CoarseIsotopePatternGenerator

class pyopenms.CoarseIsotopePatternGenerator

Bases: object

Cython implementation of _CoarseIsotopePatternGenerator

Original C++ documentation is available here

__init__()

Overload:

__init__(self) → None

Overload:

__init__(self, max_isotope: int) → None

Overload:

__init__(self, max_isotope: int, round_masses: bool) → None

Methods

`__init__`	Overload:
`approximateFromPeptideWeight`(self, mass, ...)	Roughly approximate peptide IsotopeDistribution from monoisotopic weight using Poisson distribution.
`approximateIntensities`(self, mass, num_peaks)	Roughly approximate peptidic isotope pattern intensities from monoisotopic weight using Poisson distribution.
`calcFragmentIsotopeDist`(self, ...)	Calculate isotopic distribution for a fragment molecule
`estimateForFragmentFromDNAWeight`(self, ...)	Estimate DNA fragment IsotopeDistribution from the precursor's average weight, fragment's average weight, and a set of isolated precursor isotopes.
`estimateForFragmentFromPeptideWeight`(self, ...)	Estimate peptide fragment IsotopeDistribution from the precursor's average weight, fragment's average weight, and a set of isolated precursor isotopes
`estimateForFragmentFromPeptideWeightAndS`(...)	Estimate peptide fragment IsotopeDistribution from the precursor's average weight, number of sulfurs in the precursor, fragment's average weight, number of sulfurs in the fragment, and a set of isolated precursor isotopes.
`estimateForFragmentFromRNAWeight`(self, ...)	Estimate RNA fragment IsotopeDistribution from the precursor's average weight, fragment's average weight, and a set of isolated precursor isotopes
`estimateForFragmentFromWeightAndComp`(self, ...)	Estimate fragment IsotopeDistribution from the precursor's average weight, fragment's average weight, a set of isolated precursor isotopes, and average composition
`estimateFromDNAWeight`(self, average_weight)	Estimate Nucleotide Isotopedistribution from weight
`estimateFromPeptideWeight`(self, average_weight)	Estimate Peptide Isotopedistribution from weight and number of isotopes that should be reported
`estimateFromPeptideWeightAndS`(self, ...)	Estimate peptide IsotopeDistribution from average weight and exact number of sulfurs
`estimateFromRNAWeight`(self, average_weight)	Estimate Nucleotide Isotopedistribution from weight
`estimateFromWeightAndComp`(self, ...)
`estimateFromWeightAndCompAndS`(self, ...)	Estimate IsotopeDistribution from weight, exact number of sulfurs, and average remaining composition
`getMaxIsotope`(self)	Returns the currently set maximum isotope
`getRoundMasses`(self)	Returns the current value of the flag to round masses to integer values (true) or return accurate masses (false)
`run`(self, in_0)
`setMaxIsotope`(self, max_isotope)	Sets the maximal isotope with 'max_isotope'
`setRoundMasses`(self, round_masses_)	Sets the round_masses_ flag to round masses to integer values (true) or return accurate masses (false)

approximateFromPeptideWeight(self, mass: float, num_peaks: int, charge: int) → IsotopeDistribution: Roughly approximate peptide IsotopeDistribution from monoisotopic weight using Poisson distribution. m/z values approximated by adding one neutron mass (divided by charge) for every peak, starting at the given monoisotopic weight. Foundation from: Bellew et al, https://dx.doi.org/10.1093/bioinformatics/btl276 This method is around 50 times faster than estimateFromPeptideWeight, but only an approximation. The following are the intensities of the first 6 peaks generated for a monoisotopic mass of 1000: estimateFromPeptideWeight: 0.571133000;0.306181000;0.095811100;0.022036900;0.004092170;0.000644568 approximateFromPeptideWeight: 0.573753000;0.318752000;0.088542200;0.016396700;0.002277320;0.000253036 KL divergences of the first 20 intensities of estimateFromPeptideWeight and this approximation range from 4.97E-5 for a monoisotopic mass of 20 to 0.0144 for a mass of 2500. For comparison, when comparing an observed pattern with a theoretical ground truth, the observed pattern is said to be an isotopic pattern if the KL between the two is below 0.05 for 2 peaks and below 0.6 for >=6 peaks by Guo Ci Teo et al.

