PrecursorPurity

class pyopenms.PrecursorPurity

Bases: object

Cython implementation of _PrecursorPurity

Documentation is available at http://www.openms.de/current_doxygen/html/classOpenMS_1_1PrecursorPurity.html

This class computes metrics for precursor isolation window purity (or noise) The function extracts the peaks from an isolation window targeted for fragmentation and determines which peaks are isotopes of the target and which come from other sources The intensities of the assumed target peaks are summed up as the target intensity Using this information it calculates an intensity ratio for the relative intensity of the target compared to other sources These metrics are combined over the previous and the next MS1 spectrum

__init__()

• Cython signature: void PrecursorPurity()

• Cython signature: void PrecursorPurity(PrecursorPurity &)

Methods

__init__	Cython signature: void PrecursorPurity()
computePrecursorPurity	Cython signature: PurityScores computePrecursorPurity(MSSpectrum ms1, Precursor pre, double precursor_mass_tolerance, bool precursor_mass_tolerance_unit_ppm)

computePrecursorPurity()

Cython signature: PurityScores computePrecursorPurity(MSSpectrum ms1, Precursor pre, double precursor_mass_tolerance, bool precursor_mass_tolerance_unit_ppm)

Note: This function is implemented in a general way and can also be used for e.g. MS3 precursor isolation windows in MS2 spectra Spectra annotated with charge 0 will be treated as charge 1. —– :param ms1: The Spectrum containing the isolation window :param pre: The precursor containing the definition the isolation window :param precursor_mass_tolerance: The precursor tolerance. Is used for determining the targeted peak and deisotoping :param precursor_mass_tolerance_unit_ppm: The unit of the precursor tolerance