run.strong.peaks {FTICRMS}R Documentation

Locate Peaks that are "Large" in All Samples

Description

Takes the file generated by run.peaks, extracts all peaks that are “large” in all samples, and writes the results to a file.

Usage

run.strong.peaks(cor.thresh = 0.8, isotope.dist = 7, pre.align = FALSE, 
                 root.dir = ".", lrg.dir, lrg.file = "lrg.peaks.RData", 
                 overwrite = FALSE, use.par.file = FALSE, 
                 par.file = "parameters.RData")

Arguments

cor.thresh threshhold correlation for declaring two peaks to be isotopes
isotope.dist maximum difference in mass for declaring two peaks to be isotopes
pre.align either FALSE, or a numeric vector of shifts to apply to spectra, or a two-component list (of the form described in the Note section below) to be used before identifying peaks from different spectra
root.dir string containing location of raw data directory
lrg.dir directory for significant peaks file; default is paste(root.dir, "/Large_Peaks", sep = "")
lrg.file string containing name of significant peaks file
overwrite logical; whether to replace existing files with new ones
use.par.file logical; if TRUE, then parameters are read from par.file in directory root.dir
par.file string containing name of parameters file

Details

Reads in information from file created by run.lrg.peaks, locates peaks which appear in all samples, and overwrites the file lrg.file in lrg.dir. The resulting file contains variables
amps data frame of amplitudes of non-isotope peaks that occur in all samples
centers data frame of centers of non-isotope peaks that occur in all samples
lrg.peaks the data frame of significant peaks created by run.lrg.peaks

and is ready to be used by run.cluster.matrix.

Value

No value returned; the file is simply created.

Note

A peak is “large” if its value of Max_hat is at least numsds standard deviations above the mean value in the data generated by run.peaks for the spectrum it comes from.

If use.par.file = TRUE, then the parameters read in from the file overwrite any arguments entered in the function call.

pre.align is used if the spectra have not already been aligned by the mass spectroscopists. If it is not FALSE, it can either be a vector of additive shifts to be applied to the spectra, or a list with components targets and actual. In the last case, targets is a vector of target masses, and actual is a matrix with length(targets) columns and a row for each spectrum, actual[i,j] being the mass in spectrum i that should be matched exactly to target[j], with NA being a valid entry in actual. The matching is done (depending on the number of non-missing values in row i) either with a simple shift (one non-missing value), an affine transformation (two non-missing values), a piecewise affine transformation (three non-missing values), or an interpolation spline (four or more non-missing values).

Author(s)

Don Barkauskas (barkda@wald.ucdavis.edu)

References

Barkauskas, D.A. et al. (2008) “Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data”. Submitted to Bioinformatics

See Also

run.lrg.peaks, run.cluster.matrix, interpSpline

Examples






[Package FTICRMS version 0.5 Index]