This class implements the simulation of the spectra from PILIS. More...

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

Inheritance diagram for PILISNeutralLossModel:

Public Member Functions
PILISNeutralLossModel &	operator= (const PILISNeutralLossModel &mode)
	assignment operator
Constructors and destructors

	PILISNeutralLossModel ()
	default constructor
	PILISNeutralLossModel (const PILISNeutralLossModel &model)
	copy constructor
virtual	~PILISNeutralLossModel ()
	destructor
Accessors

DoubleReal	train (const RichPeakSpectrum &spec, const AASequence &peptide, DoubleReal ion_weight, UInt charge, DoubleReal peptide_weight)
	performs a training step; needs as parameters a spectrum with annotated sequence and charge; returns the intensity sum of the matched peaks
void	getIons (std::vector< RichPeak1D > &peaks, const AASequence &peptide, DoubleReal initial_prob)
	given a peptide (a ion) the model returns the peaks with intensities relative to initial_prob
void	setHMM (const HiddenMarkovModel &model)
	sets the hidden markov model
const HiddenMarkovModel &	getHMM () const
	writes the HMM to the given file in the GraphML format. A detailed description of the GraphML format can be found under http://graphml.graphdrawing.org/
void	generateModel ()
	generates the models
void	evaluate ()
	this method evaluates the model after training; it should be called after all training steps with train
Protected Member Functions
DoubleReal	getIntensitiesFromSpectrum_ (const RichPeakSpectrum &train_spec, Map< String, DoubleReal > &pre_ints, DoubleReal ion_weight, const AASequence &peptide, UInt charge)
	extracts the precursor and related intensities of a training spectrum
void	trainIons_ (DoubleReal initial_probability, const Map< String, DoubleReal > &intensities, const AASequence &peptide)
	trains precursor and related peaks
void	getIons_ (Map< String, DoubleReal > &intensities, DoubleReal initial_probability, const AASequence &precursor)
	estimates the precursor intensities
void	enableIonStates_ (const AASequence &peptide)
	enables the states needed for precursor training/simulation
void	updateMembers_ ()
	This method is used to update extra member variables at the end of the setParameters() method.
Protected Attributes
HiddenMarkovModel	hmm_precursor_
	precursor model used
UInt	num_explicit_
Friends
class	PILISNeutralLossModelGenerator

Detailed Description

This class implements the simulation of the spectra from PILIS.

PILIS uses a HMM based structure to model the population of fragment ions from a peptide. The spectrum generator can be accessed via the getSpectrum method.

Parameters of this class are:

Name	Type	Default	Restrictions	Description
fragment_mass_tolerance	float	0.4		Peak mass tolerance of the product ions, used to identify the ions for training
fixed_modifications	string list	[]		Fixed modifications
variable_modifications	string list	[]		Variable modifications
pseudo_counts	float	1e-15		Value which is added for every transition trained of the underlying hidden Markov model
num_explicit	int	2		Number of explicitly modeled losses from the same kind of amino acid or combinations thereof
min_int_to_train	float	0.1		Minimal intensity a ion and its losses must have to be considered for training.
C_term_H2O_loss	string	true	true, false	enable water loss of the C-terminus
ion_name	string	p	p, a, b, b2, y	Ion base names used to set in meta values
enable_double_losses	string	true	true, false	if true, two different losses can occur at the same time, e.g. -H2O and -NH3 forming loss of -35Da

Note:

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

Constructor & Destructor Documentation

PILISNeutralLossModel ( )

default constructor

PILISNeutralLossModel ( const PILISNeutralLossModel & model )

copy constructor

virtual ~PILISNeutralLossModel ( ) [virtual]

destructor

Member Function Documentation

void enableIonStates_ ( const AASequence & peptide ) [protected]

enables the states needed for precursor training/simulation

void evaluate ( )

this method evaluates the model after training; it should be called after all training steps with train

void generateModel ( )

generates the models

const HiddenMarkovModel& getHMM ( ) const

writes the HMM to the given file in the GraphML format. A detailed description of the GraphML format can be found under http://graphml.graphdrawing.org/

DoubleReal getIntensitiesFromSpectrum_	(	const RichPeakSpectrum &	train_spec,
		Map< String, DoubleReal > &	pre_ints,
		DoubleReal	ion_weight,
		const AASequence &	peptide,
		UInt	charge
	)			`[protected]`

extracts the precursor and related intensities of a training spectrum

void getIons	(	std::vector< RichPeak1D > &	peaks,
		const AASequence &	peptide,
		DoubleReal	initial_prob
	)

given a peptide (a ion) the model returns the peaks with intensities relative to initial_prob

void getIons_	(	Map< String, DoubleReal > &	intensities,
		DoubleReal	initial_probability,
		const AASequence &	precursor
	)			`[protected]`

estimates the precursor intensities

PILISNeutralLossModel& operator= ( const PILISNeutralLossModel & mode )

assignment operator

void setHMM ( const HiddenMarkovModel & model )

sets the hidden markov model

DoubleReal train	(	const RichPeakSpectrum &	spec,
		const AASequence &	peptide,
		DoubleReal	ion_weight,
		UInt	charge,
		DoubleReal	peptide_weight
	)

performs a training step; needs as parameters a spectrum with annotated sequence and charge; returns the intensity sum of the matched peaks

void trainIons_	(	DoubleReal	initial_probability,
		const Map< String, DoubleReal > &	intensities,
		const AASequence &	peptide
	)			`[protected]`

trains precursor and related peaks

void updateMembers_ ( ) [protected, virtual]

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.

Friends And Related Function Documentation

friend class PILISNeutralLossModelGenerator [friend]

Member Data Documentation

HiddenMarkovModel hmm_precursor_ [protected]

precursor model used

UInt num_explicit_ [protected]

OpenMS / TOPP release 1.10.0

Documentation generated on Thu Mar 7 2013 09:42:49 using doxygen 1.7.1

PILISNeutralLossModel Class Reference [Identification]

Public Member Functions

Protected Member Functions

Protected Attributes

Friends

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Friends And Related Function Documentation

Member Data Documentation

PILISNeutralLossModel Class Reference
[Identification]