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Generate conversion factors for FP calibrations

Source: R/generate_cfs.R
generate_cfs.Rd

Generate conversion factors for fluorescent protein (FP) calibrations. Originally based on flopr::generate_cfs() but with numerous changes. The original function was intended for fluorescein and microsphere calibrations, whereas this one can be used for any fluorescent calibrant, including proteins. Takes as input a parsed CSV of fluorescence data of a dilution series of FPs at one or more gains, that contains both data and metadata columns (including: instrument, plate, seal, channel_name, channel_ex, channel_em, media, calibrant, protein, replicate, volume, mw_gmol1, concentration_ngul, well, the columns for the fluorescence data, row, column). A number of arguments allow the tweaking of the original data set. Following this, the data is reshaped, normalised, trimmed of saturated points, summarised and used to fit a model for the conversion factors from arbitrary to absolute units. Optional extras: the sensitivity_plots argument extends this analysis to identify the limits of detection and relative sensitivity and dynamic range of each gain. Plots are saved to record the processed data at every step, allowing for visual sanity checks and troubleshooting. A CSV file with the fitted conversion factors is saved (along with the processed data if requested with more_csvs).

Usage

generate_cfs(
  calibration_csv,
  more_csvs = FALSE,
  more_plots = FALSE,
  sensitivity_plots = FALSE,
  include_only = NULL,
  exclude = NULL,
  gain_fix = FALSE,
  rename_from = NULL,
  rename_to = NULL,
  subset_rows = FALSE,
  rows_to_keep = c("C", "D"),
  separator = "",
  complete_blank = FALSE,
  outfolder = "."
)

Arguments

calibration_csv

character string. Path of the calibration data CSV file.

more_csvs

logical. Optionally save all the intermediate tables in this function. Defaults to FALSE.

more_plots

logical. Optionally save more plots. Defaults to FALSE.

sensitivity_plots

logical. Optionally adds a few extra columns to the data such as the min/max normalised fluorescence and detectable molecules. It also plots a few extra plots. Defaults to FALSE.

include_only

character string. If specified, only includes the measures (column names) specified here.

exclude

character string. If specified, excludes any measures (column names) specified here.

gain_fix

logical. Optionally add "0" before 2-digit gain names i.e. 'GFP 40' -> 'GFP 040', or blueblue 40 -> blueblue 040- which fixes ordering of plots. Defaults to FALSE.

rename_from

character string. Rename measures (column names) containing character string rename_from to character string specified in rename_to. Both rename_from and rename_to need to be completed to trigger renaming.

rename_to

character string. Rename measures (column names) containing character string rename_from to character string specified in rename_to. Both rename_from and rename_to need to be completed to trigger renaming.

subset_rows

logical. Should script take a subset of the rows (or whole table)? Defaults to FALSE.

rows_to_keep

character array. If subset_rows is TRUE, script will choose rows to keep from this list. Defaults to c("C","D").

separator

character string that represents the separator between the channel name and the gain value in the measures columns, e.g. for "GFP 40" it is " ", for "GFP40" it is "" and for "GFP_40" it is "_". Required for plotting the gain vs conversion factors. Defaults to "".

complete_blank

logical. Optionally adds "0" to the concentration_ngul column for wells identified as blank (protein = "none"). Useful if metadata is missing these values. Defaults to FALSE.

outfolder

character string. Path to folder where output files should be saved. Defaults to current working directory.

Examples

if (FALSE) {
  fitvals <- generate_cfs(
    calibration_csv = "data_parsed.csv",
    subset_rows = TRUE, rows_to_keep = c("C","D"),
    outfolder = "cfs_mCherry"
  )
}