diff --git a/DESCRIPTION b/DESCRIPTION
index bd98e648..454f93db 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -32,15 +32,14 @@ Imports:
     shinyjs,
     shinyvalidate,
     stats,
-    teal.data (>= 0.3.0.9010),
+    teal.data (>= 0.3.0.9017),
     teal.logger (>= 0.1.1),
-    teal.slice (>= 0.4.0.9023),
     teal.widgets (>= 0.4.0),
     tidyr (>= 0.8.3),
     tidyselect
 Suggests:
     knitr (>= 1.42),
-    shinytest (>= 1.5.1),
+    rmarkdown (>= 2.19),
     teal.code (>= 0.4.0),
     testthat (>= 3.1.5)
 VignetteBuilder:
@@ -49,10 +48,10 @@ RdMacros:
     lifecycle
 Config/Needs/verdepcheck: tidyverse/magrittr, mllg/checkmate,
     tidyverse/dplyr, r-lib/lifecycle, daroczig/logger, r-lib/rlang,
-    rstudio/shiny, daattali/shinyjs, rstudio/shinyvalidate,
+    rstudio/rmarkdown, rstudio/shiny, daattali/shinyjs, rstudio/shinyvalidate,
     insightsengineering/teal.data, insightsengineering/teal.logger,
-    insightsengineering/teal.slice, insightsengineering/teal.widgets,
-    tidyverse/tidyr, r-lib/tidyselect, yihui/knitr, rstudio/shinytest,
+    insightsengineering/teal.widgets,
+    tidyverse/tidyr, r-lib/tidyselect, yihui/knitr,
     insightsengineering/teal.code, r-lib/testthat
 Config/Needs/website: insightsengineering/nesttemplate
 Encoding: UTF-8
diff --git a/NAMESPACE b/NAMESPACE
index 8aedd686..49700e8d 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -2,10 +2,15 @@
 
