make.par.file {FTICRMS}R Documentation

Create Parameter File for FT-ICR MS Analysis

Description

Creates a file of parameters that can be read by the functions in the FTICRMS package

Usage

make.par.file(covariates, form, root.dir = ".", par.file = "parameters.RData", ...)

Arguments

covariates data frame with rownames given by raw data files
form object of class “formula” to be used for testing using covariates
root.dir string containing location for file
par.file string containing name of file
... parameters whose default values are to be overwritten (see below)

Details

Creates a file called parameters.RData in directory root.dir which contains values for all of the parameters used in the programs in the FTICRMS package. The possible parameters that can be included in ..., their default values, and their descriptions are as follows:
add.norm = TRUE logical; whether to normalize additively or multiplicatively on the log scale
add.par = 10 additive parameter for "shiftedlog" or "glog" options for trans.method
align.method = "spline" alignment algorithm for peaks
base.dir = paste(root.dir, "/Baseline_Corrected", sep="") directory for baseline-corrected files
clust.constant = 10 parameter used in running cluster.method
clust.method = "ppm" method for determining when two peaks from different spectra are the same
cor.thresh = 0.8 threshhold correlation for declaring isotopes
FDR = 0.1 False Discovery Rate in Benjamini-Hochberg test
frac.changed = 0.001 convergence criterion in baseline calculation
isotope.dist = 7 maximum distance for declaring isotopes
k.biweight = 6 parameter for robust center and scale estimation using Tukey's biweight
lrg.dir = paste(root.dir, "/Large_Peaks", sep="") directory for significant peaks file
lrg.only = TRUE whether to consider only peaks that have at least one peak “significant”; i.e., identified by run.lrg.peaks
masses = NULL specific masses to test
max.iter = 30 convergence criterion in baseline calculation
neg.pen = sqrt(pi/2) negativity penalty in baseline calculation
normalization = "common" type of normalization to use on spectra before statistical anlaysis
num.pts = 5 number of points needed for peak fitting
oneside.min = 1 minimum number of points on each side of local maximum for peak fitting
overwrite = FALSE whether to replace exisiting files with new ones
peak.dir = paste(root.dir, "/All_Peaks", sep="") directory for peak location files
peak.method = "parabola" method for locating peaks
pre.align = 0 shifts to apply before running run.strong.peaks
pval.fcn = "default" function to calculate p-values if use.t.test = FALSE
R2.thresh = 0.98 R^2 value needed for peak fitting
raw.dir = paste(root.dir, "/Raw_Data", sep="") directory for raw data files
repl.method = max how to deal with replicates
res.dir = paste(root.dir, "/Results", sep="") directory for result file
root.dir = "." directory for parameters file and raw data
sm.par = 1.1E-9 smoothing parameter for baseline calculation
trans.method = "shiftedlog" data transformation method
use.t.test = TRUE whether to use a t-test to calculate p-values

Value

No value returned; the file par.file is simply created in root.dir.

Note

do.call(make.par.file, extract.pars()) recreates the original parameter file.

See the individual function help pages for each function for more detailed descriptions of the above parameters.

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

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

See Also

extract.pars


[Package FTICRMS version 0.6 Index]