A map alignment algorithm based on peptide identifications from MS2 spectra. More...

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

Inheritance diagram for MapAlignmentAlgorithmTreeGuided:

Collaboration diagram for MapAlignmentAlgorithmTreeGuided:

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

	~MapAlignmentAlgorithmTreeGuided () override
	Destructor. More...

void	treeGuidedAlignment (const std::vector< BinaryTreeNode > &tree, std::vector< FeatureMap > &feature_maps_transformed, std::vector< std::vector< double >> &maps_ranges, FeatureMap &map_transformed, std::vector< Size > &trafo_order)
	Align feature maps tree guided using align() of OpenMS::MapAlignmentAlgorithmIdentification and use TreeNode with larger 10/90 percentile range as reference. More...

void	align (std::vector< FeatureMap > &data, std::vector< TransformationDescription > &transformations)
	Align feature maps tree guided using align() of OpenMS::MapAlignmentAlgorithmIdentification and use TreeNode with larger 10/90 percentile range as reference. More...

void	computeTrafosByOriginalRT (std::vector< FeatureMap > &feature_maps, FeatureMap &map_transformed, std::vector< TransformationDescription > &transformations, const std::vector< Size > &trafo_order)
	Extract original RT ("original_RT" MetaInfo) and transformed RT for each feature to compute RT transformations. 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	setLogger (ProgressLoggerImpl *logger)
	Sets the logger to be used for progress logging. 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 (UInt64 bytes_processed=0) const

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

Static Public Member Functions
static void	buildTree (std::vector< FeatureMap > &feature_maps, std::vector< BinaryTreeNode > &tree, std::vector< std::vector< double >> &maps_ranges)
	Extract RTs given for individual features of each map, calculate distances for each pair of maps and cluster hierarchical using average linkage. More...

static void	computeTransformedFeatureMaps (std::vector< FeatureMap > &feature_maps, const std::vector< TransformationDescription > &transformations)
	Apply transformations on input maps. 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...

Protected Types
typedef std::map< String, DoubleList >	SeqAndRTList
	Type to store feature retention times given for individual peptide sequence. More...

Protected Member Functions
void	updateMembers_ () override
	This method is used to update extra member variables at the end of the setParameters() method. 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
static void	addPeptideSequences_ (const std::vector< PeptideIdentification > &peptides, SeqAndRTList &peptide_rts, std::vector< double > &map_range, double feature_rt)
	For given peptide identifications extract sequences and store with associated feature RT. More...

static void	extractSeqAndRt_ (const std::vector< FeatureMap > &feature_maps, std::vector< SeqAndRTList > &maps_seq_and_rt, std::vector< std::vector< double >> &maps_ranges)
	For each input map, extract peptide identifications (sequences) of existing features with associated feature RT. More...

Protected Attributes
String	model_type_
	Type of transformation model. More...

Param	model_param_
	Default params of transformation models linear, b_spline, lowess and interpolated. More...

MapAlignmentAlgorithmIdentification	align_algorithm_
	Instantiation of alignment algorithm. 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_

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

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

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

Static Protected Attributes inherited from ProgressLogger
static int	recursion_depth_

Detailed Description

A map alignment algorithm based on peptide identifications from MS2 spectra.

ID groups with the same sequence in different maps represent points of correspondence in RT between the maps. They are used to evaluate the distances between the maps for hierarchical clustering and form the basis for the alignment. Only the best PSM per spectrum is considered as the correct identification.

For each pair of maps, the similarity is determined based on the intersection of the contained identifications using Pearson correlation. For small intersections, the Pearson value is reduced by multiplying the ratio of the intersection size to the union size: \(\texttt{PearsonValue(map1}\cap \texttt{map2)}*\Bigl(\frac{\texttt{N(map1 }\cap\texttt{ map2})}{\texttt{N(map1 }\cup\texttt{ map2})}\Bigr)\) Using hierarchical clustering together with average linkage a binary tree is produced. Following the tree, the maps are aligned, resulting in a transformed feature map that contains both the original and the transformed retention times. As long as there are at least two clusters, the alignment is done as follows: Of every pair of clusters, the one with the larger 10/90 percentile retention time range is selected as reference for the align() method of OpenMS::MapAlignmentAlgorithmIdentification. align() aligns the median retention time of each ID group in the second cluster to the reference retention time of this group. Cubic spline smoothing is used to convert this mapping to a smooth function. Retention times in the second cluster are transformed to the reference scale by applying this function. Additionally, the original retention times are stored in the meta information of each feature. The reference is combined with the transformed cluster.

