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) }