This class implements different precursor ion selection strategies. More...

#include <OpenMS/ANALYSIS/TARGETED/PrecursorIonSelection.h>

Inheritance diagram for PrecursorIonSelection:

Classes
struct	SeqTotalScoreMore
	Compare by score. More...
struct	TotalScoreMore
	Compare by score. More...
Public Types
enum	Type { IPS, ILP_IPS, SPS, UPSHIFT, DOWNSHIFT, DEX }
	Precursor ion selection type (iterative, static, upshift, downshift, dynamic exclusion). More...
Public Member Functions
	PrecursorIonSelection ()
	PrecursorIonSelection (const PrecursorIonSelection &source)
	~PrecursorIonSelection ()
const DoubleReal &	getMaxScore () const
void	setMaxScore (const DoubleReal &max_score)
void	sortByTotalScore (FeatureMap<> &features)
	Sort features by total score.
void	getNextPrecursors (FeatureMap<> &features, FeatureMap<> &next_features, UInt number)
	Returns features with highest score for MS/MS.
void	getNextPrecursorsSeq (FeatureMap<> &features, FeatureMap<> &next_features, UInt number, DoubleReal &rt)
void	getNextPrecursors (std::vector< Int > &solution_indices, std::vector< PSLPFormulation::IndexTriple > &variable_indices, std::set< Int > &measured_variables, FeatureMap<> &features, FeatureMap<> &new_features, UInt step_size, PSLPFormulation &ilp)
void	rescore (FeatureMap<> &features, std::vector< PeptideIdentification > &new_pep_ids, std::vector< ProteinIdentification > &prot_ids, PrecursorIonSelectionPreprocessing &preprocessed_db, bool check_meta_values=true)
	Change scoring of features using peptide identifications only from spectra of the last iteration.
void	simulateRun (FeatureMap<> &features, std::vector< PeptideIdentification > &pep_ids, std::vector< ProteinIdentification > &prot_ids, PrecursorIonSelectionPreprocessing &preprocessed_db, String path, MSExperiment<> &experiment, String precursor_path="")
	Simulate the iterative precursor ion selection.
void	setLPSolver (LPWrapper::SOLVER solver)
LPWrapper::SOLVER	getLPSolver ()
void	reset ()
const std::map< String, std::set< String > > &	getPeptideProteinCounter ()
Private Member Functions
void	simulateILPBasedIPSRun_ (FeatureMap<> &features, MSExperiment<> &experiment, std::vector< PeptideIdentification > &pep_ids, std::vector< ProteinIdentification > &prot_ids, PrecursorIonSelectionPreprocessing &preprocessed_db, String output_path, String precursor_path="")
void	simulateRun_ (FeatureMap<> &features, std::vector< PeptideIdentification > &pep_ids, std::vector< ProteinIdentification > &prot_ids, PrecursorIonSelectionPreprocessing &preprocessed_db, String path, String precursor_path="")
void	shiftDown_ (FeatureMap<> &features, PrecursorIonSelectionPreprocessing &preprocessed_db, String protein_acc)
void	shiftUp_ (FeatureMap<> &features, PrecursorIonSelectionPreprocessing &preprocessed_db, String protein_acc)
void	updateMembers_ ()
	update members method from DefaultParamHandler to update the members
void	rescore_ (FeatureMap<> &features, std::vector< PeptideIdentification > &new_pep_ids, PrecursorIonSelectionPreprocessing &preprocessed_db, PSProteinInference &protein_inference)
void	checkForRequiredUserParams_ (FeatureMap<> &features)
	Adds user params, required for the use of IPS, to a feature map using default values.
UInt	filterProtIds_ (std::vector< ProteinIdentification > &prot_ids)
	Groups protein identifications that cannot be distinguished by their peptide identifications.
std::vector < PeptideIdentification >	filterPeptideIds_ (std::vector< PeptideIdentification > &pep_ids)
void	convertPeptideIdScores_ (std::vector< PeptideIdentification > &pep_ids)
Private Attributes
UInt	min_pep_ids_
	minimal number of peptides identified for a protein to be declared identified
DoubleReal	max_score_
	maximal score in the FeatureMap
Type	type_
	precursor ion selection strategy
std::map< String, std::set < String > >	prot_id_counter_
	stores the peptide sequences for all protein identifications
std::vector< Size >	fraction_counter_
	stores the number of selected precursors per fraction
DoubleReal	mz_tolerance_
	precursor ion error tolerance
String	mz_tolerance_unit_
	precursor ion error tolerance unit (ppm or Da)
UInt	max_iteration_
	maximal number of iterations
Size	x_variable_number_
LPWrapper::SOLVER	solver_

Detailed Description

This class implements different precursor ion selection strategies.

