tests/testthat/test-model.R

In SerolyzeR: Reading, Quality Control and Preprocessing of MBA (Multiplex Bead Assay) Data

library(testthat)

test_that("Artificial model with insufficient number of analytes", {
  expect_no_error(
    model <- Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(0.1, 0.2),
      mfi = c(100, 50)
    )
  )

  expect_no_error(print(model))

  expect_equal(model$top_asymptote, 100)
  expect_equal(model$bottom_asymptote, 50)
})

test_that("Test high dose hook detection and handling", {
  dilutions <- c(
    1 / 50, 1 / 100, 1 / 200, 1 / 400, 1 / 800, 1 / 1600, 1 / 4000, 1 / 16000
  )
  # Normal case
  mfi <- c(2000, 1000, 500, 300, 200, 100, 50, 25)
  expect_true(all(handle_high_dose_hook(mfi, dilutions)))

  # High dose hook
  mfi <- c(2000, 500, 1000, 300, 200, 100, 50, 200)
  expect_warning(p <- handle_high_dose_hook(mfi, dilutions))
  expect_equal(p, c(FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE))

  # High dose hook insufficient samples
  # That would remove all but 3 samples which is less than the minimum required
  expect_warning(p <- handle_high_dose_hook(mfi, dilutions, high_dose_threshold = 1 / 800))
  expect_true(all(p))

  # Another high dose hook
  mfi <- c(2000, 1000, 500, 300, 200, 100, 50, 200)
  dilutions <- c(
    1 / 100, 1 / 50, 1 / 200, 1 / 400, 1 / 800, 1 / 1600, 1 / 4000, 1 / 16000
  )
  expect_warning(p <- handle_high_dose_hook(mfi, dilutions))
  expect_equal(p, c(FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE))
})

test_that("Test high dose hook on a plate object", {
  path <- system.file("extdata", "CovidOISExPONTENT.csv", package = "SerolyzeR", mustWork = TRUE)
  layout_path <- system.file("extdata", "CovidOISExPONTENT_layout.xlsx", package = "SerolyzeR", mustWork = TRUE)
  expect_no_error(plate <- read_luminex_data(path, format = "xPONENT", layout_filepath = layout_path, verbose = FALSE))

  plate$dilutions[c(2, 3)] <- plate$dilutions[c(3, 2)]
  plate$dilution_values[c(2, 3)] <- plate$dilution_values[c(3, 2)]

  expect_warning(model <- create_standard_curve_model_analyte(plate, "S2"))
})


test_that("Validation checks", {
  # Incompatible lengths
  expect_error(
    Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(0.1),
      mfi = c(100, 50)
    )
  )

  # dilutions outside the interval [0,1]
  expect_error(
    Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(-0.1, 1.1),
      mfi = c(100, 50)
    )
  )


  # negative mfi below zero
  expect_error(
    Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(0.1, 0.9),
      mfi = c(-5, -4)
    )
  )

  # NA in MFI
  expect_error(
    Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(0.1, 0.9),
      mfi = c(4, NA)
    )
  )



  # negative mfi below zero
  expect_error(
    Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(0.1, 0.9),
      mfi = c(10, 20),
      mfi_min = -15
    )
  )


  # incorrect types
  expect_error(
    Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(0.1, 0.9),
      mfi = c(-5, -4)
    )
  )

  # only one MFI value
  expect_error(
    Model$new(
      analyte = "Spike_6P_IPP",
      dilutions = c(0.1, 0.9),
      mfi = c(10, 10)
    )
  )
})