Calculates an FDR from identifications. More...

#include <OpenMS/ANALYSIS/ID/FalseDiscoveryRate.h>

Inheritance diagram for FalseDiscoveryRate:

Classes
struct	FalseFunctor

struct	GetLabelFunctor

struct	TrueFunctor

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

void	apply (std::vector< PeptideIdentification > &fwd_ids, std::vector< PeptideIdentification > &rev_ids) const
	Calculates the FDR of two runs, a forward run and a decoy run on peptide level. More...

void	apply (std::vector< PeptideIdentification > &id) const
	Calculates the FDR of one run from a concatenated sequence db search. More...

void	apply (std::vector< ProteinIdentification > &fwd_ids, std::vector< ProteinIdentification > &rev_ids) const
	Calculates the FDR of two runs, a forward run and decoy run on protein level. More...

void	apply (std::vector< ProteinIdentification > &ids) const
	Calculate the FDR of one run from a concatenated sequence db search. More...

void	applyEstimated (std::vector< ProteinIdentification > &ids) const
	Calculate the FDR based on PEPs pr PPs (if present) and modifies the IDs inplace. More...

double	applyEvaluateProteinIDs (const std::vector< ProteinIdentification > &ids, double pepCutoff=1.0, UInt fpCutoff=50, double diffWeight=0.2)
	Calculate a linear combination of the area of the difference in estimated vs. empirical (TD) FDR and the ROC-N value (AUC up to first N false positives). More...

double	applyEvaluateProteinIDs (const ProteinIdentification &ids, double pepCutoff=1.0, UInt fpCutoff=50, double diffWeight=0.2)

void	applyBasic (std::vector< PeptideIdentification > &ids)
	simpler reimplemetation of the apply function above. More...

void	applyBasic (ProteinIdentification &id, bool groups_too=true)

double	rocN (const std::vector< PeptideIdentification > &ids, Size fp_cutoff) const

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...

Private Member Functions
	FalseDiscoveryRate (const FalseDiscoveryRate &)
	Not implemented. More...

FalseDiscoveryRate &	operator= (const FalseDiscoveryRate &)
	Not implemented. More...

void	getScores_ (std::vector< std::pair< double, bool >> &scores_labels, const ProteinIdentification &id) const

void	getScores_ (std::vector< std::pair< double, bool >> &scores_labels, const std::vector< ProteinIdentification::ProteinGroup > &grps, const std::unordered_set< std::string > &decoy_accs) const

void	getScores_ (std::vector< std::pair< double, bool >> &scores_labels, const std::vector< PeptideIdentification > &ids, bool all_hits, int charge, String identifier) const

void	getScores_ (std::vector< std::pair< double, bool >> &scores_labels, const std::vector< PeptideIdentification > &targets, const std::vector< PeptideIdentification > &decoys, bool all_hits, int charge, const String &identifier) const

void	setScores_ (const std::map< double, double > &scores_to_FDR, std::vector< PeptideIdentification > &id, const std::string &score_type, bool higher_better) const

template<typename IDType >
void	setScores_ (const std::map< double, double > &scores_to_FDR, IDType &id, const std::string &score_type, bool higher_better) const

void	setScores_ (const std::map< double, double > &scores_to_FDR, std::vector< ProteinIdentification::ProteinGroup > &grps, const std::string &score_type, bool higher_better) const

template<typename IDType >
void	checkTDAnnotation_ (const IDType &id) const

template<typename HitType >
std::pair< double, bool >	getScoreLabel_ (const HitType &hit, std::function< bool(const HitType &)> fun) const

void	calculateFDRs_ (Map< double, double > &score_to_fdr, std::vector< double > &target_scores, std::vector< double > &decoy_scores, bool q_value, bool higher_score_better) const
	calculates the fdr given two vectors of scores and fills a map for lookup in scores_to_FDR More...

void	calculateEstimatedQVal_ (std::map< double, double > &scores_to_FDR, std::vector< std::pair< double, bool >> &scores_labels, bool higher_score_better) const

void	calculateFDRBasic_ (std::map< double, double > &scores_to_FDR, std::vector< std::pair< double, bool >> &scores_labels, bool qvalue, bool higher_score_better)
	calculates the FDR with a basic and faster algorithm More...

double	diffEstimatedEmpirical_ (const std::vector< std::pair< double, bool >> &scores_labels, double pepCutoff=1.0)
	calculates the area of the difference between estimated and empirical FDR on the fly. Does not store results. More...

double	rocN_ (std::vector< std::pair< double, bool >> const &scores_labels, Size fpCutoff=50) const

double	trapezoidal_area_xEqy (double exp1, double exp2, double act1, double act2) const

double	trapezoidal_area (double x1, double x2, double y1, double y2) const
	calculates the trapezoidal area for a trapezoid with a flat horizontal base e.g. for an AUC 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

Calculates an FDR from identifications.

Either two runs of forward and decoy database identification or one run containing both (with marks) can be used to annotate each of the peptide hits with a FDR.

