MRMScoring#
- class pyopenms.MRMScoring#
Bases:
object
Cython implementation of _MRMScoring
Original C++ documentation is available here
- __init__()#
Overload:
- __init__(self) None
Overload:
- __init__(self, in_0: MRMScoring) None
Methods
Overload:
calcMIPrecursorScore
(self)calcMIScore
(self)calcMIWeightedScore
(self, ...)calcRTScore
(self, peptide, ...)Calculate the separate cross-correlation contrast score
Calculate the separate cross-correlation contrast shape score
calcXcorrCoelutionScore
(self)Calculate the cross-correlation coelution score.
calcXcorrCoelutionWeightedScore
(self, ...)Calculate the weighted cross-correlation coelution score
Calculate the precursor cross-correlation contrast score against the transitions
Calculate the precursor cross-correlation shape score against the transitions
calcXcorrShapeScore
(self)Calculate the cross-correlation shape score
calcXcorrShapeWeightedScore
(self, ...)Calculate the weighted cross-correlation shape score
getMIMatrix
(self)- calcMIPrecursorCombinedScore(self) float #
- calcMIPrecursorContrastScore(self) float #
- calcMIPrecursorScore(self) float #
- calcMIScore(self) float #
- calcMIWeightedScore(self, normalized_library_intensity: List[float]) float #
- calcRTScore(self, peptide: LightCompound, normalized_experimental_rt: float) float #
- calcSeparateMIContrastScore(self) List[float] #
- calcSeparateXcorrContrastCoelutionScore(self) List[float] #
Calculate the separate cross-correlation contrast score
- calcSeparateXcorrContrastShapeScore(self) List[float] #
Calculate the separate cross-correlation contrast shape score
- calcXcorrCoelutionScore(self) float #
Calculate the cross-correlation coelution score. The score is a distance where zero indicates perfect coelution
- calcXcorrCoelutionWeightedScore(self, normalized_library_intensity: List[float]) float #
Calculate the weighted cross-correlation coelution score
The score is a distance where zero indicates perfect coelution. The score is weighted by the transition intensities, non-perfect coelution in low-intensity transitions should thus become less important
- calcXcorrPrecursorContrastCoelutionScore(self) float #
Calculate the precursor cross-correlation contrast score against the transitions
The score is a distance where zero indicates perfect coelution
- calcXcorrPrecursorContrastShapeScore(self) float #
Calculate the precursor cross-correlation shape score against the transitions
- calcXcorrShapeScore(self) float #
Calculate the cross-correlation shape score
The score is a correlation measure where 1 indicates perfect correlation and 0 means no correlation.
- calcXcorrShapeWeightedScore(self, normalized_library_intensity: List[float]) float #
Calculate the weighted cross-correlation shape score
The score is a correlation measure where 1 indicates perfect correlation and 0 means no correlation. The score is weighted by the transition intensities, non-perfect coelution in low-intensity transitions should thus become less important
- getMIMatrix(self) MatrixDouble #