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Median Fluorescent Intensity (MFI) to Relative Antibody Units (RAU) conversion based on other standard

Source: R/MFItoRAU.R
MFItoRAU_Adj.Rd

This function fits a 5-parameter logistic standard curve to the dilutions of the positive controls for each protein and converts the MFI values into relative antibody units (RAU) written by Eamon Conway.

Usage

MFItoRAU_Adj(sero_data, plate_list, qc_results, std_point = 10, project = NULL)

Arguments

sero_data

Output from `readSeroData()`.

plate_list

Output from `readPlateLayout()`.

qc_results

Output from `runQC()`.

std_point

Standard Point Curve: 5 = 5-point curve, 10 = 10-point curve, "PvLDH" for LDH specific curve. Default = 10. Value is an integer.

project

Default = NULL. Only write "pkpfpv" if using Pk/Pf/Pv pipeline.

Value

A list of three data frames: 1. Data frame with MFI data, converted RAU data and matched SampleID's. 2. Plot information for `plotModel` function. 3. Data frame of RAU data for random forest classification use.

Author

Eamon Conway, Dionne Argyropoulos

Examples

# \donttest{

# Step 0: Load example raw data
your_raw_data <- c(
  system.file("extdata", "example_MAGPIX_plate1.csv", package = "SeroTrackR"),
  system.file("extdata", "example_MAGPIX_plate2.csv", package = "SeroTrackR")
)
your_plate_layout <- system.file(
  "extdata",
  "example_platelayout_1.xlsx",
  package = "SeroTrackR"
)

# Step 1: Read serology data and plate layout
sero_data  <- readSeroData(your_raw_data,"magpix")
#> PASS: File example_magpix_plate1.csv successfully validated.
#> PASS: File example_magpix_plate2.csv successfully validated.
plate_list <- readPlateLayout(your_plate_layout, sero_data)
#> Plate layouts correctly identified!

# Step 2: Process counts and perform quality control
qc_results  <- runQC(sero_data, plate_list)

# Step 3: Convert MFI to RAU using ETH beads
mfi_to_rau <- MFItoRAU_Adj(
  sero_data    = sero_data,
  plate_list   = plate_list,
  qc_results   = qc_results
)
#> Joining with `by = join_by(antigen)`
#> Joining with `by = join_by(antigen)`
#> Joining with `by = join_by(antigen)`
#> Joining with `by = join_by(antigen)`
#> Joining with `by = join_by(antigen)`
#> Joining with `by = join_by(antigen)`

# }