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FeatureGroupingAlgorithmUnlabeled Class Reference
[FeatureGrouping]

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

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

Inheritance diagram for FeatureGroupingAlgorithmUnlabeled:
FeatureGroupingAlgorithm DefaultParamHandler

List of all members.

Public Member Functions

 FeatureGroupingAlgorithmUnlabeled ()
 Default constructor.
virtual ~FeatureGroupingAlgorithmUnlabeled ()
 Destructor.
virtual void group (const std::vector< FeatureMap<> > &maps, ConsensusMap &out)
 Applies the algorithm.

Static Public Member Functions

static FeatureGroupingAlgorithmcreate ()
 Creates a new instance of this class (for Factory).
static String getProductName ()
 Returns the product name (for the Factory).

Private Member Functions

 FeatureGroupingAlgorithmUnlabeled (const FeatureGroupingAlgorithmUnlabeled &)
 Copy constructor intentionally not implemented -> private.
FeatureGroupingAlgorithmUnlabeledoperator= (const FeatureGroupingAlgorithmUnlabeled &)
 Assignment operator intentionally not implemented -> private.

Detailed Description

A map feature grouping algorithm for unlabeled data.

It takes many maps and searches for corresponding features. The corresponding features must be aligned, but may have small position deviations.

Parameters of this class are:

NameTypeDefaultRestrictionsDescription
second_nearest_gap float2 min: 1The distance to the second nearest neighbors must be larger by this factor than the distance to the matching element itself.
use_identifications stringfalse true, falseNever link features that are annotated with different peptides (only the best hit per peptide identification is taken into account).
ignore_charge stringfalse true, falseCompare features normally even if their charge states are different
distance_RT:max_difference float100 min: 0Maximum allowed difference in RT in seconds
distance_RT:exponent float1 min: 0Normalized RT differences are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)
distance_RT:weight float1 min: 0RT distances are weighted by this factor
distance_MZ:max_difference float0.3 min: 0Maximum allowed difference in m/z (unit defined by 'unit')
distance_MZ:unit stringDa Da, ppmUnit of the 'max_difference' parameter
distance_MZ:exponent float2 min: 0Normalized 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: 0m/z distances are weighted by this factor
distance_intensity:exponent float1 min: 0Differences in relative intensity are raised to this power (using 1 or 2 will be fast, everything else is REALLY slow)
distance_intensity:weight float0 min: 0Distances based on relative intensity are weighted by this factor

Note:

Constructor & Destructor Documentation

Default constructor.

virtual ~FeatureGroupingAlgorithmUnlabeled (  )  [virtual]

Destructor.

Copy constructor intentionally not implemented -> private.


Member Function Documentation

static FeatureGroupingAlgorithm* create (  )  [inline, static]

Creates a new instance of this class (for Factory).

static String getProductName (  )  [inline, static]

Returns the product name (for the Factory).

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

Applies the algorithm.

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

Implements FeatureGroupingAlgorithm.

Assignment operator intentionally not implemented -> private.


OpenMS / TOPP release 1.10.0 Documentation generated on Thu Mar 7 2013 09:42:49 using doxygen 1.7.1