Similarity score based of Stein & Scott. More...
#include <OpenMS/COMPARISON/SPECTRA/SteinScottImproveScore.h>
Public Member Functions | |
| SteinScottImproveScore () | |
| default constructor | |
| SteinScottImproveScore (const SteinScottImproveScore &source) | |
| copy constructor | |
| virtual | ~SteinScottImproveScore () |
| destructor | |
| SteinScottImproveScore & | operator= (const SteinScottImproveScore &source) |
| assignment operator | |
| double | operator() (const PeakSpectrum &spec1, const PeakSpectrum &spec2) const |
| Similarity pairwise score. | |
| double | operator() (const PeakSpectrum &spec) const |
| Similarity pairwise score itself. | |
Static Public Member Functions | |
| static PeakSpectrumCompareFunctor * | create () |
| static const String | getProductName () |
Similarity score based of Stein & Scott.
This is a pairwise based score function. The spectrum contains peaks, and each peak can be defined by two values (mz and the intensity). The score function takes the sum of the product of the peak intensities from Spectrum 1 and Spectrum 2, only if the mz-ratio distance between the two spectrums is smaller than a given window size. In the default status, the window size is (accuracy of the mass spectrometer). This sum is normalised by dividing it with a distance function. sqrt(sum of the Intensity of square Spectrum1 sum of the Intensity of square Spectrum2). This is all based on SteinScott score. To distinguish the close from the distant spectra an additional term is calculated. It denotes the expected value of both Spectrums under the random placement of all peaks, within the given mass-to-charge range. The probability that two peaks with randomized intensity values lie within two epsilon of each other is a constant. This constant is proportional to epsilon. So the additional term is the sum over all peaks of Spectrum 1 and Spectrum 2 of the products of their intensities multiplied with the constant.
The details of the score can be found in: Signal Maps for Mass Spectrometry-based Comparative Proteomics Amol Prakash, Parag Mallick , Jeffrey Whiteaker, Heidi Zhang, Amanda Paulovich, Mark Flory, Hookeun Lee, Ruedi Aebersold, and Benno Schwikowski
Parameters of this class are:| Name | Type | Default | Restrictions | Description |
|---|---|---|---|---|
| tolerance | float | 0.2 | defines the absolute error of the mass spectrometer | |
| threshold | float | 0.2 | if the calculated score is smaller than the threshold, a zero is given back |
default constructor
| SteinScottImproveScore | ( | const SteinScottImproveScore & | source | ) |
copy constructor
| virtual ~SteinScottImproveScore | ( | ) | [virtual] |
destructor
| static PeakSpectrumCompareFunctor* create | ( | ) | [inline, static] |
| static const String getProductName | ( | ) | [inline, static] |
Reimplemented from PeakSpectrumCompareFunctor.
| double operator() | ( | const PeakSpectrum & | spec1, | |
| const PeakSpectrum & | spec2 | |||
| ) | const [virtual] |
Similarity pairwise score.
This function return the similarity score of two Spectrums based on SteinScott.
Implements PeakSpectrumCompareFunctor.
| double operator() | ( | const PeakSpectrum & | spec | ) | const [virtual] |
Similarity pairwise score itself.
This function return the similarity score of itself based on SteinScott.
Implements PeakSpectrumCompareFunctor.
| SteinScottImproveScore& operator= | ( | const SteinScottImproveScore & | source | ) |
assignment operator
| OpenMS / TOPP release 1.10.0 | Documentation generated on Thu Mar 7 2013 09:42:51 using doxygen 1.7.1 |