plotArray: Plot microarray images
In RGLab/pepStat: Statistical analysis of peptide microarrays

Description Usage Arguments Details Author(s) Examples

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 `peptideSet` object. The object must contain all the original probes. See details below.
`array.index`	A vector subsetting `exprs(peptideSet)`, indicating which slides to plot
`smooth`	A `logical`, a 2D spatial smoother is applied to residuals, the fitted residuals are plotted.
`low`	A `character` string. The color of the lowest slide intensity. passed to `scale_fill_gradient2`. the fitted residuals are plotted.
`high`	A `character` string. The color of the highest slide intensity. passed to `scale_fill_gradient2`.
`ask`	A `logical`. If TRUE, the user is asked before each plot. See `par(ask=.)`.

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)

}