process_plate {SerolyzeR} | R Documentation |
Process Plate Data and Save Normalised Output
Description
Processes a Luminex plate and computes normalised values using the specified
normalisation_type
. Depending on the chosen method, the function performs
blank adjustment, fits models, and extracts values for test samples.
Optionally, the results can be saved as a CSV file.
Usage
process_plate(
plate,
filename = NULL,
output_dir = "normalised_data",
write_output = TRUE,
normalisation_type = "RAU",
data_type = "Median",
sample_type_filter = "ALL",
blank_adjustment = FALSE,
verbose = TRUE,
reference_dilution = 1/400,
...
)
Arguments
plate |
A Plate object containing raw or processed Luminex data. |
filename |
( |
output_dir |
( |
write_output |
( |
normalisation_type |
(
|
data_type |
( |
sample_type_filter |
( |
blank_adjustment |
( |
verbose |
( |
reference_dilution |
( |
... |
Additional arguments passed to the model fitting function |
Details
Supported normalisation types:
-
RAU (Relative Antibody Units): Requires model fitting. Produces estimates using a standard curve. See
create_standard_curve_model_analyte
for details. -
nMFI (Normalised Median Fluorescence Intensity): Requires a reference dilution. See
get_nmfi
. -
MFI (Blank-adjusted Median Fluorescence Intensity): Returns raw MFI values (adjusted for blanks, if requested).
Value
A data frame of computed values, with test samples as rows and analytes as columns.
RAU Workflow
Optionally perform blank adjustment.
Fit a model for each analyte using standard curve data.
Predict RAU values for test samples.
Aggregate and optionally save results.
nMFI Workflow
Optionally perform blank adjustment.
Compute normalised MFI using the
reference_dilution
.Aggregate and optionally save results.
MFI Workflow
Optionally perform blank adjustment.
Return adjusted MFI values.
See Also
create_standard_curve_model_analyte
, get_nmfi
Examples
plate_file <- system.file("extdata", "CovidOISExPONTENT_CO_reduced.csv", package = "SerolyzeR")
layout_file <- system.file("extdata", "CovidOISExPONTENT_CO_layout.xlsx", package = "SerolyzeR")
plate <- read_luminex_data(plate_file, layout_file, verbose = FALSE)
example_dir <- tempdir(check = TRUE)
# Process using default settings (RAU normalisation)
process_plate(plate, output_dir = example_dir)
# Use a custom filename and skip blank adjustment
process_plate(plate,
filename = "no_blank.csv",
output_dir = example_dir,
blank_adjustment = FALSE
)
# Use nMFI normalisation with reference dilution
process_plate(plate,
normalisation_type = "nMFI",
reference_dilution = "1/400",
output_dir = example_dir
)