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PeakIntensityPredictor Class Reference
[Analysis]

Predict peak heights of peptides based on Local Linear Map model. More...

#include <OpenMS/ANALYSIS/PIP/PeakIntensityPredictor.h>

List of all members.

Public Member Functions

DoubleReal predict (const AASequence &sequence)
 Returns predicted peak heights (intensites) of a single peptide.
DoubleReal predict (const AASequence &sequence, std::vector< DoubleReal > &add_info)
 Returns predicted peak heights (intensites) of a single peptide.
std::vector< DoubleRealpredict (const std::vector< AASequence > &sequences)
 Returns predicted peak heights (intensites) of several peptides.
std::vector< DoubleRealpredict (const std::vector< AASequence > &sequences, std::vector< std::vector< DoubleReal > > &add_info)
 Returns predicted peak heights (intensites) of several peptides.

 PeakIntensityPredictor ()
 Constructors and Destructors.
virtual ~PeakIntensityPredictor ()
 destructor

Private Member Functions

DoubleReal map_ (const std::vector< DoubleReal > &data)
 calculate and return predicted value based on given LocalLinearMap model for corresponding aaindex variables
Size findWinner_ (const std::vector< DoubleReal > &data)
 find winning prototype
std::vector< DoubleRealcalculateAddInfo_ (const std::vector< DoubleReal > &data)
 calculate assignments of peptides to cluster and the corresponding error
std::vector< DoubleRealgetPropertyVector_ (const AASequence &sequence)
 Calculates an array of properties for an amino acid sequence.
 PeakIntensityPredictor (const PeakIntensityPredictor &llmModel)
 copy constructor not impemented => private
PeakIntensityPredictoroperator= (const PeakIntensityPredictor &peakIntensityPredictor)
 assignment operator not impemented => private

Private Attributes

LocalLinearMap llm_
 Local Linear Map model.

Detailed Description

Predict peak heights of peptides based on Local Linear Map model.

This class can be used for predictions of peptide peak heights (referred to as intensities) from a peptide sequence by a Local Linear Map (LLM) model. A general introduction to the Peak Intensity Predictor (PIP) can be found in the PIP Tutorial.

The predictor performs only on the peptides sequences as an AASequence representation. Every sequence is transformed to an 18 dimensional data vector representing certain chemical characteristics and is loaded into the trained LocalLinearMap model to find the predicted peptides peak intensity.

Every predictor object calls the appropriate LocalLinearMap model, transforms the given sequences and creates a vector space in which the LocalLinearMap performs.


Constructor & Destructor Documentation

Constructors and Destructors.

default constructor

virtual ~PeakIntensityPredictor (  )  [virtual]

destructor

PeakIntensityPredictor ( const PeakIntensityPredictor llmModel  )  [private]

copy constructor not impemented => private


Member Function Documentation

std::vector<DoubleReal> calculateAddInfo_ ( const std::vector< DoubleReal > &  data  )  [private]

calculate assignments of peptides to cluster and the corresponding error

Size findWinner_ ( const std::vector< DoubleReal > &  data  )  [private]

find winning prototype

std::vector<DoubleReal> getPropertyVector_ ( const AASequence sequence  )  [private]

Calculates an array of properties for an amino acid sequence.

The array contains the following properties:

  • 0: Number of 'R' residues
  • 1: Signal sequence helical potential
  • 2: Number of 'F' residues
  • 3: Positive charge
  • 4: Helix-coil equilibrium constant
  • 5: Estimated gas-phase basicity at 500 K
  • 6: Number of 'H' residues
  • 7: Kerr-constant increments
  • 8: Number of 'M' residues
  • 9: Average amino acid weight
  • 10: Hydropathy scale (36% accessibility)
  • 11: Hydropathy scale (50% accessibility)
  • 12: Optimized average non-bonded energy per atom
  • 13: Number of 'Q' residues
  • 14: Information measure for extended without H-bond
  • 15: Relative population of conformational state E
  • 16: Hydrophobicity coefficient in RP-HPLC, C8 with 0.1TFA/MeCN/H2 O,
  • 17: Number of 'Y' residues
Exceptions:
InvalidValue is thrown if an undefined one-letter-code is used
DoubleReal map_ ( const std::vector< DoubleReal > &  data  )  [private]

calculate and return predicted value based on given LocalLinearMap model for corresponding aaindex variables

PeakIntensityPredictor& operator= ( const PeakIntensityPredictor peakIntensityPredictor  )  [private]

assignment operator not impemented => private

DoubleReal predict ( const AASequence sequence,
std::vector< DoubleReal > &  add_info 
)

Returns predicted peak heights (intensites) of a single peptide.

Some additional information is returned in add_info :

  • 0: x coordinates of associated cluster (first column)
  • 1: y coordinates of associated cluster (2nd column)
  • 2: error (RMSE) of the peptide to the associated next prototype (cluster center)
std::vector<DoubleReal> predict ( const std::vector< AASequence > &  sequences,
std::vector< std::vector< DoubleReal > > &  add_info 
)

Returns predicted peak heights (intensites) of several peptides.

Some additional information foreach peptide is returned in add_info . For each peptide a row with the following components is returned:

  • 0: x coordinates of associated cluster (first column)
  • 1: y coordinates of associated cluster (2nd column)
  • 2: error (RMSE) of the peptide to the associated next prototype (cluster center)
DoubleReal predict ( const AASequence sequence  ) 

Returns predicted peak heights (intensites) of a single peptide.

std::vector<DoubleReal> predict ( const std::vector< AASequence > &  sequences  ) 

Returns predicted peak heights (intensites) of several peptides.


Member Data Documentation

LocalLinearMap llm_ [private]

Local Linear Map model.


OpenMS / TOPP release 1.10.0 Documentation generated on Thu Mar 7 2013 09:42:50 using doxygen 1.7.1