run.lrg.peaks {FTICRMS} | R Documentation |
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 = "shiftedlog", 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)
trans.method |
type of transformation to use on spectra before statistical analysis; currently, only "shiftedlog" , "glog" , and "none" are supported |
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 |
whether to replace exisiting 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 |
Reads in information from each file created by run.peaks
, extracts peaks which have
zero weight in the spectrum they come from when using Tukey's biweight with parameter k.biweight
to estimate center and scale, 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 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 3/2*peak.thresh
to estimate center and scale.
If use.par.file = TRUE
, then the parameters read in from the file overwrite any arguments entered in the
function call.
Don Barkauskas (barkda@wald.ucdavis.edu)
Barkauskas, D.A. (2009) “Statistical Analysis of Matrix-Assisted Laser Desorption/Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Data with Applications to Cancer Biomarker Detection”. Ph.D. dissertation, University of California at Davis.
Barkauskas, D.A. et al. (2009) “Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data”. Bioinformatics, 25:2, 251–257.