementMapping
 Map to store which grid features are next to which clusters. More...
 
typedef HashGrid< OpenMS::GridFeature * > Grid
 

Private Member Functions

double getDistance_ (const OpenMS::GridFeature *left, const OpenMS::GridFeature *right)
 Calculates the distance between two grid features. More...
 
void setParameters_ (double max_intensity, double max_mz)
 Sets algorithm parameters. More...
 
void makeConsensusFeature_ (std::list< QTCluster > &clustering, ConsensusFeature &feature, ElementMapping &element_mapping, Grid &)
 Generates a consensus feature from the best cluster and updates the clustering. More...
 
void computeClustering_ (Grid &grid, std::list< QTCluster > &clustering)
 Computes an initial QT clustering of the points in the hash grid. More...
 
template<typename MapType >
void run_ (const std::vector< MapType > &input_maps, ConsensusMap &result_map)
 Runs the algorithm on feature maps or consensus maps. More...
 
template<typename MapType >
void run_internal_ (const std::vector< MapType > &input_maps, ConsensusMap &result_map, bool do_progress)
 Runs the algorithm on feature maps or consensus maps (internal) More...
 
void addClusterElements_ (int x, int y, const Grid &grid, QTCluster &cluster, const OpenMS::GridFeature *center_feature)
 Adds elements to the cluster based on the elements hashed in the grid. More...
 

Private Attributes

Size num_maps_
 Number of input maps. More...
 
bool use_IDs_
 Consider peptide identifications for grouping? More...
 
double max_diff_rt_
 Maximum RT difference. More...
 
double max_diff_mz_
 Maximum m/z difference. More...
 
int nr_partitions_
 Maximum m/z difference. More...
 
FeatureDistance feature_distance_
 Feature distance functor. More...
 
std::set< OpenMS::GridFeature * > already_used_
 Set of features already used. More...
 

Additional Inherited Members

- Public Types inherited from ProgressLogger
enum  LogType { CMD, GUI, NONE }
 Possible log types. More...
 
- 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
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...
 
- 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< Stringsubsections_
 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_
 
ProgressLoggerImplcurrent_logger_
 
- Static Protected Attributes inherited from ProgressLogger
static int recursion_depth_
 

Detailed Description

A variant of QT clustering for the detection of feature groups.

The algorithm accumulates all features from all input maps, then applies a variant of QT clustering to find groups of corresponding features. In more detail, every feature from every input map is considered as a potential cluster center. For every center, its nearest neighbors from the other input maps are detected and added to the potential cluster. Iteratively, the cluster with the highest quality is extracted and the clustering is updated.

Properties affecting the grouping

To be included in a particular cluster, a feature has to fulfill the following conditions:

Every cluster contains at most one feature from each input map - namely the feature closest to the cluster center that meets the criteria and does not belong to a better cluster.

The notion of "closeness" for features is defined by the distance function implemented in FeatureDistance, the parameters of which can be set by the user.

The quality of a cluster is computed from the number of elements in it and their distances to the cluster center. For more details see QTCluster.

Optimization

This algorithm includes a number of optimizations to reduce run-time:

See also
FeatureGroupingAlgorithmQT
Parameters of this class are:

NameTypeDefaultRestrictionsDescription
use_identifications stringfalse true, falseNever link features that are annotated with different peptides (only the best hit per peptide identification is taken into account).
nr_partitions int100 min: 1How many partitions in m/z space should be used for the algorithm (more partitions means faster runtime and more memory efficient execution )
ignore_charge stringfalse true, falsefalse [default]: pairing requires equal charge state (or at least one unknown charge '0'); true: Pairing irrespective of charge state
distance_RT:max_difference float100 min: 0Never pair features with a larger RT distance (in seconds).
distance_RT:exponent float1 min: 0Normalized 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 float1 min: 0Final RT distances are weighted by this factor
distance_MZ:max_difference float0.3 min: 0Never pair features with larger m/z distance (unit defined by 'unit')
distance_MZ:unit stringDa Da, ppmUnit of the 'max_difference' parameter
distance_MZ:exponent float2 min: 0Normalized ([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 float1 min: 0Final m/z distances are weighted by this factor
distance_intensity:exponent float1 min: 0Differences 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 float0 min: 0Final intensity distances are weighted by this factor
distance_intensity:log_transform stringdisabled enabled, disabledLog-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:

Member Typedef Documentation

◆ ElementMapping

typedef OpenMSBoost::unordered_map< OpenMS::GridFeature*, std::vector<QTCluster*> > ElementMapping
private

Map to store which grid features are next to which clusters.