Also q-values can be reported instead of p-values. q-values are basically only adjusted p-values, also ranging from 0 to 1, with lower values being preferable. When looking at the list of hits ordered by q-values, then a hit with q-value of x means that there is an x*100 percent chance that all hits with a q-value <= x are a false positive hit.

Todo:: implement combined searches properly (Andreas)

Improvement:: implement charge state separated fdr/q-values (Andreas)

Parameters of this class are:

Name	Type	Default	Restrictions	Description
no_qvalues	string	false	true, false	If 'true' strict FDRs will be calculated instead of q-values (the default)
use_all_hits	string	false	true, false	If 'true' not only the first hit, but all are used (peptides only)
split_charge_variants	string	false	true, false	If 'true' charge variants are treated separately (for peptides of combined target/decoy searches only).
treat_runs_separately	string	false	true, false	If 'true' different search runs are treated separately (for peptides of combined target/decoy searches only).
add_decoy_peptides	string	false	true, false	If 'true' decoy peptides will be written to output file, too. The q-value is set to the closest target score.
add_decoy_proteins	string	false	true, false	If 'true' decoy proteins will be written to output file, too. The q-value is set to the closest target score.

Note:

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

Constructor & Destructor Documentation

◆ FalseDiscoveryRate() [1/2]

FalseDiscoveryRate ( )

Default constructor.

◆ FalseDiscoveryRate() [2/2]

FalseDiscoveryRate ( const FalseDiscoveryRate & )

private

Not implemented.

Member Function Documentation

◆ apply() [1/4]

void apply	(	std::vector< PeptideIdentification > &	fwd_ids,
		std::vector< PeptideIdentification > &	rev_ids
	)		const

Calculates the FDR of two runs, a forward run and a decoy run on peptide level.

Parameters

fwd_ids	forward peptide identifications
rev_ids	reverse peptide identifications

Referenced by RNPxlSearch::main_().

◆ apply() [2/4]

void apply ( std::vector< PeptideIdentification > & id ) const

Calculates the FDR of one run from a concatenated sequence db search.

Parameters

id	peptide identifications, containing target and decoy hits

◆ apply() [3/4]

void apply	(	std::vector< ProteinIdentification > &	fwd_ids,
		std::vector< ProteinIdentification > &	rev_ids
	)		const

Calculates the FDR of two runs, a forward run and decoy run on protein level.

Parameters

fwd_ids	forward protein identifications
rev_ids	reverse protein identifications

◆ apply() [4/4]

void apply ( std::vector< ProteinIdentification > & ids ) const

Calculate the FDR of one run from a concatenated sequence db search.

Parameters

ids	protein identifications, containing target and decoy hits

◆ applyBasic() [1/2]

void applyBasic ( std::vector< PeptideIdentification > & ids )

simpler reimplemetation of the apply function above.

Referenced by TOPPBayesianProteinInference::main_(), and UTILProteomicsLFQ::main_().

◆ applyBasic() [2/2]

void applyBasic	(	ProteinIdentification &	id,
		bool	groups_too = `true`
	)

◆ applyEstimated()

void applyEstimated ( std::vector< ProteinIdentification > & ids ) const

Calculate the FDR based on PEPs pr PPs (if present) and modifies the IDs inplace.

Parameters

ids	protein identifications, containing PEP scores (not necessarily) annotated with target decoy.

◆ applyEvaluateProteinIDs() [1/2]

double applyEvaluateProteinIDs	(	const std::vector< ProteinIdentification > &	ids,
		double	pepCutoff = `1.0`,
		UInt	fpCutoff = `50`,
		double	diffWeight = `0.2`
	)

Calculate a linear combination of the area of the difference in estimated vs. empirical (TD) FDR and the ROC-N value (AUC up to first N false positives).

Parameters

ids	protein identifications, containing PEP scores annotated with target decoy. If vector, only first will be evaluated-
pepCutoff	up to which PEP should the differences between the two FDRs be calculated
fpCutoff	up to which nr. of false positives should the target-decoy AUC be evaluated
diffWeight	which weight should the difference get. The ROC-N value gets 1 - this weight.

◆ applyEvaluateProteinIDs() [2/2]

double applyEvaluateProteinIDs	(	const ProteinIdentification &	ids,
		double	pepCutoff = `1.0`,
		UInt	fpCutoff = `50`,
		double	diffWeight = `0.2`
	)

◆ calculateEstimatedQVal_()

void calculateEstimatedQVal_	(	std::map< double, double > &	scores_to_FDR,
		std::vector< std::pair< double, bool >> &	scores_labels,
		bool	higher_score_better
	)		const

private

calculates an estimated FDR (based on P(E)Ps) given a vector of score value pairs and fills a map for lookup in scores_to_FDR