Parameters of this class are:

Name	Type	Default	Restrictions	Description
type	string	IPS	ILP_IPS, IPS, SPS, Upshift, Downshift, DEX	Strategy for precursor ion selection.
max_iteration	int	100	min: 1	Maximal number of iterations.
rt_bin_capacity	int	10	min: 1	Maximal number of precursors per rt bin.
step_size	int	1	min: 1	Maximal number of precursors per iteration.
peptide_min_prob	float	0.2		Minimal peptide probability.
sequential_spectrum_order	string	false	true, false	If true, precursors are selected sequentially with respect to their RT.
MIPFormulation:thresholds:min_protein_probability	float	0.2	min: 0 max: 1	Minimal protein probability for a protein to be considered in the ILP
MIPFormulation:thresholds:min_protein_id_probability	float	0.95	min: 0 max: 1	Minimal protein probability for a protein to be considered identified.
MIPFormulation:thresholds:min_pt_weight	float	0.5	min: 0 max: 1	Minimal pt weight of a precursor
MIPFormulation:thresholds:min_mz	float	500	min: 0	Minimal mz to be considered in protein based LP formulation.
MIPFormulation:thresholds:max_mz	float	5000	min: 0	Minimal mz to be considered in protein based LP formulation.
MIPFormulation:thresholds:min_pred_pep_prob	float	0.5	min: 0 max: 1	Minimal predicted peptide probability of a precursor
MIPFormulation:thresholds:min_rt_weight	float	0.5	min: 0 max: 1	Minimal rt weight of a precursor
MIPFormulation:thresholds:use_peptide_rule	string	false	true, false	Use peptide rule instead of minimal protein id probability
MIPFormulation:thresholds:min_peptide_ids	int	2	min: 1	If use_peptide_rule is true, this parameter sets the minimal number of peptide ids for a protein id
MIPFormulation:thresholds:min_peptide_probability	float	0.95	min: 0 max: 1	If use_peptide_rule is true, this parameter sets the minimal probability for a peptide to be safely identified
MIPFormulation:combined_ilp:k1	float	0.2	min: 0	combined ilp: weight for z_i
MIPFormulation:combined_ilp:k2	float	0.2	min: 0	combined ilp: weight for x_j,s*int_j,s
MIPFormulation:combined_ilp:k3	float	0.4	min: 0	combined ilp: weight for -x_j,s*w_j,s
MIPFormulation:combined_ilp:scale_matching_probs	string	true	true, false	flag if detectability * rt_weight shall be scaled to cover all [0,1]
Preprocessing:precursor_mass_tolerance	float	10	min: 0	Precursor mass tolerance which is used to query the peptide database for peptides
Preprocessing:precursor_mass_tolerance_unit	string	ppm	ppm, Da	Precursor mass tolerance unit.
Preprocessing:preprocessed_db_path	string			Path where the preprocessed database should be stored
Preprocessing:preprocessed_db_pred_rt_path	string			Path where the predicted rts of the preprocessed database should be stored
Preprocessing:preprocessed_db_pred_dt_path	string			Path where the predicted rts of the preprocessed database should be stored
Preprocessing:max_peptides_per_run	int	100000	min: 1	Number of peptides for that the pt and rt are parallely predicted.
Preprocessing:missed_cleavages	int	1	min: 0	Number of allowed missed cleavages.
Preprocessing:taxonomy	string			Taxonomy
Preprocessing:tmp_dir	string			Absolute path to tmp data directory used to store files needed for rt and dt prediction.
Preprocessing:store_peptide_sequences	string	false		Flag if peptide sequences should be stored.
Preprocessing:rt_settings:min_rt	float	960	min: 1	Minimal RT in the experiment (in seconds)
Preprocessing:rt_settings:max_rt	float	3840		Maximal RT in the experiment (in seconds)
Preprocessing:rt_settings:rt_step_size	float	30		Time between two consecutive spectra (in seconds)
Preprocessing:rt_settings:gauss_mean	float	-1		mean of the gauss curve
Preprocessing:rt_settings:gauss_sigma	float	3		std of the gauss curve

Note:

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

Member Enumeration Documentation

enum Type

Precursor ion selection type (iterative, static, upshift, downshift, dynamic exclusion).

The iterative strategy changes the ranking of possible precursors based on identification results from previous iterations.

The upshift strategy assigns a higher priority to precursors whose masses are matching peptide masses of potential protein identifications to enable a safe identification in the next iterations.

The downshift strategy assigns a lower priority to precursors whose masses are matching peptide masses of safe protein identifications.

The dynamic exclusion exludes precursors whose masses are matching peptide masses of safe protein identifications.

The static selection uses precomputed scores to rank the precursor, the order of precursors isn't changed throughout the run.