◆ Grid

typedef HashGrid<OpenMS::GridFeature*> Grid
private

◆ PairDistances

typedef OpenMSBoost::unordered_map< std::pair<OpenMS::GridFeature*, OpenMS::GridFeature*>, double> PairDistances
private

Distances between pairs of grid features.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum
protected
Enumerator
RT 
MZ 

Constructor & Destructor Documentation

◆ QTClusterFinder()

Constructor.

◆ ~QTClusterFinder()

virtual ~QTClusterFinder ( )
virtual

Destructor.

Member Function Documentation

◆ addClusterElements_()

void addClusterElements_ ( int  x,
int  y,
const Grid grid,
QTCluster cluster,
const OpenMS::GridFeature center_feature 
)
private

Adds elements to the cluster based on the elements hashed in the grid.

◆ computeClustering_()

void computeClustering_ ( Grid grid,
std::list< QTCluster > &  clustering 
)
private

Computes an initial QT clustering of the points in the hash grid.

◆ create()

static BaseGroupFinder* create ( )
inlinestatic

Returns an instance of this class.

◆ getDistance_()

double getDistance_ ( const OpenMS::GridFeature left,
const OpenMS::GridFeature right 
)
private

Calculates the distance between two grid features.

◆ getProductName()

static const String getProductName ( )
inlinestatic

Returns the name of the product.

◆ makeConsensusFeature_()

void makeConsensusFeature_ ( std::list< QTCluster > &  clustering,
ConsensusFeature feature,
ElementMapping element_mapping,
Grid  
)
private

Generates a consensus feature from the best cluster and updates the clustering.

◆ run() [1/2]

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

Runs the algorithm on consensus maps.

Precondition
The data ranges of the input maps have to be up-to-date (use ConsensusMap::updateRanges).
Exceptions
Exception::IllegalArgumentis thrown if the input data is not valid.

Implements BaseGroupFinder.

◆ run() [2/2]

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

Runs the algorithm on feature maps.

Precondition
The data ranges of the input maps have to be up-to-date (use FeatureMap::updateRanges).
Exceptions
Exception::IllegalArgumentis thrown if the input data is not valid.

◆ run_()

void run_ ( const std::vector< MapType > &  input_maps,
ConsensusMap result_map 
)
private

Runs the algorithm on feature maps or consensus maps.

◆ run_internal_()

void run_internal_ ( const std::vector< MapType > &  input_maps,
ConsensusMap result_map,
bool  do_progress 
)
private

Runs the algorithm on feature maps or consensus maps (internal)

◆ setParameters_()

void setParameters_ ( double  max_intensity,
double  max_mz 
)
private

Sets algorithm parameters.

Member Data Documentation

◆ already_used_

std::set<OpenMS::GridFeature*> already_used_
private

Set of features already used.

◆ feature_distance_

FeatureDistance feature_distance_
private

Feature distance functor.

◆ max_diff_mz_

double max_diff_mz_
private

Maximum m/z difference.

◆ max_diff_rt_

double max_diff_rt_
private

Maximum RT difference.

◆ nr_partitions_

int nr_partitions_
private

Maximum m/z difference.

◆ num_maps_

Size num_maps_
private

Number of input maps.

◆ use_IDs_

bool use_IDs_
private

Consider peptide identifications for grouping?


OpenMS / TOPP release 2.3.0 Documentation generated on Tue Jan 9 2018 18:22:12 using doxygen 1.8.13