 S3method(data_extract_multiple_srv,FilteredData)
 S3method(data_extract_multiple_srv,list)
+S3method(data_extract_multiple_srv,reactive)
 S3method(data_extract_srv,FilteredData)
 S3method(data_extract_srv,list)
 S3method(filter_spec_internal,default)
 S3method(filter_spec_internal,delayed_data)
+S3method(merge_expression_module,list)
+S3method(merge_expression_module,reactive)
+S3method(merge_expression_srv,list)
+S3method(merge_expression_srv,reactive)
 S3method(print,choices_labeled)
 S3method(print,delayed_choices_selected)
 S3method(print,delayed_data_extract_spec)
@@ -24,12 +29,8 @@ S3method(resolve,delayed_variable_choices)
 S3method(resolve,list)
 S3method(resolve_delayed,FilteredData)
 S3method(resolve_delayed,list)
-S3method(value_choices,TealDataset)
-S3method(value_choices,TealDatasetConnector)
 S3method(value_choices,character)
 S3method(value_choices,data.frame)
-S3method(variable_choices,TealDataset)
-S3method(variable_choices,TealDatasetConnector)
 S3method(variable_choices,character)
 S3method(variable_choices,data.frame)
 export(add_no_selected_choices)
@@ -42,8 +43,6 @@ export(data_extract_multiple_srv)
 export(data_extract_spec)
 export(data_extract_srv)
 export(data_extract_ui)
-export(data_merge_module)
-export(data_merge_srv)
 export(datanames_input)
 export(filter_spec)
 export(format_data_extract)
diff --git a/R/Queue.R b/R/Queue.R
index bceaf0b2..4709a267 100644
--- a/R/Queue.R
+++ b/R/Queue.R
@@ -105,6 +105,5 @@ Queue <- R6::R6Class( # nolint
   private = list(
     array = c()
   ),
-
   lock_class = TRUE
 )
diff --git a/R/check_selector.R b/R/check_selector.R
index cd3617e4..53de6540 100644
--- a/R/check_selector.R
+++ b/R/check_selector.R
@@ -21,9 +21,10 @@ check_selector_filters <- function(filters) {
     is.list(x) &&
       all(c("columns", "selected") %in% names(x)) &&
       checkmate::test_character(x$columns, null.ok = TRUE, min.len = 1, any.missing = FALSE) &&
-      (is.null(x$selected) ||
-        all(vapply(x$selected, is.character, logical(1))) ||
-        all(vapply(x$selected, is.numeric, logical(1)))
+      (
+        is.null(x$selected) ||
+          all(vapply(x$selected, is.character, logical(1))) ||
+          all(vapply(x$selected, is.numeric, logical(1)))
       )
   }
   stopifnot(is.null(filters) || all(vapply(filters, check_selector_filter, logical(1))))
diff --git a/R/choices_labeled.R b/R/choices_labeled.R
index 93fcc2c7..bf44ddaa 100644
--- a/R/choices_labeled.R
+++ b/R/choices_labeled.R
@@ -117,10 +117,9 @@ choices_labeled <- function(choices, labels, subset = NULL, types = NULL) {
 #'
 #' @description `r lifecycle::badge("stable")`
 #'
-#' @param data (`data.frame`, `character`, `TealDataset`, `TealDatasetConnector`)
+#' @param data (`data.frame`, `character`)
 #' If `data.frame`, then data to extract labels from
 #' If `character`, then name of the dataset to extract data from once available
-#' If `TealDataset` or `TealDatasetConnector`, then raw data to extract labels from.
 #' @param subset (`character` or `function`)
 #' If `character`, then a vector of column names.
 #' If `function`, then this function is used to determine the possible columns (e.g. all factor columns).
@@ -144,22 +143,15 @@ choices_labeled <- function(choices, labels, subset = NULL, types = NULL) {
 #' variable_choices(ADRS)
 #' variable_choices(ADRS, subset = c("PARAM", "PARAMCD"))
 #' variable_choices(ADRS, subset = c("", "PARAM", "PARAMCD"))
-#' variable_choices(ADRS, subset = c("", "PARAM", "PARAMCD"), key = teal.data::get_cdisc_keys("ADRS"))
+#' variable_choices(
+#'   ADRS,
+#'   subset = c("", "PARAM", "PARAMCD"),
+#'   key = teal.data::default_cdisc_join_keys["ADRS", "ADRS"]
+#' )
 #'
 #' # delayed version
 #' variable_choices("ADRS", subset = c("USUBJID", "STUDYID"))
 #'
-#' # also works with [teal.data::TealDataset] and [teal.data::TealDatasetConnector]
-#' ADRS_dataset <- teal.data::dataset("ADRS", ADRS, key = teal.data::get_cdisc_keys("ADRS"))
-#' variable_choices(ADRS_dataset)
-#'
-#' ADRS_conn <- teal.data::dataset_connector(
-#'   "ADRS",
-#'   pull_callable = teal.data::callable_code("radrs(cached = TRUE)"),
-#'   key = teal.data::get_cdisc_keys("ADRS")
-#' )
-#' variable_choices(ADRS_conn)
-#'
 #' # functional subset (with delayed data) - return only factor variables
 #' variable_choices("ADRS", subset = function(data) {
 #'   idx <- vapply(data, is.factor, logical(1))
@@ -205,7 +197,8 @@ variable_choices.data.frame <- function(data, subset = NULL, fill = TRUE, key =
 
   key <- intersect(subset, key)
 
-  var_types <- stats::setNames(teal.slice:::variable_types(data = data), names(data))
+  var_types <- vapply(data, function(x) class(x)[[1]], character(1))
+
   if (length(key) != 0) {
     var_types[key] <- "primary_key"
   }
@@ -237,49 +230,13 @@ variable_choices.data.frame <- function(data, subset = NULL, fill = TRUE, key =
   return(res)
 }
 
