Process assay test result to titer

Usage

to_titer(
  df,
  model = "4PL",
  positive_threshold = NULL,
  ci = 0.95,
  negative_control = TRUE
)

df: - a standardized data.frame generated by`standardize_data()`
model: - either the name of a built-in model to fit standard curve or a named list of 2 functions for "mod" and "quantify_ci"
positive_threshold: - if not NULL, processed_data will have the serostatus labeled
ci: - confidence interval for the titer estimates
negative_control: - if TRUE, output tibble will include the result for negative controls

a data.frame with 8 columns

plate_id: id of the plate
data: list of `data.frame`s containing the results from each plate
antitoxin_df: list of `data.frame`s containing the results for antitoxins from each plate
standard_curve_func: list of functions mapping from OD to titer for each plate
std_crv_midpoint: midpoint of the standard curve, for qualitative analysis
processed_data: list of `tibble`s containing samples with titer estimates (lower, median, upper)
negative_control: list of `tibble`s containing negative control check results (if `negative_control=TRUE`)