estimateMzScattering {MSnbase} | R Documentation

## Estimate m/z scattering in consecutive scans

### Description

Estimate scattering of m/z values (due to technical, instrument specific noise) for the same ion in consecutive scans of a LCMS experiment.

### Usage

    estimateMzScattering(x, halfWindowSize = 1L, timeDomain = FALSE)

### Arguments

`x` | `MSnExp` or `OnDiskMSnExp` object.
`halfWindowSize` | `integer(1)` defining the half window size for the moving window to combine consecutive spectra.
`timeDomain` | `logical(1)` whether m/z scattering should be estimated on `mz` (`timeDomain = FALSE`) or `sqrt(mz)` (`timeDomain = TRUE`) values. See `combineSpectraMovingWindow()` for details on this parameter.

### Details

The m/z values of the same ions in consecutive scans (spectra) of a LCMS run will not be identical. This random noise is expected to be smaller than the resolution of the MS instrument. The distribution of differences of m/z values from neighboring spectra is thus expected to be (at least) bi-modal with the first peak representing the above described random variation and the second (or largest) peak the m/z resolution. The m/z value of the first local minimum between these first two peaks in the distribution is returned as the m/z scattering.

### Note

For `timeDomain = TRUE` the function does not return the estimated scattering of m/z values, but the scattering of `sqrt(mz)` values.

### Author(s)

Johannes Rainer

### See Also

`estimateMzResolution()` for the function to estimate a profile-mode spectrum's m/z resolution from it's data.

### Examples

    library(MSnbase)
    library(msdata)
    ## Load a profile-mode LC-MS data file
    f <- dir(system.file("sciex", package = "msdata"), full.names = TRUE)[1]
    od <- readMSData(f, mode = "onDisk")
    im <- as(filterRt(od, c(10, 20)), "MSnExp")

    res <- estimateMzScattering(im)

    ## Plot the distribution of estimated m/z scattering
    plot(density(unlist(res)))

    ## Compare the m/z resolution and m/z scattering of the spectrum with the
    ## most peaks
    idx <- which.max(unlist(spectrapply(im, peaksCount)))

    res[[idx]]
    abline(v = res[[idx]], lty = 2)
    estimateMzResolution(im[[idx]])
    ## As expected, the m/z scattering is much lower than the m/z resolution.

[Package MSnbase version 2.18.0 Index]