tests/testthat/test-build_evaluation_sheet.R
In bjoleary/dxr: Diagnostic Product Evaluation in R
# Error checking ---------------------------------------------------------------
test_that("evaluations and panels must have compatable analytes", {
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Sputum",
analytes = "SARS-CoV-2 Antigen",
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = "Garbage",
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "^At least one of the analytes.*Garbage.*"
)
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "^At least one of the analytes.*"
)
})
test_that("evaluations and panels should have compatible qual outcomes", {
expect_warning(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Equivocal", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "^At least one of the qualitative outcomes.*Equivocal.*Equivocal"
)
})
test_that("input checking works", {
expect_type(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
type = "list"
)
bad_char_input <-
list(
1L, # Not a character
c("Name 1", "Name 2"), # Not length 1
NA_character_, # NA
NULL # Null
)
for (bad_input in bad_char_input) {
# Evaluation Name
expect_error(
object =
build_evaluation_sheet(
evaluation_name = bad_input,
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(evaluation_name\\).* is not TRUE"
)
}
bad_input_na_ok <-
list(
1L, # Not a character
c("Name 1", "Name 2") # Not length 1
)
for (bad_input in bad_input_na_ok) {
# Evaluation Description
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = bad_input,
developer = "Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(evaluation_description\\).* is not TRUE"
)
# Developer
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = bad_input,
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(developer\\).* is not TRUE"
)
# Assay
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = bad_input,
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(assay\\).* is not TRUE"
)
# Quantitative Units
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = bad_input
),
regexp = "\\(quantitative_units\\).* is not TRUE"
)
}
bad_vector <- c(1:14)
# Lot numbers
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = bad_vector,
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(lot_numbers.* is not TRUE"
)
# Qualitative outcomes
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = bad_vector,
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(qualitative_outcomes.* is not TRUE"
)
# Semi-quantitative outcomes
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = bad_vector,
quantitative_units = NA_character_
),
regexp = "\\(semiquantitative_outcomes.* is not TRUE"
)
# Blind is not logical
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
blind = "TRUE"
),
regexp = "\\(blind\\) is not TRUE"
)
# Randomize is not logical
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = "TRUE"
),
regexp = "\\(randomize\\) is not TRUE"
)
})
# Build sheet ------------------------------------------------------------------
test_that("building the evaluation sheet works", {
# First, let's build the expected output
good_output <-
list(
evaluation_metadata =
structure(
list(
name =
c("evaluation_name", "evaluation_description", "developer",
"assay", "lot_numbers", "analytes", "targets",
"qualitative_outcomes", "semiquantitative_outcomes",
"quantitative_units", "blinded"),
value =
list("Test Evaluation", "A test...", "Test Developer",
"The assay Name", "20200101", c("IgM", "IgG", "Pan-Ig"),
"RBD", c("Positive", "Negative"), NA_character_,
NA_character_, FALSE)),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -11L)),
sample_blinding =
structure(
list(
evaluation_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5"),
panel_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5")),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -5L)),
evaluation_table =
structure(
list(
sample =
c("just_a_test_1", "just_a_test_1", "just_a_test_1",
"just_a_test_2", "just_a_test_2", "just_a_test_2",
"just_a_test_3", "just_a_test_3", "just_a_test_3",
"just_a_test_4", "just_a_test_4", "just_a_test_4",
"just_a_test_5", "just_a_test_5", "just_a_test_5"),
analyte =
c("IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG",
"Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig"),
target =
c("RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD",
"RBD", "RBD", "RBD", "RBD", "RBD", "RBD"),
lot_number =
c("20200101", "20200101", "20200101", "20200101", "20200101",
"20200101", "20200101", "20200101", "20200101", "20200101",
"20200101", "20200101", "20200101", "20200101", "20200101"),
datetime_observation =
structure(
c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_),
tzone = "UTC",
class = c("POSIXct", "POSIXt")),
qualitative_result =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_),
notes_and_anomalies =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_)),
row.names = c(NA, -15L),
class = c("tbl_df", "tbl", "data.frame")
)
)
# Save the panel data to a temporary location
filepath_temp_panel <- tempfile(fileext = ".xlsx")
write_panel_sheet(
panel_sheet_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
filepath = filepath_temp_panel
)
# Now let's put it all in using standard functions
expect_equal(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
expected = good_output
)
# And again using the panel filepath
expect_equal(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data = NA,
panel_data_filepath = filepath_temp_panel,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
expected = good_output
)
})
test_that("you can't provide panel and panel filepath", {
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = "bad_move_there_friend.xlsx",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
