MSnbase (version 1.20.7)

plot.Spectrum.Spectrum-methods: Plotting a 'Spectrum' vs another 'Spectrum' object.

Description

These method plot mass spectra MZ values against the intensities as line plots. The first spectrum is plotted in the upper panel and the other in upside down in the lower panel. Common peaks are drawn in a slightly darker colour. If a peptide sequence is provided it automatically calculates and labels the fragments.

Arguments

x

Object of class "Spectrum" .

y

Object of class "Spectrum" .

...

Further arguments passed to internal functions.

Methods

signature(x = "Spectrum", y = "Spectrum", ...)

Plots two spectra against each other. Common peaks are drawn in a slightly darker colour. The ... arguments are passed to the internal functions. Currently tolerance, relative, sequences and most of the plot.default arguments (like xlim, ylim, main, xlab, ylab, ...) are supported. You could change the tolerance (default 25e-6) and decide whether this tolerance should be applied relative (default relative = TRUE) or absolute (relative = FALSE) to find and colour common peaks. Use a character vector of length 2 to provide sequences which would be used to calculate and draw the corresponding fragments. If sequences are given the type argument (default: type=c("b", "y") specify the fragment types which should calculated. Also it is possible to allow some modifications. Therefore you have to apply a named character vector for modifications where the name corresponds to the one-letter-code of the modified amino acid (default: Carbamidomethyl modifications=c(C=160.030649)). See calculateFragments for details.

See Also

More spectrum plotting available in plot.Spectrum.

Examples

## find path to a mzXML file
file <- dir(system.file(package = "MSnbase", dir = "extdata"),
            full.name = TRUE, pattern = "mzXML$")

## create basic MSnExp
msexp <- readMSData(file)

## centroid them
msexp <- pickPeaks(msexp)

## plot the first against the second spectrum
plot(msexp[[1]], msexp[[2]])

## add sequence information
plot(msexp[[1]], msexp[[2]], sequences=c("VESITARHGEVLQLRPK",
                                         "IDGQWVTHQWLKK"))


itraqdata2 <- pickPeaks(itraqdata)
(k <- which(fData(itraqdata2)[, "PeptideSequence"] == "TAGIQIVADDLTVTNPK"))
mzk <- precursorMz(itraqdata2)[k]
zk <- precursorCharge(itraqdata2)[k]
mzk * zk
plot(itraqdata2[[k[1]]], itraqdata2[[k[2]]])