-#' @rdname variable_choices
-#' @export
-variable_choices.TealDataset <- function(data, subset = NULL, fill = FALSE, key = teal.data::get_keys(data)) {
-  variable_choices(
-    data = teal.data::get_raw_data(data),
-    subset = subset,
-    fill = fill,
-    key = key
-  )
-}
-
-#' @rdname variable_choices
-#' @export
-variable_choices.TealDatasetConnector <- function(data, # nolint
-                                                  subset = NULL,
-                                                  fill = FALSE,
-                                                  key = teal.data::get_keys(data)) {
-  if (teal.data::is_pulled(data)) {
-    variable_choices(
-      data = teal.data::get_raw_data(data),
-      subset = subset,
-      fill = fill,
-      key = key
-    )
-  } else {
-    variable_choices(
-      data = teal.data::get_dataname(data),
-      subset = subset,
-      fill = fill,
-      key = key
-    )
-  }
-}
-
-
 #' Wrapper on [choices_labeled] to label variable values basing on other variable values
 #'
 #' @description `r lifecycle::badge("stable")`
 #'
-#' @param data (`data.frame`, `character`, `TealDataset`, `TealDatasetConnector`)
-#' If `data.frame`, then data to extract labels from
-#' If `character`, then name of the dataset to extract data from once available
-#' If `TealDataset` or `TealDatasetConnector`, then raw data to extract labels from.
+#' @param data (`data.frame`, `character`)
+#' If `data.frame`, then data to extract labels from.
+#' If `character`, then name of the dataset to extract data from once available.
 #' @param var_choices (`character` or `NULL`) vector with choices column names
 #' @param var_label (`character`) vector with labels column names
 #' @param subset (`character` or `function`)
@@ -407,47 +364,6 @@ value_choices.data.frame <- function(data, # nolint
   return(res)
 }
 
-#' @rdname value_choices
-#' @export
-value_choices.TealDataset <- function(data,
-                                      var_choices,
-                                      var_label = NULL,
-                                      subset = NULL,
-                                      sep = " - ") {
-  value_choices(
-    data = teal.data::get_raw_data(data),
-    var_choices = var_choices,
-    var_label = var_label,
-    subset = subset,
-    sep = sep
-  )
-}
-
-#' @rdname value_choices
-#' @export
-value_choices.TealDatasetConnector <- function(data, # nolint
-                                               var_choices,
-                                               var_label = NULL,
-                                               subset = NULL,
-                                               sep = " - ") {
-  if (teal.data::is_pulled(data)) {
-    value_choices(
-      data = teal.data::get_raw_data(data),
-      var_choices = var_choices,
-      var_label = var_label,
-      subset = subset,
-      sep = sep
-    )
-  } else {
-    value_choices(
-      data = teal.data::get_dataname(data),
-      var_choices = var_choices,
-      var_label = var_label,
-      subset = subset,
-      sep = sep
-    )
-  }
-}
 #' Print choices_labeled object
 #' @description `r lifecycle::badge("stable")`
 #' @rdname choices_labeled
diff --git a/R/choices_selected.R b/R/choices_selected.R
index dd94e199..5c182015 100644
--- a/R/choices_selected.R
+++ b/R/choices_selected.R
@@ -148,16 +148,7 @@ choices_selected <- function(choices,
   # remove duplicates
   choices <- vector_remove_dups(choices)
   selected <- vector_remove_dups(selected)
-
-  if (!all(selected %in% choices)) {
-    stop(paste(
-      paste(
-        selected[which(!selected %in% choices)],
-        collapse = ", "
-      ),
-      "'selected' but not in 'choices'"
-    ))
-  }
+  checkmate::assert_subset(selected, choices)
 
   if (!keep_order && length(choices) > 0) {
     choices_in_selected <- which(choices %in% selected)
diff --git a/R/data_extract_datanames.R b/R/data_extract_datanames.R
index fd5a7099..0d2d156b 100644
--- a/R/data_extract_datanames.R
+++ b/R/data_extract_datanames.R
@@ -37,9 +37,7 @@ get_extract_datanames <- function(data_extracts) {
   stopifnot(length(data_extracts) > 0)
   stopifnot(
     checkmate::test_list(data_extracts, types = "data_extract_spec") ||
-      all(
-        vapply(data_extracts, function(x) checkmate::test_list(x, types = "data_extract_spec"), logical(1))
-      )
+      all(vapply(data_extracts, function(x) checkmate::test_list(x, types = "data_extract_spec"), logical(1)))
   )
 
   datanames <- lapply(data_extracts, function(x) {
diff --git a/R/data_extract_filter_module.R b/R/data_extract_filter_module.R
index e37dee0b..21dc2b73 100644
--- a/R/data_extract_filter_module.R
+++ b/R/data_extract_filter_module.R
@@ -18,9 +18,9 @@ data_extract_filter_ui <- function(filter, id = "filter") {
 