regexp =
"^You supplied both a panel_data object and a panel_data_filepath.*"
)
})
test_that("multiple lot numbers results in NA column", {
# First, let's build the expected output
good_output <-
list(
evaluation_metadata =
structure(
list(
name =
c("evaluation_name", "evaluation_description", "developer",
"assay", "lot_numbers", "analytes", "targets",
"qualitative_outcomes", "semiquantitative_outcomes",
"quantitative_units", "blinded"),
value =
list("Test Evaluation", "A test...", "Test Developer",
"The assay Name", c("20200101", "20200102"),
c("IgM", "IgG", "Pan-Ig"),
"RBD", c("Positive", "Negative"), NA_character_,
NA_character_, FALSE)),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -11L)),
sample_blinding =
structure(
list(
evaluation_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5"),
panel_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5")),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -5L)),
evaluation_table =
structure(
list(
sample =
c("just_a_test_1", "just_a_test_1", "just_a_test_1",
"just_a_test_2", "just_a_test_2", "just_a_test_2",
"just_a_test_3", "just_a_test_3", "just_a_test_3",
"just_a_test_4", "just_a_test_4", "just_a_test_4",
"just_a_test_5", "just_a_test_5", "just_a_test_5"),
analyte =
c("IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG",
"Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig"),
target =
c("RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD",
"RBD", "RBD", "RBD", "RBD", "RBD", "RBD"),
lot_number =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_),
datetime_observation =
structure(
c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_),
tzone = "UTC",
class = c("POSIXct", "POSIXt")),
qualitative_result =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_),
notes_and_anomalies =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_)),
row.names = c(NA, -15L),
class = c("tbl_df", "tbl", "data.frame")
)
)
expect_equal(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = c("20200101", "20200102"),
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
expected = good_output
)
})
test_that("semiquantitative_outcomes behave as expected", {
skip("TODO")
})
test_that("quantitative_units behaves as expected", {
skip("TODO")
})
bjoleary/dxr documentation built on Dec. 5, 2023, 8:33 p.m.
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# Error checking ---------------------------------------------------------------
test_that("evaluations and panels must have compatable analytes", {
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Sputum",
analytes = "SARS-CoV-2 Antigen",
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = "Garbage",
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "^At least one of the analytes.*Garbage.*"
)
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "^At least one of the analytes.*"
)
})
test_that("evaluations and panels should have compatible qual outcomes", {
expect_warning(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Equivocal", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "^At least one of the qualitative outcomes.*Equivocal.*Equivocal"
)
})
test_that("input checking works", {
expect_type(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
type = "list"
)
bad_char_input <-
list(
1L, # Not a character
c("Name 1", "Name 2"), # Not length 1
NA_character_, # NA
NULL # Null
)
for (bad_input in bad_char_input) {
# Evaluation Name
expect_error(
object =
build_evaluation_sheet(
evaluation_name = bad_input,
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(evaluation_name\\).* is not TRUE"
)
}
bad_input_na_ok <-
list(
1L, # Not a character
c("Name 1", "Name 2") # Not length 1
)
for (bad_input in bad_input_na_ok) {
# Evaluation Description
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = bad_input,
developer = "Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(evaluation_description\\).* is not TRUE"
)
# Developer
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = bad_input,
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(developer\\).* is not TRUE"
)
# Assay
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = bad_input,
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(assay\\).* is not TRUE"
)
# Quantitative Units
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = bad_input
),
regexp = "\\(quantitative_units\\).* is not TRUE"
)
}
bad_vector <- c(1:14)
# Lot numbers
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = bad_vector,
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(lot_numbers.* is not TRUE"
)
# Qualitative outcomes
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = bad_vector,
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_
),
regexp = "\\(qualitative_outcomes.* is not TRUE"
)
# Semi-quantitative outcomes
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = bad_vector,
quantitative_units = NA_character_
),
regexp = "\\(semiquantitative_outcomes.* is not TRUE"
)
# Blind is not logical
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
blind = "TRUE"
),
regexp = "\\(blind\\) is not TRUE"
)
# Randomize is not logical
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "A test",
evaluation_description = "A test...",
developer = "Developer",
assay = "Assay",
lot_numbers = "1234567",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = "TRUE"
),
regexp = "\\(randomize\\) is not TRUE"
)
})
# Build sheet ------------------------------------------------------------------
test_that("building the evaluation sheet works", {
# First, let's build the expected output
good_output <-
list(
evaluation_metadata =
structure(
list(
name =
c("evaluation_name", "evaluation_description", "developer",
