locate.peaks: Locate Peaks in a FT-ICR MS Spectrum
In FTICRMS: Programs for Analyzing Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Data

Description Usage Arguments Details Value Note Author(s) References See Also

Locates peaks in FT-ICR MS spectra assuming that the peaks are roughly parabolic on the log scale.

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locate.peaks(peak.base, num.pts = 5, R2.thresh = 0.98, 
             oneside.min = 1, peak.method = c("parabola", "locmaxes"), 
             thresh = -Inf)

`peak.base`	numeric matrix with two columns containing the masses and the transformed spectrum intensities
`num.pts`	minimum number of points needed to have a peak
`R2.thresh`	minimum R^2 needed to have a peak
`oneside.min`	minimum number of points needed on each side of the local maximum
`peak.method`	how to locate peaks
`thresh`	only local maxes that are larger than this will be checked to see if they are peaks

If peak.method == "parabola", the algorithm works by locating local maxima in the spectrum, then seeing if any num.pts consecutive points with at least oneside.min point(s) on each side of the local maximum have a coefficient of determination (R^2) of at least R2.thresh when fitted with a quadratic. If, in addition, the coefficient of the squared term is negative, then this is declared a peak and the vertex of the corresponding parabola is located. The coordinates of the vertex give the components Center_hat and Max_hat in the return value. The Width_hat component is the negative reciprocal of the coefficient of the squared term.

If peak.method == "locmax", then the algorithm merely returns the set of local maxima larger than thresh, and the Width_hat component of the return value is NA.

A data frame with columns

`Center_hat`	estimated mass of peak
`Max_hat`	estimated intensity of peak
`Width_hat`	estimated width of peak

An extremely large value for Width_hat most likely indicates a bad fit.

peak.method can be abbreviated. Using peak.method = "locmax" will vastly speed up the runtime, but may affect the quality of the analysis.

As noted in both papers in the References, a typical FT-ICR MS spectrum has far more peaks than can be accounted for by actual compounds. Thus, defining a good value of thresh will vastly speed up the computation without materially affecting the analysis.

Don Barkauskas (barkda@wald.ucdavis.edu)

Barkauskas, D.A. and D.M. Rocke. (2009a) “A general-purpose baseline estimation algorithm for spectroscopic data”. to appear in Analytica Chimica Acta. doi:10.1016/j.aca.2009.10.043

Barkauskas, D.A. et al. (2009b) “Analysis of MALDI FT-ICR mass spectrometry data: A time series approach”. Analytica Chimica Acta, 648:2, 207–214.

Barkauskas, D.A. et al. (2009c) “Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data”. Bioinformatics, 25:2, 251–257.

run.peaks

FTICRMS documentation built on May 1, 2019, 10:53 p.m.