   html_col <- teal.widgets::optionalSelectInput(
     inputId = ns("col"),
-    label = filter$vars_label,
-    choices = filter$vars_choices,
-    selected = filter$vars_selected,
+    label = `if`(inherits(filter, "delayed_filter_spec"), NULL, filter$vars_label),
+    choices = `if`(inherits(filter, "delayed_filter_spec"), NULL, filter$vars_choices),
+    selected = `if`(inherits(filter, "delayed_filter_spec"), NULL, filter$vars_selected),
     multiple = filter$vars_multiple,
     fixed = filter$vars_fixed
   )
@@ -28,8 +28,8 @@ data_extract_filter_ui <- function(filter, id = "filter") {
   html_vals <- teal.widgets::optionalSelectInput(
     inputId = ns("vals"),
     label = filter$label,
-    choices = filter$choices,
-    selected = filter$selected,
+    choices = `if`(inherits(filter, "delayed_filter_spec"), NULL, filter$choices),
+    selected = `if`(inherits(filter, "delayed_filter_spec"), NULL, filter$selected),
     multiple = filter$multiple,
     fixed = filter$fixed
   )
@@ -60,19 +60,31 @@ data_extract_filter_srv <- function(id, datasets, filter) {
       # We force the evaluation of filter, otherwise the observers are set up with the last element
       # of the list in data_extract_single_srv and not all of them (due to R lazy evaluation)
       force(filter)
-      logger::log_trace(
-        "data_extract_filter_srv initialized with: { filter$dataname } dataset."
-      )
+      logger::log_trace("data_extract_filter_srv initialized with: { filter$dataname } dataset.")
+
+      isolate({
+        # when the filter is initialized with a delayed spec, the choices and selected are NULL
+        # here delayed are resolved and the values are set up
+        teal.widgets::updateOptionalSelectInput(
+          session = session,
+          inputId = "col",
+          choices = filter$vars_choices,
+          selected = filter$vars_selected
+        )
+        teal.widgets::updateOptionalSelectInput(
+          session = session,
+          inputId = "vals",
+          choices = filter$choices,
+          selected = filter$selected
+        )
+      })
 
-      observeEvent(input$col,
+      observeEvent(
+        input$col,
+        ignoreInit = TRUE, # When observeEvent is initialized input$col is still NULL as it is set few lines above
+        ignoreNULL = FALSE, # columns could be NULL, then vals should be set to NULL also
         handlerExpr = {
-          if (!filter$initialized) {
-            initial_inputs <- get_initial_filter_values(filter, datasets)
-            choices <- initial_inputs$choices
-            selected <- initial_inputs$selected
-            filter$initialized <- TRUE
-            filter <<- filter
-          } else if (!rlang::is_empty(input$col)) {
+          if (!rlang::is_empty(input$col)) {
             choices <- value_choices(
               datasets[[filter$dataname]](),
               input$col,
@@ -108,9 +120,7 @@ data_extract_filter_srv <- function(id, datasets, filter) {
             choices = choices,
             selected = selected
           )
-        },
-        ignoreInit = FALSE,
-        ignoreNULL = FALSE
+        }
       )
     }
   )
diff --git a/R/data_extract_module.R b/R/data_extract_module.R
index 87f2646a..9921ef00 100644
--- a/R/data_extract_module.R
+++ b/R/data_extract_module.R
@@ -250,7 +250,7 @@ check_data_extract_spec_react <- function(datasets, data_extract) {
 #'
 #' @inheritParams shiny::moduleServer
 #' @param datasets (`FilteredData` or `list` of `reactive` or non-`reactive` `data.frame`)\cr
-#'  object containing data either in the form of [teal.slice::FilteredData] or as a list of `data.frame`.
+#'  object containing data either in the form of `FilteredData` or as a list of `data.frame`.
 #'  When passing a list of non-reactive `data.frame` objects, they are converted to reactive `data.frame`s internally.
 #'  When passing a list of reactive or non-reactive `data.frame` objects, the argument `join_keys` is required also.
 #' @param data_extract_spec (`data_extract_spec` or a list of `data_extract_spec`)\cr
@@ -349,13 +349,6 @@ check_data_extract_spec_react <- function(datasets, data_extract) {
 #'   shinyApp(app$ui, app$server)
 #' }
 #'
-#' # Using FilteredData - Note this method will be deprecated
-#' datasets <- teal.slice::init_filtered_data(
-#'   list(ADSL = list(dataset = ADSL)),
-#'   join_keys = teal.data::join_keys(
-#'     teal.data::join_key("ADSL", "ADSL", c("USUBJID", "STUDYID"))
-#'   )
-#' )
 #'
 #' app <- shinyApp(
 #'   ui = fluidPage(
@@ -551,7 +544,6 @@ data_extract_srv.list <- function(id, datasets, data_extract_spec, join_keys = N
 #' @description `r lifecycle::badge("experimental")`
 #' `data_extract_multiple_srv` loops over the list of `data_extract` given and
 #' runs `data_extract_srv` for each one returning a list of reactive objects.
-#' This was suitable as input for (deprecated) [data_merge_srv()].
 #'
 #' @inheritParams data_extract_srv
 #' @param data_extract (named `list` of `data_extract_spec` objects) the list `data_extract_spec` objects.
@@ -655,15 +647,23 @@ data_extract_srv.list <- function(id, datasets, data_extract_spec, join_keys = N
 #' }
 data_extract_multiple_srv <- function(data_extract, datasets, ...) {
   checkmate::assert_list(data_extract, names = "named")
+  checkmate::assert_multi_class(datasets, c("reactive", "FilteredData", "list"))
   lapply(data_extract, function(x) {
     if (is.list(x) && !inherits(x, "data_extract_spec")) {
       checkmate::assert_list(x, "data_extract_spec")
     }
   })
-  checkmate::assert_multi_class(datasets, classes = c("FilteredData", "list"))
   UseMethod("data_extract_multiple_srv", datasets)
 }
 
