ggplot2 Version of plotPrecursorIons()

Creates a ggplot2 version of precursor ion visualization for MsExperiment objects. This function plots the m/z and retention time of all precursor ions in MS2 spectra, useful for visualizing DDA (Data-Dependent Acquisition) data.

Usage

gplotPrecursorIons(object, pch = 21, col = "#00000080", bg = "#00000020", ...)

# S4 method for class 'MsExperiment'
gplotPrecursorIons(object, pch = 21, col = "#00000080", bg = "#00000020", ...)

Arguments

object

An MsExperiment object containing MS/MS data.

pch

Point shape for precursor ions (default: 21 = filled circle).

col

Point color (default: semi-transparent black).

bg

Point background/fill color (default: very transparent black).

...

Additional arguments passed to ggplot2 functions.

Value

A ggplot object (or list of ggplot objects if multiple files). Use + labs() to customize axis labels and titles.

Details

This function visualizes the precursor ions selected for fragmentation in MS/MS experiments. Each point represents a precursor ion, with:

• X-axis: Retention time of the MS2 spectrum

• Y-axis: Precursor m/z value

For MsExperiment objects with multiple files, separate plots are created for each file.

The plot range includes all MS1 data to provide context, but only shows precursor ions from MS2 spectra.

Default labels are provided ("retention time", "m/z"), but can be customized using ggplot2's labs() function, e.g., gplotPrecursorIons(x) + labs(x = "RT (s)").

See also

xcms::plotPrecursorIons() for the original xcms implementation.

Author

Jan Stanstrup

Examples

library(xcmsVis)
library(MsExperiment)
library(ggplot2)
library(MsDataHub)

## Load a test data file with DDA LC-MS/MS data
fl <- MsDataHub::PestMix1_DDA.mzML()
#> 
#> see ?MsDataHub and browseVignettes('MsDataHub') for documentation
#> downloading 1 resources
#> retrieving 1 resource
#> 
#> loading from cache
pest_dda <- readMsExperiment(fl)

gplotPrecursorIons(pest_dda)


## Customize labels with ggplot2
gplotPrecursorIons(pest_dda) + labs(x = "RT (s)", y = "Precursor m/z",
    title = "DDA Analysis")


## Subset the data object to plot the data specifically for one or
## selected file/sample:
gplotPrecursorIons(pest_dda[1L])