Learn R Programming

MALDIquant (version 1.22.3)

calibrateIntensity-methods: Calibrates intensities of a MassSpectrum object.

Description

This function calibrates (normalize) intensities of MassSpectrum objects.

Usage

# S4 method for MassSpectrum
calibrateIntensity(object,
  method=c("TIC", "PQN", "median"), range, ...)
# S4 method for list
calibrateIntensity(object,
  method=c("TIC", "PQN", "median"), range, ...)

Value

Returns a modified MassSpectrum object with calibrated intensities.

Arguments

object

MassSpectrum object or a list of MassSpectrum objects.

method

the calibration method to be used. This should be one of "TIC", "PQN" or "median". See ‘Details’ section.

range

numeric of length 2, if given the scaling factor is calculated on the mass range from range[1L] to range[2L] and applied to the whole spectrum.

...

arguments to be passed to other functions. Currently only mc.cores is supported if object is a list.

Author

Sebastian Gibb mail@sebastiangibb.de

Details

A number of different calibration methods are provided:

"TIC":

The TIC (Total Ion Current) of a MassSpectrum object is set to one. If range is given the TIC is only calculated for the intensities in the specified mass range.

"PQN":

The PQN (Probabilistic Quotient Normalization) is described in Dieterle et al 2006. calibrateIntensity uses the following algorithm:

  1. Calibrate all spectra using the "TIC" calibration.

  2. Calculate a median reference spectrum.

  3. Calculate the quotients of all intensities of the spectra with those of the reference spectrum.

  4. Calculate the median of these quotients for each spectrum.

  5. Divide all intensities of each spectrum by its median of quotients.

"median":

The median of intensities of a MassSpectrum object is set to one.

References

F. Dieterle, A. Ross, G. Schlotterbeck, and Hans Senn. 2006. Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics. Analytical Chemistry 78(13): 4281-4290.

See Also

Examples

Run this code
## load package
library("MALDIquant")

## load example data
data("fiedler2009subset", package="MALDIquant")

## baseline correction
b <- removeBaseline(fiedler2009subset)

## calibrate intensity values
calibrateIntensity(b, method="TIC")

## calibrate intensity values using TIC for a specific mass range
calibrateIntensity(b, method="TIC", range=c(3000, 5000))

Run the code above in your browser using DataLab