"assay", "lot_numbers", "analytes", "targets",
"qualitative_outcomes", "semiquantitative_outcomes",
"quantitative_units", "blinded"),
value =
list("Test Evaluation", "A test...", "Test Developer",
"The assay Name", "20200101", c("IgM", "IgG", "Pan-Ig"),
"RBD", c("Positive", "Negative"), NA_character_,
NA_character_, FALSE)),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -11L)),
sample_blinding =
structure(
list(
evaluation_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5"),
panel_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5")),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -5L)),
evaluation_table =
structure(
list(
sample =
c("just_a_test_1", "just_a_test_1", "just_a_test_1",
"just_a_test_2", "just_a_test_2", "just_a_test_2",
"just_a_test_3", "just_a_test_3", "just_a_test_3",
"just_a_test_4", "just_a_test_4", "just_a_test_4",
"just_a_test_5", "just_a_test_5", "just_a_test_5"),
analyte =
c("IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG",
"Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig"),
target =
c("RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD",
"RBD", "RBD", "RBD", "RBD", "RBD", "RBD"),
lot_number =
c("20200101", "20200101", "20200101", "20200101", "20200101",
"20200101", "20200101", "20200101", "20200101", "20200101",
"20200101", "20200101", "20200101", "20200101", "20200101"),
datetime_observation =
structure(
c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_),
tzone = "UTC",
class = c("POSIXct", "POSIXt")),
qualitative_result =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_),
notes_and_anomalies =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_)),
row.names = c(NA, -15L),
class = c("tbl_df", "tbl", "data.frame")
)
)
# Save the panel data to a temporary location
filepath_temp_panel <- tempfile(fileext = ".xlsx")
write_panel_sheet(
panel_sheet_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
filepath = filepath_temp_panel
)
# Now let's put it all in using standard functions
expect_equal(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
expected = good_output
)
# And again using the panel filepath
expect_equal(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data = NA,
panel_data_filepath = filepath_temp_panel,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
expected = good_output
)
})
test_that("you can't provide panel and panel filepath", {
expect_error(
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = "20200101",
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = "bad_move_there_friend.xlsx",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
regexp =
"^You supplied both a panel_data object and a panel_data_filepath.*"
)
})
test_that("multiple lot numbers results in NA column", {
# First, let's build the expected output
good_output <-
list(
evaluation_metadata =
structure(
list(
name =
c("evaluation_name", "evaluation_description", "developer",
"assay", "lot_numbers", "analytes", "targets",
"qualitative_outcomes", "semiquantitative_outcomes",
"quantitative_units", "blinded"),
value =
list("Test Evaluation", "A test...", "Test Developer",
"The assay Name", c("20200101", "20200102"),
c("IgM", "IgG", "Pan-Ig"),
"RBD", c("Positive", "Negative"), NA_character_,
NA_character_, FALSE)),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -11L)),
sample_blinding =
structure(
list(
evaluation_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5"),
panel_sample_id =
c("just_a_test_1", "just_a_test_2", "just_a_test_3",
"just_a_test_4", "just_a_test_5")),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -5L)),
evaluation_table =
structure(
list(
sample =
c("just_a_test_1", "just_a_test_1", "just_a_test_1",
"just_a_test_2", "just_a_test_2", "just_a_test_2",
"just_a_test_3", "just_a_test_3", "just_a_test_3",
"just_a_test_4", "just_a_test_4", "just_a_test_4",
"just_a_test_5", "just_a_test_5", "just_a_test_5"),
analyte =
c("IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG",
"Pan-Ig", "IgM", "IgG", "Pan-Ig", "IgM", "IgG", "Pan-Ig"),
target =
c("RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD", "RBD",
"RBD", "RBD", "RBD", "RBD", "RBD", "RBD"),
lot_number =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_),
datetime_observation =
structure(
c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_),
tzone = "UTC",
class = c("POSIXct", "POSIXt")),
qualitative_result =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_),
notes_and_anomalies =
c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_)),
row.names = c(NA, -15L),
class = c("tbl_df", "tbl", "data.frame")
)
)
expect_equal(
# Working example -- no error
object =
build_evaluation_sheet(
evaluation_name = "Test Evaluation",
evaluation_description = "A test...",
developer = "Test Developer",
assay = "The assay Name",
lot_numbers = c("20200101", "20200102"),
panel_data =
build_panel_sheet(
panel_name = "Just a test",
panel_description = "A test case.",
n_samples = 5L,
sample_groups = "Samples",
sample_matrices = "Serum",
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "Spike",
qualitative_outcomes = c("Positive", "Negative"),
qualitative_comparators = "Authorized NAAT and CDC Assay",
semiquantitative_outcomes = NA,
semiquantitative_comparators = NA,
quantitative_units = NA,
quantitative_comparators = NA
),
panel_data_filepath = NA,
analytes = c("IgM", "IgG", "Pan-Ig"),
targets = "RBD",
qualitative_outcomes = c("Positive", "Negative"),
semiquantitative_outcomes = NA_character_,
quantitative_units = NA_character_,
randomize = FALSE,
blind = FALSE
),
expected = good_output
)
})
test_that("semiquantitative_outcomes behave as expected", {
skip("TODO")
})
test_that("quantitative_units behaves as expected", {
skip("TODO")
})
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