Plot the Median Fluorescent Intensity (MFI) to Relative Antibody Units (RAU) Results Data based on ETH standard

This function gets the Median Fluorescent Intensity (MFI) to Relative Antibody Units (RAU) model results data and plots the model fits based on `MFItoRAU_Adj.`

Usage

plotModel_Adj(mfi_to_rau_output, sero_data)

Arguments

mfi_to_rau_output

Output from `MFItoRAU_Adj()`.

sero_data

Output from `readSeroData()`.

Value

List of dot and line plots of MFI to RAU model standard curve, with each one representing an individual plate (ggplot).

Author

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)`

# Step 4: Plot Model Results
plotModel_Adj(mfi_to_rau, sero_data)
#> $plate1
#> Ignoring unknown labels:
#> • fill : "Antigen"

#> 
#> $plate2
#> Ignoring unknown labels:
#> • fill : "Antigen"

#> 
# }