Description Usage Arguments Details Value Note Author(s) References See Also
Takes the spectra from files in raw.dir
, calculates the baselines from them,
and writes the results in the directory base.dir
.
1 2 3 4 5 6 | run.baselines(root.dir = ".", raw.dir, base.dir, overwrite = FALSE,
use.par.file = FALSE, par.file = "parameters.RData",
sm.par = 1e-11, sm.ord = 2, max.iter = 20, tol = 5e-8,
sm.div = NA, sm.norm.by = c("baseline", "overestimate", "constant"),
neg.div = NA, neg.norm.by = c("baseline", "overestimate", "constant"),
rel.conv.crit = TRUE, zero.rm = TRUE, halve.search = FALSE)
|
root.dir |
directory for parameters file and raw data |
raw.dir |
directory for raw data files; default is |
base.dir |
directory for baseline files; default is |
overwrite |
logical; whether to replace existing files with new ones |
use.par.file |
logical; if |
par.file |
string containing name of parameters file |
sm.par |
smoothing parameter for baseline calculation |
sm.ord |
order of derivative to penalize in baseline analysis |
max.iter |
convergence criterion in baseline calculation |
tol |
convergence criterion |
sm.div |
smoothness divisor in baseline calculation |
sm.norm.by |
method for smoothness penalty in baseline analysis |
neg.div |
negativity divisor in baseline calculation |
neg.norm.by |
method for negativity penalty in baseline analysis |
rel.conv.crit |
logical; whether convergence criterion should be relative to size of current baseline estimate |
zero.rm |
logical; whether to replace zeros with average of surrounding values |
halve.search |
logical; whether to use a halving-line search if step leads to smaller value of function |
Goes through the entire directory raw.dir
file-by-file and computes each
baseline using baseline
, then writes the spectrum and the baseline
to a file in directory base.dir
. The name of the new file is the same as
the name of the old file with “.txt” replaced by “.RData”, and the
new file is ready to be used by run.peaks
.
The files in raw.dir
must be in a specific format (future versions of the
package will allow for more flexibility). The files should be two-column text
files with mass in the first column and spectrum intensity in the second column.
There should be no header row (just start the file with the first data point).
The columns can be either comma-separated or whitespace-separated and the
program will automatically detect which each file is. The decimal separator
should be "."
, as using ","
will cause errrors in reading the
files.
See baseline
for details of all the parameters after
par.file
.
No value returned; the files are 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. Note that this is opposite from the behavior for
FTICRMS versions 0.7 and earlier.
The values of sm.norm.by
and neg.norm.by
can be abbreviated and
both have default value "baseline"
.
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.
Xi, Y. and Rocke, D.M. (2008) “Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis”. BMC Bioinformatics, 9:324.
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