Isotopocule coverage — orbi_plot_isotopocule

The coverage of each isotopcule across scans/time is an important indicator for data completeness. These functions provide ways to summarize and visualize the isotopocule coverage in a dataset.

Usage

orbi_plot_isotopocule_coverage(
  dataset,
  isotopocules = c(),
  x = c("scan.no", "time.min"),
  x_breaks = scales::breaks_pretty(5),
  add_data_blocks = TRUE
)

orbi_get_isotopocule_coverage(dataset)

Arguments

dataset: a data frame or aggregated dataset with satellite peaks already identified (i.e. after orbi_flag_satellite_peaks())
isotopocules: which isotopocules to visualize, if none provided will visualize all (this may take a long time or even crash your R session if there are too many isotopocules in the data set)
x: x-axis column for the plot, either "time.min" or "scan.no", default is "scan.no"
x_breaks: what breaks to use for the x axis, change to make more specifid tickmarks
add_data_blocks: add highlight for data blocks if there are any block definitions in the dataset (uses orbi_add_blocks_to_plot()). To add blocks manually, set add_data_blocks = FALSE and manually call the orbi_add_blocks_to_plot() function afterwards.

Value

a ggplot object

summary data frame

Functions

orbi_plot_isotopocule_coverage(): visualizes isotope coverage. Weak isotopocules (if previously defined by orbi_flag_weak_isotopocules()) are highlighted in red.
orbi_get_isotopocule_coverage(): calculates which stretches of the data have data for which isotopocules. This function is usually used indicrectly by orbi_plot_isotopocule_coverage() but can be called directly to investigate isotopocule coverage.