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Call this function to visualize orbitrap data vs. time or scan number. The most common uses are orbi_plot_raw_data(y = intensity), orbi_plot_raw_data(y = ratio), and orbi_plot_raw_data(y = tic * it.ms). By default includes all isotopcules that have not been previously identified by orbi_flag_weak_isotopcules() (if already called on dataset). To narrow down the isotopocules to show, use the isotopocule parameter.

Usage

orbi_plot_raw_data(
  dataset,
  isotopocules = c(),
  x = c("time.min", "scan.no"),
  x_breaks = scales::breaks_pretty(5),
  y,
  y_scale = c("raw", "linear", "pseudo-log", "log"),
  y_scale_sci_labels = TRUE,
  color = .data$isotopocule,
  colors = c("#1B9E77", "#D95F02", "#7570B3", "#E7298A", "#66A61E", "#E6AB02", "#A6761D",
    "#666666"),
  color_scale = scale_color_manual(values = colors),
  add_data_blocks = TRUE,
  add_all_blocks = FALSE,
  show_outliers = TRUE
)

Arguments

dataset

isox dataset

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"

x_breaks

what breaks to use for the x axis, change to make more specifid tickmarks

y

expression for what to plot on the y-axis, e.g. intensity, tic * it.ms (pick one isotopocules as this is identical for different istopocules), ratio. Depending on the variable, you may want to adjust the y_scale and potentially y_scale_sci_labels argument.

y_scale

what type of y scale to use: "log" scale, "pseudo-log" scale (smoothly transitions to linear scale around 0), "linear" scale, or "raw" (if you want to add a y scale to the plot manually instead)

y_scale_sci_labels

whether to render numbers with scientific exponential notation

color

expression for what to use for the color aesthetic, default is isotopocule

colors

which colors to use, by default a color-blind friendly color palettes (RColorBrewer, dark2)

color_scale

use this parameter to replace the entire color scale rather than just the colors

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.

add_all_blocks

add highlight for all blocks, not just data blocks (equivalent to the data_only = FALSE argument in orbi_add_blocks_to_plot())

show_outliers

whether to highlight data previously flagged as outliers by orbi_flag_outliers()

Value

a ggplot object