The resulting map is used to extract transformation descriptions for each input map. For each map cubic spline smoothing is used to convert the mapping to a smooth function. Retention times of each map are transformed by applying the smoothed function.

Parameters of this class are:

Name	Type	Default	Restrictions	Description
model_type	string	b_spline	linear, b_spline, lowess, interpolated	Options to control the modeling of retention time transformations from data
model:type	string	b_spline	linear, b_spline, lowess, interpolated	Type of model
model:linear:symmetric_regression	string	false	true, false	Perform linear regression on 'y - x' vs. 'y + x', instead of on 'y' vs. 'x'.
model:linear:x_weight	string	x	1/x, 1/x2, ln(x), x	Weight x values
model:linear:y_weight	string	y	1/y, 1/y2, ln(y), y	Weight y values
model:linear:x_datum_min	float	1.0e-15		Minimum x value
model:linear:x_datum_max	float	1.0e15		Maximum x value
model:linear:y_datum_min	float	1.0e-15		Minimum y value
model:linear:y_datum_max	float	1.0e15		Maximum y value
model:b_spline:wavelength	float	0.0	min: 0.0	Determines the amount of smoothing by setting the number of nodes for the B-spline. The number is chosen so that the spline approximates a low-pass filter with this cutoff wavelength. The wavelength is given in the same units as the data; a higher value means more smoothing. '0' sets the number of nodes to twice the number of input points.
model:b_spline:num_nodes	int	5	min: 0	Number of nodes for B-spline fitting. Overrides 'wavelength' if set (to two or greater). A lower value means more smoothing.
model:b_spline:extrapolate	string	linear	linear, b_spline, constant, global_linear	Method to use for extrapolation beyond the original data range. 'linear': Linear extrapolation using the slope of the B-spline at the corresponding endpoint. 'b_spline': Use the B-spline (as for interpolation). 'constant': Use the constant value of the B-spline at the corresponding endpoint. 'global_linear': Use a linear fit through the data (which will most probably introduce discontinuities at the ends of the data range).
model:b_spline:boundary_condition	int	2	min: 0 max: 2	Boundary condition at B-spline endpoints: 0 (value zero), 1 (first derivative zero) or 2 (second derivative zero)
model:lowess:span	float	0.666666666666667	min: 0.0 max: 1.0	Fraction of datapoints (f) to use for each local regression (determines the amount of smoothing). Choosing this parameter in the range .2 to .8 usually results in a good fit.
model:lowess:num_iterations	int	3	min: 0	Number of robustifying iterations for lowess fitting.
model:lowess:delta	float	-1.0		Nonnegative parameter which may be used to save computations (recommended value is 0.01 of the range of the input, e.g. for data ranging from 1000 seconds to 2000 seconds, it could be set to 10). Setting a negative value will automatically do this.
model:lowess:interpolation_type	string	cspline	linear, cspline, akima	Method to use for interpolation between datapoints computed by lowess. 'linear': Linear interpolation. 'cspline': Use the cubic spline for interpolation. 'akima': Use an akima spline for interpolation
model:lowess:extrapolation_type	string	four-point-linear	two-point-linear, four-point-linear, global-linear	Method to use for extrapolation outside the data range. 'two-point-linear': Uses a line through the first and last point to extrapolate. 'four-point-linear': Uses a line through the first and second point to extrapolate in front and and a line through the last and second-to-last point in the end. 'global-linear': Uses a linear regression to fit a line through all data points and use it for interpolation.
model:interpolated:interpolation_type	string	cspline	linear, cspline, akima	Type of interpolation to apply.
model:interpolated:extrapolation_type	string	two-point-linear	two-point-linear, four-point-linear, global-linear	Type of extrapolation to apply: two-point-linear: use the first and last data point to build a single linear model, four-point-linear: build two linear models on both ends using the first two / last two points, global-linear: use all points to build a single linear model. Note that global-linear may not be continuous at the border.
align_algorithm:score_type	string			Name of the score type to use for ranking and filtering (.oms input only). If left empty, a score type is picked automatically.
align_algorithm:score_cutoff	string	false	true, false	Use only IDs above a score cut-off (parameter 'min_score') for alignment?
align_algorithm:min_score	float	0.05		If 'score_cutoff' is 'true': Minimum score for an ID to be considered. Unless you have very few runs or identifications, increase this value to focus on more informative peptides.
align_algorithm:min_run_occur	int	2	min: 2	Minimum number of runs (incl. reference, if any) in which a peptide must occur to be used for the alignment. Unless you have very few runs or identifications, increase this value to focus on more informative peptides.
align_algorithm:max_rt_shift	float	0.5	min: 0.0	Maximum realistic RT difference for a peptide (median per run vs. reference). Peptides with higher shifts (outliers) are not used to compute the alignment. If 0, no limit (disable filter); if > 1, the final value in seconds; if <= 1, taken as a fraction of the range of the reference RT scale.
align_algorithm:use_unassigned_peptides	string	true	true, false	Should unassigned peptide identifications be used when computing an alignment of feature or consensus maps? If 'false', only peptide IDs assigned to features will be used.
align_algorithm:use_feature_rt	string	true	true, false	When aligning feature or consensus maps, don't use the retention time of a peptide identification directly; instead, use the retention time of the centroid of the feature (apex of the elution profile) that the peptide was matched to. If different identifications are matched to one feature, only the peptide closest to the centroid in RT is used. Precludes 'use_unassigned_peptides'.
align_algorithm:use_adducts	string	true	true, false	If IDs contain adducts, treat differently adducted variants of the same molecule as different.

