Quick start guide

# load isoorbi library

A basic data processing example


# path to a test file included in the isoorbi package
# this file contains data from multiple analyses for the same compound
file_path <- system.file(package = "isoorbi", "extdata", "testfile_flow.isox")

# load data
df <- 
  file_path |>  
  # reads .isox test data
  orbi_read_isox() |>
  # optionally: keeps only most important columns; equivalent to simplify check box in IsoX

# If you wish to read a whole folder of files, you can use the orbi_find_isox() function
# df <- "path_to_your_folder" |> orbi_find_isox() |> orbi_read_isox()


Now that the data is loaded, check for satellite peaks, weak isotopocules and outliers.

# check for noise and outliers
df_flagged <- df |> 
  orbi_flag_satellite_peaks() |> # removes minor signals that were reported by IsoX in the same tolerance window where the peak of interest is
  orbi_flag_weak_isotopocules(min_percent = 2) |> # removes signals of isotopocules that were not detected at least in min_percent scans
  orbi_flag_outliers(agc_fold_cutoff = 2) # removes outlying scans that have more than 2 times or less than 1/2 times the average number of ions in the Orbitrap analyzer; another method: agc_window (see function documentation for more details)

The info messages from these functions suggest that no data was flagged.


# define base peak and calculate the results table
df_results <- 
  df_flagged |> 
  orbi_define_basepeak(basepeak_def = "M0")|> # sets one isotopocule in the dataset as the base peak (denominator) for ratio calculation
  orbi_summarize_results(ratio_method = "sum") # calculates ratios and generates a results table


# use a ggplot to plot the data
df_results |>
  ggplot() +
    x = sprintf("%s/%s", isotopocule, basepeak),
    y = ratio, ymin = ratio - ratio_sem, ymax = ratio + ratio_sem,
    color = filename
  ) +
  geom_pointrange() +
  scale_color_brewer(palette = "Set1") +
  orbi_default_theme() +
  labs(x = NULL, y = "ratio") +