+#' @rdname data_extract_multiple_srv
+#' @export
+data_extract_multiple_srv.reactive <- function(data_extract, datasets, ...) {
+  # convert reactive containing teal_data to list of reactives with one dataset each
+  datasets_new <- convert_teal_data(datasets)
+  data_extract_multiple_srv.list(data_extract, datasets_new, ...)
+}
+
 #' @rdname data_extract_multiple_srv
 #' @export
 data_extract_multiple_srv.FilteredData <- function(data_extract, datasets, ...) {
diff --git a/R/data_extract_read_module.R b/R/data_extract_read_module.R
index 8425c284..15eeaa8f 100644
--- a/R/data_extract_read_module.R
+++ b/R/data_extract_read_module.R
@@ -30,9 +30,11 @@ data_extract_read_srv <- function(id, datasets, single_data_extract_spec, iv, se
         }
         for (col in input_col) {
           # replace NA with NA_character_ for class consistency
-          if (any(vapply(input_vals, identical, logical(1), "NA")) &&
-            anyNA(datasets[[x$dataname]]()[col]) &&
-            !any(vapply(unique(datasets[[x$dataname]]()[col]), identical, logical(1), "NA"))) {
+          if (
+            any(vapply(input_vals, identical, logical(1), "NA")) &&
+              anyNA(datasets[[x$dataname]]()[col]) &&
+              !any(vapply(unique(datasets[[x$dataname]]()[col]), identical, logical(1), "NA"))
+          ) {
             input_vals[vapply(input_vals, identical, logical(1), "NA")] <- NA_character_
           }
         }
diff --git a/R/data_extract_select_module.R b/R/data_extract_select_module.R
index f8c15fec..79d84ef4 100644
--- a/R/data_extract_select_module.R
+++ b/R/data_extract_select_module.R
@@ -20,8 +20,8 @@ data_extract_select_ui <- function(select, id = "select") {
     teal.widgets::optionalSelectInput(
       inputId = id,
       label = select$label,
-      choices = select$choices,
-      selected = select$selected,
+      choices = `if`(inherits(select, "delayed_select_spec"), NULL, select$choices),
+      selected = `if`(inherits(select, "delayed_select_spec"), NULL, select$selected),
       multiple = select$multiple,
       fixed = select$fixed
     )
diff --git a/R/data_extract_single_module.R b/R/data_extract_single_module.R
index de75f7bf..8616b0e8 100644
--- a/R/data_extract_single_module.R
+++ b/R/data_extract_single_module.R
@@ -73,11 +73,22 @@ data_extract_single_srv <- function(id, datasets, single_data_extract_spec) {
   moduleServer(
     id,
     function(input, output, session) {
-      logger::log_trace(
-        "data_extract_single_srv initialized with dataset: { single_data_extract_spec$dataname }."
-      )
-      for (idx in seq_along(single_data_extract_spec$filter)) {
-        x <- single_data_extract_spec$filter[[idx]]
+      logger::log_trace("data_extract_single_srv initialized with dataset: { single_data_extract_spec$dataname }.")
+
+      # ui could be initialized with a delayed select spec so the choices and selected are NULL
+      # here delayed are resolved
+      isolate({
+        resolved <- resolve_delayed(single_data_extract_spec, datasets)
+        teal.widgets::updateOptionalSelectInput(
+          session = session,
+          inputId = "select",
+          choices = resolved$select$choices,
+          selected = resolved$select$selected
+        )
+      })
+
+      for (idx in seq_along(resolved$filter)) {
+        x <- resolved$filter[[idx]]
         if (inherits(x, "filter_spec")) {
           data_extract_filter_srv(
             id = paste0("filter", idx),
diff --git a/R/data_extract_spec.R b/R/data_extract_spec.R
index 7c66f4a0..8bcdb78b 100644
--- a/R/data_extract_spec.R
+++ b/R/data_extract_spec.R
@@ -107,8 +107,10 @@ data_extract_spec <- function(dataname, select = NULL, filter = NULL, reshape =
 