Enumerator:

IPS
ILP_IPS
SPS
UPSHIFT
DOWNSHIFT
DEX

Constructor & Destructor Documentation

PrecursorIonSelection ( )

PrecursorIonSelection ( const PrecursorIonSelection & source )

~PrecursorIonSelection ( )

Member Function Documentation

void checkForRequiredUserParams_ ( FeatureMap<> & features ) [private]

Adds user params, required for the use of IPS, to a feature map using default values.

Parameters:

features

FeatureMap with all possible precursors

void convertPeptideIdScores_ ( std::vector< PeptideIdentification > & pep_ids ) [private]

std::vector<PeptideIdentification> filterPeptideIds_ ( std::vector< PeptideIdentification > & pep_ids ) [private]

UInt filterProtIds_ ( std::vector< ProteinIdentification > & prot_ids ) [private]

Groups protein identifications that cannot be distinguished by their peptide identifications.

Parameters:

prot_ids

All protein identifications.

LPWrapper::SOLVER getLPSolver ( ) [inline]

const DoubleReal& getMaxScore ( ) const

void getNextPrecursors	(	FeatureMap<> &	features,
		FeatureMap<> &	next_features,
		UInt	number
	)

Returns features with highest score for MS/MS.

Parameters:

	features	FeatureMap with all possible precursors
	next_features	FeatureMap with next precursors
	number	Number of features to be reported

void getNextPrecursors	(	std::vector< Int > &	solution_indices,
		std::vector< PSLPFormulation::IndexTriple > &	variable_indices,
		std::set< Int > &	measured_variables,
		FeatureMap<> &	features,
		FeatureMap<> &	new_features,
		UInt	step_size,
		PSLPFormulation &	ilp
	)

void getNextPrecursorsSeq	(	FeatureMap<> &	features,
		FeatureMap<> &	next_features,
		UInt	number,
		DoubleReal &	rt
	)

const std::map<String, std::set<String> >& getPeptideProteinCounter ( ) [inline]

void rescore	(	FeatureMap<> &	features,
		std::vector< PeptideIdentification > &	new_pep_ids,
		std::vector< ProteinIdentification > &	prot_ids,
		PrecursorIonSelectionPreprocessing &	preprocessed_db,
		bool	check_meta_values = `true`
	)

Change scoring of features using peptide identifications only from spectra of the last iteration.

Parameters:

	features	FeatureMap with all possible precursors
	new_pep_ids	Peptide identifications
	preprocessed_db	Information from preprocessed database Change scoring of features using peptide identifications from all spectra.
	features	FeatureMap with all possible precursors
	new_pep_ids	Peptide identifications
	prot_ids	Protein identifications
	preprocessed_db	Information from preprocessed database
	check_meta_values	True if the FeatureMap should be checked for the presence of required meta values

void rescore_	(	FeatureMap<> &	features,
		std::vector< PeptideIdentification > &	new_pep_ids,
		PrecursorIonSelectionPreprocessing &	preprocessed_db,
		PSProteinInference &	protein_inference
	)			`[private]`

void reset ( )

void setLPSolver ( LPWrapper::SOLVER solver ) [inline]

void setMaxScore ( const DoubleReal & max_score )

void shiftDown_	(	FeatureMap<> &	features,
		PrecursorIonSelectionPreprocessing &	preprocessed_db,
		String	protein_acc
	)			`[private]`

void shiftUp_	(	FeatureMap<> &	features,
		PrecursorIonSelectionPreprocessing &	preprocessed_db,
		String	protein_acc
	)			`[private]`

void simulateILPBasedIPSRun_	(	FeatureMap<> &	features,
		MSExperiment<> &	experiment,
		std::vector< PeptideIdentification > &	pep_ids,
		std::vector< ProteinIdentification > &	prot_ids,
		PrecursorIonSelectionPreprocessing &	preprocessed_db,
		String	output_path,
		String	precursor_path = `""`
	)			`[private]`

void simulateRun	(	FeatureMap<> &	features,
		std::vector< PeptideIdentification > &	pep_ids,
		std::vector< ProteinIdentification > &	prot_ids,
		PrecursorIonSelectionPreprocessing &	preprocessed_db,
		String	path,
		MSExperiment<> &	experiment,
		String	precursor_path = `""`
	)

Simulate the iterative precursor ion selection.

Parameters:

	features	FeatureMap with all possible precursors
	pep_ids	Peptide identifications
	prot_ids	Protein identifications
	preprocessed_db	Information from preprocessed database
	step_size	Number of MS/MS spectra considered per iteration
	path	Path to output file

void simulateRun_	(	FeatureMap<> &	features,
		std::vector< PeptideIdentification > &	pep_ids,
		std::vector< ProteinIdentification > &	prot_ids,
		PrecursorIonSelectionPreprocessing &	preprocessed_db,
		String	path,
		String	precursor_path = `""`
	)			`[private]`