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R: Function computing probabilities of aggregated isotopic...

calculateIsotopicProbabilities

R Documentation

Function computing probabilities of aggregated isotopic variants using BRAIN algorithm.

Description

Function computing probabilities of aggregated isotopic variants for chemical components built from carbon, hydrogen, oxygen, nitrogen and sulfur (e.g. peptides).

Usage

calculateIsotopicProbabilities(aC, stopOption = "nrPeaks", 
nrPeaks, coverage, abundantEstim)

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`	one of the following strings: "nrPeaks" (default), "coverage", "abundantEstim"
`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 <stopOption> is not a default setting. In the latter case it is a hard stopping criterion.
`coverage`	Scalar indicating the value of the cumulative aggregated distribution. The calculations will be stopped after reaching this value.
`abundantEstim`	Integer indicating the number of consecutive isotopic variants to be calculated, starting from one after the most abundant one. All consecutive isotopic variants before the most abundant peak are also returned.

Details

Remember that the isotopic variants starts from the monoisotopic one. In case of large chemical molecules, first masses may have very low abundance values for the lower mass aggregated values. A sufficient number of peaks should be calculated to reach most abundant isotopic variant.

Value

Probabilities of aggregated isotopic variants (numeric vector)

Note

If also masses associated with the aggregated isotopic variants are needed, then the function useBRAIN should be used.

Author(s)

Piotr Dittwald <piotr.dittwald@mimuw.edu.pl>

References

[Clae] Claesen J., Dittwald P., Burzykowski T. and Valkenborg D. An efficient method to calculate the aggregated isotopic distribution and exact center-masses. JASMS, 2012, doi:10.1007/s13361-011-0326-2

Examples

  nrPeaks = 1000
  aC <-  list(C=23832, H=37816, N=6528, O=7031, S=170)  # Human dynein heavy chain  
  res <- calculateIsotopicProbabilities(aC = aC, stopOption="nrPeaks", 
nrPeaks = nrPeaks)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(BRAIN)
Loading required package: PolynomF
Loading required package: Biostrings
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/BRAIN/calculateIsotopicProbabilities.Rd_%03d_medium.png", width=480, height=480)
> ### Name: calculateIsotopicProbabilities
> ### Title: Function computing probabilities of aggregated isotopic variants
> ###   using BRAIN algorithm.
> ### Aliases: calculateIsotopicProbabilities
> 
> ### ** Examples
> 
>   nrPeaks = 1000
>   aC <-  list(C=23832, H=37816, N=6528, O=7031, S=170)  # Human dynein heavy chain  
>   res <- calculateIsotopicProbabilities(aC = aC, stopOption="nrPeaks", 
+ nrPeaks = nrPeaks)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>