◆ calculateFDRBasic_()

void calculateFDRBasic_	(	std::map< double, double > &	scores_to_FDR,
		std::vector< std::pair< double, bool >> &	scores_labels,
		bool	qvalue,
		bool	higher_score_better
	)

private

calculates the FDR with a basic and faster algorithm

◆ calculateFDRs_()

void calculateFDRs_	(	Map< double, double > &	score_to_fdr,
		std::vector< double > &	target_scores,
		std::vector< double > &	decoy_scores,
		bool	q_value,
		bool	higher_score_better
	)		const

private

calculates the fdr given two vectors of scores and fills a map for lookup in scores_to_FDR

◆ checkTDAnnotation_()

void checkTDAnnotation_ ( const IDType & id ) const

inlineprivate

◆ diffEstimatedEmpirical_()

double diffEstimatedEmpirical_	(	const std::vector< std::pair< double, bool >> &	scores_labels,
		double	pepCutoff = `1.0`
	)

private

calculates the area of the difference between estimated and empirical FDR on the fly. Does not store results.

◆ getScoreLabel_()

std::pair<double,bool> getScoreLabel_	(	const HitType &	hit,
		std::function< bool(const HitType &)>	fun
	)		const

inlineprivate

◆ getScores_() [1/4]

void getScores_	(	std::vector< std::pair< double, bool >> &	scores_labels,
		const ProteinIdentification &	id
	)		const

private

◆ getScores_() [2/4]

void getScores_	(	std::vector< std::pair< double, bool >> &	scores_labels,
		const std::vector< ProteinIdentification::ProteinGroup > &	grps,
		const std::unordered_set< std::string > &	decoy_accs
	)		const

private

◆ getScores_() [3/4]

void getScores_	(	std::vector< std::pair< double, bool >> &	scores_labels,
		const std::vector< PeptideIdentification > &	ids,
		bool	all_hits,
		int	charge,
		String	identifier
	)		const

private

◆ getScores_() [4/4]

void getScores_	(	std::vector< std::pair< double, bool >> &	scores_labels,
		const std::vector< PeptideIdentification > &	targets,
		const std::vector< PeptideIdentification > &	decoys,
		bool	all_hits,
		int	charge,
		const String &	identifier
	)		const

private

◆ operator=()

FalseDiscoveryRate& operator= ( const FalseDiscoveryRate & )

private

Not implemented.

◆ rocN()

double rocN	(	const std::vector< PeptideIdentification > &	ids,
		Size	fp_cutoff
	)		const

calculates the auc until the first fp_cutoff False positive pep IDs (currently only takes all runs together) if fp_cutoff = 0, it will calculate the full AUC

◆ rocN_()

double rocN_	(	std::vector< std::pair< double, bool >> const &	scores_labels,
		Size	fpCutoff = `50`
	)		const

private

calculates AUC of empirical FDR up to the first fpCutoff false positives on the fly. Does not store results. use e.g. fpCutoff = scores_labels.size() for complete AUC

◆ setScores_() [1/3]

void setScores_	(	const std::map< double, double > &	scores_to_FDR,
		std::vector< PeptideIdentification > &	id,
		const std::string &	score_type,
		bool	higher_better
	)		const

private

◆ setScores_() [2/3]

void setScores_	(	const std::map< double, double > &	scores_to_FDR,
		IDType &	id,
		const std::string &	score_type,
		bool	higher_better
	)		const

inlineprivate

◆ setScores_() [3/3]

void setScores_	(	const std::map< double, double > &	scores_to_FDR,
		std::vector< ProteinIdentification::ProteinGroup > &	grps,
		const std::string &	score_type,
		bool	higher_better
	)		const

private

◆ trapezoidal_area()

double trapezoidal_area	(	double	x1,
		double	x2,
		double	y1,
		double	y2
	)		const

private

calculates the trapezoidal area for a trapezoid with a flat horizontal base e.g. for an AUC

◆ trapezoidal_area_xEqy()

double trapezoidal_area_xEqy	(	double	exp1,
		double	exp2,
		double	act1,
		double	act2
	)		const

private

calculates the error area around the x=x line between two consecutive values of expected and actual i.e. it assumes exp2 > exp1

Classes

Public Member Functions

Private Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ FalseDiscoveryRate() [1/2]

◆ FalseDiscoveryRate() [2/2]

Member Function Documentation

◆ apply() [1/4]

◆ apply() [2/4]

◆ apply() [3/4]

◆ apply() [4/4]

◆ applyBasic() [1/2]

◆ applyBasic() [2/2]

◆ applyEstimated()

◆ applyEvaluateProteinIDs() [1/2]

◆ applyEvaluateProteinIDs() [2/2]

◆ calculateEstimatedQVal_()

◆ calculateFDRBasic_()

◆ calculateFDRs_()

◆ checkTDAnnotation_()

◆ diffEstimatedEmpirical_()

◆ getScoreLabel_()

◆ getScores_() [1/4]

◆ getScores_() [2/4]

◆ getScores_() [3/4]

◆ getScores_() [4/4]

◆ operator=()

◆ rocN()

◆ rocN_()

◆ setScores_() [1/3]

◆ setScores_() [2/3]

◆ setScores_() [3/3]

◆ trapezoidal_area()

◆ trapezoidal_area_xEqy()