R: find isotop pattern in a given mass spectrum

deisotoper {protViz} | R Documentation

## find isotop pattern in a given mass spectrum

### Description

`deisotoper` returns the indices and scores of the isotop pattern. The score is computed by considering the isotop L2 norm of a given iostop model. `protViz` contains the `averagine` data.

### Usage

        deisotoper(data, Z=1:4, isotopPatternDF=averagine, massError=0.005, plot=FALSE)

### Arguments

`data` | A mass spectrometric measurement containing a list.
`Z` | Charge states to be considered. The default is `Z=1:4`
`isotopPatternDF` | a data frame containing isotope envelopes of peptide averagine.
`massError` | mass error in Dalton. default is 0.005.
`plot` | boolean if the isotops should be plotted. The default is false.

### Details

The output of the `deisotoper` function is a `list` data structure containing for each input MS data set a `result`, `score`, and `group` lists.

`result` is a list which contains for each charge state a list of isotop groups. Analoge to `result` a score is provide in the `score` list.

`group` provides information about the charge states of each isotop cluster.

The algorithm for finding the isotop chains as implemented in protViz is based on the idea of 'Features-Based Deisotoping Method for Tandem Mass Spectra'. Each peak represents one node of a graph `G=(V,E)` with `V = {1, ..., n}`. The edges are defined by `(v, node_array_G[v])` iff `node_array_G[v] > -1`. In other words an edge is defined between two peaks if the mZ difference is below the given massError. The isotop chains are determined by a DFS run. The time complexity is `O(n log (n))` where n is the number of peaks.

### Author(s)

Witold Eryk Wolski, Christian Trachsel, and Christian Panse 2013

### References

isotopic-cluster graphs:

Features-Based Deisotoping Method for Tandem Mass Spectra, Zheng Yuan Jinhong Shi Wenjun Lin Bolin Chen and Fang-Xiang Wu Advances in Bioinformatics Volume 2011 (2011), Article ID 210805, 12 pages http://www.hindawi.com/journals/abi/2011/210805/

### Examples

        # example1 - tandem ms
        x <- list(mZ = c(726.068, 726.337, 726.589, 726.842, 727.343, 727.846, 728.346,
            728.846, 729.348, 730.248, 730.336, 730.581, 730.836),
            intensity = c(6.77850e+03, 2.81688e+04, 6.66884e+04, 1.22032e+07,
                9.90405e+06, 4.61409e+06, 1.50973e+06, 3.33996e+05, 5.09421e+04,
                1.15869e+03, 2.14788e+03, 5.37853e+03, 5.79094e+02))

        # the plain C interface function
        out1 <- .Call("deisotoper_main", x$mZ, x$intensity, Z=1:4, averagine,
            massError=0.01, PACKAGE="protViz")

        out<-deisotoper(data=list(x), Z=2:4, isotopPatternDF=averagine)

        # example2 - a ms from heavy labeld peptide in water background
        x <- list(mZ=c(642.572, 643.054, 643.569, 644.062, 644.557),
            intensity=c(17000, 25000, 12000, 9000,4000))

        diff(x$mZ)
        diff(x$mZ,lag=2)
        diff(x$mZ, difference=2)

        out2<-deisotoper(data=list(x), Z=1:2, isotopPatternDF=averagine,
            massError=0.02, plot=TRUE)

[Package protViz version 0.2.45 Index]