plotArray: Plot microarray images

In pepStat: Statistical analysis of peptide microarrays

Description

Plot a color image of the intensities on a slide. These plots are helpful to diagnose spatial abnormalities.

Usage

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))

Arguments

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=.).

Details

The most coherent results are achieved when the peptideSet object is read with makePeptideSet with empty.control.list = NULL and rm.control.list = NULL

Author(s)

Gregory Imholte

Examples

## 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)

}

Example output

Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: IRanges
Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

No methods found in "GenomicRanges" for requests: mcols<-
No methods found in "GenomicRanges" for requests: mcols
Loading required package: pepDat
Warning message:
In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called 'pepDat'

pepStat documentation built on Nov. 8, 2020, 6:45 p.m.