| plotArrayImage {pepStat} | R Documentation |
Plot a color image of the intensities on a slide. These plots are helpful to diagnose spatial abnormalities.
plotArrayImage(peptideSet, array.index = NULL, low = "white", high = "steelblue", ask = dev.interactive(orNone = TRUE) & 1 < length(array.index)) plotArrayResiduals(peptideSet, array.index = NULL, smooth = FALSE, low = "blue", high = "red", ask = dev.interactive(orNone = TRUE) & 1 < length(array.index))
peptideSet |
A |
array.index |
A vector subsetting |
smooth |
A |
low |
A |
high |
A |
ask |
A |
The most coherent results are achieved when the peptideSet object is
read with makePeptideSet with empty.control.list = NULL and rm.control.list
= NULL
Gregory Imholte
## This example curated from the vignette -- please see vignette("pepStat")
## for more information
if (require("pepDat")) {
## Get example GPR files + associated mapping file
dirToParse <- system.file("extdata/gpr_samples", package = "pepDat")
mapFile <- system.file("extdata/mapping.csv", package = "pepDat")
## Make a peptide set
pSet <- makePeptideSet(files = NULL, path = dirToParse,
mapping.file = mapFile, log=TRUE)
## Plot array images -- useful for quality control
plotArrayImage(pSet, array.index = 1)
plotArrayResiduals(pSet, array.index = 1, smooth = TRUE)
## Summarize peptides, using pep_hxb2 as the position database
data(pep_hxb2)
psSet <- summarizePeptides(pSet, summary = "mean", position = pep_hxb2)
## Normalize the peptide set
pnSet <- normalizeArray(psSet)
## Smooth
psmSet <- slidingMean(pnSet, width = 9)
## Make calls
calls <- makeCalls(psmSet, freq = TRUE, group = "treatment",
cutoff = .1, method = "FDR", verbose = TRUE)
## Produce a summary of the results
summary <- restab(psmSet, calls)
}