massdash.structs.TransitionGroupFeature
- class massdash.structs.TransitionGroupFeature(leftBoundary: float, rightBoundary: float, areaIntensity: float | None = None, qvalue: float | None = None, consensusApex: float | None = None, consensusApexIntensity: float | None = None, consensusApexIM: float | None = None, precursor_mz: float | None = None, precursor_charge: int | None = None, product_annotations: List[str] | None = None, product_mz: List[float] | None = None, sequence: str | None = None, software: Literal['DIA-NN', 'OpenSWATH', 'DreamDIA'] | None = None)
Bases:
GenericFeatureAn object storing attributes on the detected feature in a TransitionGroup. All Peak Picking algorithms should output an object of this class
- leftBoundary
The left boundary of the feature
- Type:
float
- rightBoundary
The right boundary of the feature
- Type:
float
- areaIntensity
The area intensity of the feature
- Type:
float
- qvalue
The qvalue of the feature
- Type:
float
- consensusApex
The consensus apex of the feature
- Type:
float
- consensusApexIntensity
The consensus apex intensity of the feature
- Type:
float
- consensusApexIM
The consensus apex IM of the feature
- Type:
float
- precursor_mz
The precursor mz of the feature
- Type:
float
- precursor_charge
The precursor charge of the feature
- Type:
int
- product_annotations
The product annotations of the feature
- Type:
List[str]
- product_mz
The product mz of the feature
- Type:
List[float]
- sequence
The sequence of the feature
- Type:
str
- getBoundaries() Tuple[float, float]
Returns the boundaries of the feature
- static toPandasDf(transitionGroupFeatureLst: List[TransitionGroupFeature]) DataFrame
Convert a list of TransitionGroupFeature objects to a pandas dataframe