Note:

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

Member Typedef Documentation

◆ SeqAndRTList

typedef std::map<String, DoubleList> SeqAndRTList

protected

Type to store feature retention times given for individual peptide sequence.

Constructor & Destructor Documentation

◆ MapAlignmentAlgorithmTreeGuided() [1/2]

MapAlignmentAlgorithmTreeGuided ( )

Default constructor.

◆ ~MapAlignmentAlgorithmTreeGuided()

~MapAlignmentAlgorithmTreeGuided ( )

override

Destructor.

◆ MapAlignmentAlgorithmTreeGuided() [2/2]

MapAlignmentAlgorithmTreeGuided ( const MapAlignmentAlgorithmTreeGuided & )

private

Copy constructor intentionally not implemented -> private.

Member Function Documentation

◆ addPeptideSequences_()

static void addPeptideSequences_	(	const std::vector< PeptideIdentification > &	peptides,
		SeqAndRTList &	peptide_rts,
		std::vector< double > &	map_range,
		double	feature_rt
	)

staticprotected

For given peptide identifications extract sequences and store with associated feature RT.

Parameters

peptides	Vector of peptide identifications to extract sequences.
peptide_rts	Map to store a list of feature RTs for each peptide sequence as key.
map_range	Vector in which all feature RTs are stored for given peptide identifications.
feature_rt	RT value of the feature to which the peptide identifications to be analysed belong.

◆ align()

void align	(	std::vector< FeatureMap > &	data,
		std::vector< TransformationDescription > &	transformations
	)

Align feature maps tree guided using align() of OpenMS::MapAlignmentAlgorithmIdentification and use TreeNode with larger 10/90 percentile range as reference.

◆ buildTree()

static void buildTree	(	std::vector< FeatureMap > &	feature_maps,
		std::vector< BinaryTreeNode > &	tree,
		std::vector< std::vector< double >> &	maps_ranges
	)

static

Extract RTs given for individual features of each map, calculate distances for each pair of maps and cluster hierarchical using average linkage.

