run.all {FTICRMS}R Documentation

Complete Analysis of FT-ICR MS Data

Description

A wrapper that calls all six functions needed for a full analysis.

Usage

run.all(par.file = "parameters.RData", root.dir = ".")

Arguments

par.file string containing the name of the parameters file
root.dir string containing location of raw data directory and parameters file

Details

Requires par.file to be in place before starting—for example by creating it with make.par.file.

Calls (in order) run.baselines, run.peaks, run.lrg.peaks, run.strong.peaks, run.cluster.matrix, and run.analysis.

Note

The analysis described in Barkauskas et al. (2008) can be reproduced using the following parameter values instead of the defaults:
add.par = 10
calc.all.peaks = TRUE
gengamma.quantiles = FALSE
neg.norm.by = "constant"
peak.thresh = 4
sm.norm.by = "constant"
subtract.base = TRUE

Author(s)

Don Barkauskas (barkda@wald.ucdavis.edu)

References

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.

Benjamini, Y. and Hochberg, Y. (1995) “Controlling the false discovery rate: a practical and powerful approach to multiple testing.” J. Roy. Statist. Soc. Ser. B, 57:1, 289–300.

Xi, Y. and Rocke, D.M. (2008) “Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis”. BMC Bioinformatics, 9:324.

See Also

make.par.file, run.baselines, run.peaks, run.lrg.peaks, run.strong.peaks, run.cluster.matrix, run.analysis


[Package FTICRMS version 0.7 Index]