Description Usage Arguments Details Value Author(s) Examples
After normalization and data smoothing, this last step makes the call for each peptide of the peptideSet after baseline correcting the peptide intenstities.
1 2 |
peptideSet |
A |
cutoff |
A |
method |
A |
freq |
A |
group |
A |
verbose |
A |
This function requires specific variables ptid and visit in pData(peptideSet).
The variable ptid
should indicate subjects, and the variable visit
should be a factor with levels pre and post.
If slides are paired for subjects, intensities corresponding to post-visit are substracted from pre. If slides are not paired, slides with pre have intensities averaged by peptides, and averaged peptide intensities are subtracted from slides that have entry post. Calls are made on these baseline corrected intensities.
When method = FDR, a left-tail method is used to generate a threshold controlling
the False Discovery Rate at level cutoff
. When method = absolute, Intensities
exceeding the threshold are labelled as positive.
When freq = TRUE a group variable may be specified. The argument group indicates the name of a variable in pData(peptideSet) by which positive calls should be grouped. The call frequency for each peptide is calculated within groups.
If freq = TRUE, a numeric
matrix
with peptides as rows and
groups as columns where the values are the frequency of response in the group. If
freq = FALSE, a logical
matrix
indicating binding events for each
peptide in each subject.
Greg Imholte
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ## 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)
}
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Loading required package: pepDat
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