approximateIntensities(self, mass: float, num_peaks: int) → List[float]: Roughly approximate peptidic isotope pattern intensities from monoisotopic weight using Poisson distribution. Foundation from: Bellew et al, https://dx.doi.org/10.1093/bioinformatics/btl276 This method is around 100 times faster than estimateFromPeptideWeight, but only an approximation, see approximateFromPeptideWeight.

calcFragmentIsotopeDist(self, fragment_isotope_dist: IsotopeDistribution, comp_fragment_isotope_dist: IsotopeDistribution, precursor_isotopes: Set[int], fragment_mono_mass: float) → IsotopeDistribution: Calculate isotopic distribution for a fragment molecule

estimateForFragmentFromDNAWeight(self, average_weight_precursor: float, average_weight_fragment: float, precursor_isotopes: Set[int]) → IsotopeDistribution: Estimate DNA fragment IsotopeDistribution from the precursor’s average weight, fragment’s average weight, and a set of isolated precursor isotopes.

estimateForFragmentFromPeptideWeight(self, average_weight_precursor: float, average_weight_fragment: float, precursor_isotopes: Set[int]) → IsotopeDistribution: Estimate peptide fragment IsotopeDistribution from the precursor’s average weight, fragment’s average weight, and a set of isolated precursor isotopes

estimateForFragmentFromPeptideWeightAndS(self, average_weight_precursor: float, S_precursor: int, average_weight_fragment: float, S_fragment: int, precursor_isotopes: Set[int]) → IsotopeDistribution: Estimate peptide fragment IsotopeDistribution from the precursor’s average weight, number of sulfurs in the precursor, fragment’s average weight, number of sulfurs in the fragment, and a set of isolated precursor isotopes.

estimateForFragmentFromRNAWeight(self, average_weight_precursor: float, average_weight_fragment: float, precursor_isotopes: Set[int]) → IsotopeDistribution: Estimate RNA fragment IsotopeDistribution from the precursor’s average weight, fragment’s average weight, and a set of isolated precursor isotopes

estimateForFragmentFromWeightAndComp(self, average_weight_precursor: float, average_weight_fragment: float, precursor_isotopes: Set[int], C: float, H: float, N: float, O: float, S: float, P: float) → IsotopeDistribution: Estimate fragment IsotopeDistribution from the precursor’s average weight, fragment’s average weight, a set of isolated precursor isotopes, and average composition

estimateFromDNAWeight(self, average_weight: float) → IsotopeDistribution: Estimate Nucleotide Isotopedistribution from weight

estimateFromPeptideWeight(self, average_weight: float) → IsotopeDistribution: Estimate Peptide Isotopedistribution from weight and number of isotopes that should be reported

estimateFromPeptideWeightAndS(self, average_weight: float, S: int) → IsotopeDistribution: Estimate peptide IsotopeDistribution from average weight and exact number of sulfurs

estimateFromRNAWeight(self, average_weight: float) → IsotopeDistribution: Estimate Nucleotide Isotopedistribution from weight

estimateFromWeightAndComp(self, average_weight: float, C: float, H: float, N: float, O: float, S: float, P: float) → IsotopeDistribution

estimateFromWeightAndCompAndS(self, average_weight: float, S: int, C: float, H: float, N: float, O: float, P: float) → IsotopeDistribution: Estimate IsotopeDistribution from weight, exact number of sulfurs, and average remaining composition

getMaxIsotope(self) → int: Returns the currently set maximum isotope

getRoundMasses(self) → bool: Returns the current value of the flag to round masses to integer values (true) or return accurate masses (false)

run(self, in_0: EmpiricalFormula) → IsotopeDistribution

setMaxIsotope(self, max_isotope: int) → None: Sets the maximal isotope with ‘max_isotope’

setRoundMasses(self, round_masses_: bool) → None: Sets the round_masses_ flag to round masses to integer values (true) or return accurate masses (false)