Parameters

feature_maps	Vector of input maps (FeatureMap) whose distance is to be calculated.
tree	Vector of BinaryTreeNodes that will be computed
maps_ranges	Vector to store all sorted RTs of extracted identifications for each map in `feature_maps`; needed to determine the 10/90 percentiles

◆ computeTrafosByOriginalRT()

void computeTrafosByOriginalRT	(	std::vector< FeatureMap > &	feature_maps,
		FeatureMap &	map_transformed,
		std::vector< TransformationDescription > &	transformations,
		const std::vector< Size > &	trafo_order
	)

Extract original RT ("original_RT" MetaInfo) and transformed RT for each feature to compute RT transformations.

Parameters

feature_maps	Vector of input maps for size information.
map_transformed	FeatureMap that contains all features of combined maps with original and transformed RTs in order of alignment.
transformations	Vector to store transformation descriptions for each map. (output)
trafo_order	Vector that contains the indices of aligned maps in order of alignment.

◆ computeTransformedFeatureMaps()

static void computeTransformedFeatureMaps	(	std::vector< FeatureMap > &	feature_maps,
		const std::vector< TransformationDescription > &	transformations
	)

static

Apply transformations on input maps.

Parameters

feature_maps	Vector of maps to be transformed (output)
transformations	Vector that contains TransformationDescriptions that are applied to input maps

◆ extractSeqAndRt_()

static void extractSeqAndRt_	(	const std::vector< FeatureMap > &	feature_maps,
		std::vector< SeqAndRTList > &	maps_seq_and_rt,
		std::vector< std::vector< double >> &	maps_ranges
	)

staticprotected

For each input map, extract peptide identifications (sequences) of existing features with associated feature RT.

Parameters

feature_maps	Vector of original maps containing peptide identifications.
maps_seq_and_rt	Vector of maps to store feature RTs given for individual peptide sequences for each feature map.
maps_ranges	Vector to store all feature RTs of extracted identifications for each map; needed to determine the 10/90 percentiles.

◆ operator=()

MapAlignmentAlgorithmTreeGuided& operator= ( const MapAlignmentAlgorithmTreeGuided & )

private

Assignment operator intentionally not implemented -> private.

◆ treeGuidedAlignment()

void treeGuidedAlignment	(	const std::vector< BinaryTreeNode > &	tree,
		std::vector< FeatureMap > &	feature_maps_transformed,
		std::vector< std::vector< double >> &	maps_ranges,
		FeatureMap &	map_transformed,
		std::vector< Size > &	trafo_order
	)

Align feature maps tree guided using align() of OpenMS::MapAlignmentAlgorithmIdentification and use TreeNode with larger 10/90 percentile range as reference.

Parameters

tree	Vector of BinaryTreeNodes that contains order for alignment.
feature_maps_transformed	Vector with input maps for transformation process. Because the transformed maps are stored within this vector it's not const.
maps_ranges	Vector that contains all sorted RTs of extracted identifications for each map; needed to determine the 10/90 percentiles.
map_transformed	FeatureMap to store all features of combined maps with original and transformed RTs in order of alignment.
trafo_order	Vector to store indices of maps in order of alignment.

◆ 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

◆ align_algorithm_

MapAlignmentAlgorithmIdentification align_algorithm_

protected

Instantiation of alignment algorithm.

◆ model_param_

Param model_param_

protected

Default params of transformation models linear, b_spline, lowess and interpolated.

◆ model_type_

String model_type_

protected

Type of transformation model.

Public Member Functions

Static Public Member Functions

Protected Types

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Private Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ SeqAndRTList

Constructor & Destructor Documentation

◆ MapAlignmentAlgorithmTreeGuided() [1/2]

◆ ~MapAlignmentAlgorithmTreeGuided()

◆ MapAlignmentAlgorithmTreeGuided() [2/2]

Member Function Documentation

◆ addPeptideSequences_()

◆ align()

◆ buildTree()

◆ computeTrafosByOriginalRT()

◆ computeTransformedFeatureMaps()

◆ extractSeqAndRt_()

◆ operator=()

◆ treeGuidedAlignment()

◆ updateMembers_()

Member Data Documentation

◆ align_algorithm_

◆ model_param_

◆ model_type_