run.lrg.peaks: Extract "Large" Peaks from Files
In FTICRMS: Programs for Analyzing Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Data

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

Takes the files output by run.peaks, extracts “large” peaks, combines them into a single data frame, and writes the data frame to a file.

run.lrg.peaks(trans.method = c("shiftedlog", "glog", "none"), 
              add.par = 0, subtract.base = FALSE,
              root.dir = ".", peak.dir, base.dir, lrg.dir,
              lrg.file = lrg_peaks.RData, overwrite = FALSE,
              use.par.file = FALSE, par.file = "parameters.RData",
              calc.all.peaks = FALSE, gengamma.quantiles = TRUE,
              peak.thresh = 3.798194, subs)

`trans.method`	type of transformation to use on spectra before statistical analysis
`add.par`	additive parameter for `"shiftedlog"` or `"glog"` options for `trans.method`
`subtract.base`	logical; whether to subtract calculated baseline from spectrum
`root.dir`	directory for parameters file and raw data
`peak.dir`	directory for peak location files; default is `paste(root.dir, "/All_Peaks", sep = "")`
`base.dir`	directory for baseline files; default is `paste(root.dir, "/Baselines", sep = "")`
`lrg.dir`	directory for large peaks file; default is `paste(root.dir, "/Large_Peaks", sep = "")`
`lrg.file`	name of file to store large peaks in
`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
`calc.all.peaks`	logical; whether to calculate all possible peaks or only sufficiently large ones
`gengamma.quantiles`	logical; whether to use generalized gamma quantiles when calculating large peaks
`peak.thresh`	threshold for declaring large peak; see below
`subs`	subset of spectra to use for analysis; see below

Reads in information from each file created by run.peaks, extracts peaks which are “large” (see below), and creates the file lrg.file in lrg.dir. The resulting file contains the data frame lrg.peaks, which has columns


`Center_hat`	estimated mass of peak
`Max_hat`	estimated intensity of peak
`Width_hat`	estimated width of peak
`File`	name of file the peak was extracted from, with “\_peaks.RData” deleted

and is ready to be used by run.strong.peaks.

No value returned; the file is simply created.

If use.par.file == TRUE and other parameters are entered into the function call, then the parameters entered in the function call overwrite those read in from the file. This is opposite from the behavior for FTICRMS versions 0.7 and earlier.

trans.method can be abbreviated.

If gengamma.quantiles == TRUE, then a peak is “large” if it is at least peak.thresh times as large as the estimated baseline at that point.

If gengamma.quantiles == FALSE, then a peak is “large” if it has zero weight in the data generated by run.peaks for the spectrum it comes from when using Tukey's biweight with parameter K = 1.5 * peak.thresh to estimate center and scale.

If subs is not defined, the algorithm finds large peaks for all files in peak.dir. If it is defined, subs can be logical or numeric or character; if it is defined, then the algorithm finds large peaks for all entries in subs (character) or list.files(peak.dir)[subs] (logical or numeric).

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, run.cluster.matrix

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