PlotSpec {InterpretMSSpectrum} | R Documentation |
Plot Mass Spectrum.
Description
PlotSpec
will read, evaluate and plot a deconvoluted mass spectrum (mass*intensity pairs) from TMS-derivatized GC-APCI-MS data.
The main purpose is to visualize the relation between deconvoluted masses.
Usage
PlotSpec(
x = NULL,
masslab = 0.1,
rellab = FALSE,
cutoff = 0.01,
cols = NULL,
txt = NULL,
mz_prec = 4,
ionization = NULL,
neutral_losses = NULL,
neutral_loss_cutoff = NULL,
substitutions = NULL,
precursor = NULL,
xlim = NULL,
ylim = NULL
)
Arguments
x |
A two-column matrix with ("mz", "int") information. |
masslab |
The cutoff value (relative to basepeak) for text annotation of peaks. |
rellab |
TRUE/FALSE. Label masses relative to largest mass in plot (if TRUE), absolute (if FALSE) or to specified mass (if numeric). |
cutoff |
Show only peaks with intensity higher than cutoff*I(base peak). This will limit the x-axis accordingly. |
cols |
Color vector for peaks with length(cols)==nrow(x). |
txt |
Label peaks with specified text (column 1 specifies x-axis value, column 2 specifies label). |
mz_prec |
Numeric precision of m/z (=number of digits to plot). |
ionization |
Either APCI or ESI (important for main peak determination). |
neutral_losses |
Data frame of defined building blocks (Name, Formula, Mass). If not provided data("neutral_losses") will be used. |
neutral_loss_cutoff |
Specifies the allowed deviation in mDa for neutral losses to be accepted from the provided neutral loss list. |
substitutions |
May provide a two column table of potential substitutions (for adducts in ESI-MS). |
precursor |
Internally main peaks will be determined up to a supposed precursor obtained by 'DetermineIsomainPeaks' and annotations will only be plotted up to this mass. To plot annotations for the full mass range, set 'precursor' to a higher mass. |
xlim |
To specify xlim explicitly (for comparative plotting). |
ylim |
To specify ylim explicitly (for comparative plotting). |
Value
An annotated plot of the mass spectrum.
Examples
#load test data and apply function
utils::data(apci_spectrum, package = "InterpretMSSpectrum")
PlotSpec(x=apci_spectrum, ionization="APCI")
# normalize test data by intensity
s <- apci_spectrum
s[,2] <- s[,2]/max(s[,2])
PlotSpec(x=s)
# use relative labelling
PlotSpec(x=s, rellab=364.1789)
# avoid annotation of masses and fragments
PlotSpec(x=s, masslab=NULL, neutral_losses=NA)
# provide individual neutral loss set
tmp <- data.frame("Name"=c("Loss1","Loss2"),"Formula"=c("",""),"Mass"=c(90.05,27.995))
PlotSpec(x=s, neutral_losses=tmp)
# provide additional color and annotation information per peak
PlotSpec(x=s, cols=1+(s[,2]>0.1), txt=data.frame("x"=s[s[,2]>0.1,1],"txt"="txt"))
# annotate a sum formula
PlotSpec(x=s, txt=data.frame("x"=s[which.max(s[,2]),1],"txt"="C[6]~H[12]~O[6]","expr"=TRUE))
# simulate a Sodium adduct to the spectrum (and annotate using substitutions)
p <- which.max(s[,2])
s <- rbind(s, c(21.98194+s[p,1], 0.6*s[p,2]))
PlotSpec(x=s, substitutions=matrix(c("H","Na"),ncol=2,byrow=TRUE))
#load ESI test data and apply function
utils::data(esi_spectrum)
PlotSpec(x=esi_spectrum, ionization="ESI")