useBRAIN2: Function computing probabilities of aggregated isotopic...

In ditti2/BRAIN: Baffling Recursive Algorithm for Isotope distributioN calculations

Description

Function computing probabilities of isotopic variants using heuristics, for chemical components composed of carbon, hydrogen, oxygen, nitrogen and sulfur (e.g. peptides). Additionally the function returns also the monoisotopic mass and the average mass of given chemical component.

Usage

useBRAIN2(aC, stopOption = "nrPeaks", nrPeaks, approxStart = 1, approxParam = NULL))

Arguments

aC	List with fields C, H, N, O, S of integer non-negative values (if any field is ommited, then its value is set to 0).
stopOption	only option "nrPeaks" allowed
nrPeaks	Integer indicating the number of consecutive isotopic variants to be calculated, starting from the monoisotopic one. This value can always be provided, even if <stop.option> is not a default setting. In the latter case it is a hard stopping criterion.
approxStart	Integer indicating the number of first isotopic peak to be calculated
approxParam	Integer indicating the length of recurrence (see RCL in [Ditt2])

Details

Function uses RCL and LSP heuristics from [Ditt2].

Value

Named list with the following fields:

• isoDistrProbabilities of aggregated isotopic variants (numeric vector)

Note

Remember that the isotopic variants starts from monoisotopic one. For large chemical molecules, first masses may have very low abundances. So sufficient number of peaks should be calculated to reach most abundant isotopic variant.

If only isotopic probabilities are needed, then the function calculateIsotopicProbabilities should be used.

Author(s)

Piotr Dittwald <[e-mail]>

References

[Ditt2] Dittwald P., Valkenborg D. BRAIN 2.0: time and memory complexity improvements in the algorithm for calculating the isotope distribution. JASMS, 2014, doi: 10.1007/s13361-013-0796-5.

See Also

calculateIsotopicProbabilities

Examples

  nrPeaks = 1000  
  aC <-  list(C=23832, H=37816, N=6528, O=7031, S=170)  # Human dynein heavy chain  
  res <-  useBRAIN(aC = aC, stopOption="nrPeaks", nrPeaks = nrPeaks)
  res2 <-  useBRAIN2(aC = aC, stopOption="nrPeaks", nrPeaks = nrPeaks, approxStart = 10)
  old = res$iso[10:109]/res$iso[11:110]
  new  = res2$iso[1:100]/res2$iso[2:101]
  max(old - new)
  max((old - new)/old)
  res3 <-  useBRAIN2(aC = aC, stopOption="nrPeaks", nrPeaks = nrPeaks, approx=TRUE, approxParam = 10)
  max(res3$iso - res$iso)

ditti2/BRAIN documentation built on Feb. 10, 2020, 5:43 a.m.