   for (idx in seq_along(filter)) filter[[idx]]$dataname <- dataname
 
-  if (inherits(select, "delayed_select_spec") ||
-    any(vapply(filter, inherits, logical(1), "delayed_filter_spec"))) {
+  if (
+    inherits(select, "delayed_select_spec") ||
+      any(vapply(filter, inherits, logical(1), "delayed_filter_spec"))
+  ) {
     structure(
       list(dataname = dataname, select = select, filter = filter, reshape = reshape),
       class = c("delayed_data_extract_spec", "delayed_data", "data_extract_spec")
diff --git a/R/data_merge_module.R b/R/data_merge_module.R
deleted file mode 100644
index 781f32db..00000000
--- a/R/data_merge_module.R
+++ /dev/null
@@ -1,61 +0,0 @@
-#' Data merge module
-#'
-#' @description `r lifecycle::badge("deprecated")`
-#' @details This function was a convenient wrapper to combine `data_extract_multiple_srv()` and
-#' `data_merge_srv()` when no additional processing is required.
-#'
-#' @inheritParams shiny::moduleServer
-#' @param datasets (`FilteredData`)\cr
-#'  object containing data, see [teal.slice::FilteredData] for more.
-#' @param data_extract (named `list` of `data_extract_spec`)\cr
-#' @param merge_function (`character(1)`)\cr
-#'  A character string of a function that
-#'  accepts the arguments `x`, `y` and `by` to perform the merging of datasets.
-#' @param anl_name (`character(1)`)\cr
-#'  Name of the analysis dataset.
-#'
-#' @return reactive expression with output from [data_merge_srv()].
-#'
-#' @seealso [data_merge_srv()]
-#'
-#' @export
-data_merge_module <- function(datasets,
-                              data_extract,
-                              merge_function = "dplyr::full_join",
-                              anl_name = "ANL",
-                              id = "merge_id") {
-  lifecycle::deprecate_stop("0.3.1", "data_merge_module()")
-}
-
-
-#' Data merge module server
-#'
-#' @description `r lifecycle::badge("deprecated")`
-#' @details When additional processing of the `data_extract` list input was required, `data_merge_srv()` could be
-#'   combined with `data_extract_multiple_srv()` or `data_extract_srv()` to influence the `selector_list` input.
-#'
-#' @inheritParams shiny::moduleServer
-#' @param selector_list (`reactive`)\cr
-#'   output from [data_extract_multiple_srv()] or a reactive named list of outputs from [data_extract_srv()].
-#'   When using a reactive named list, the names must be identical to the shiny ids of the
-#'   respective [data_extract_ui()].
-#' @param datasets (`FilteredData`)\cr
-#'  object containing data (see `teal.slice::FilteredData`).
-#' @param merge_function (`character(1)` or `reactive`)\cr
-#'  A character string of a function that accepts the arguments
-#'  `x`, `y` and `by` to perform the merging of datasets.
-#' @param anl_name (`character(1)`)\cr
-#'  Name of the analysis dataset.
-#'
-#' @return reactive expression with output from [merge_datasets].
-#'
-#' @seealso [data_extract_srv()]
-#'
-#' @export
-data_merge_srv <- function(id = "merge_id",
-                           selector_list,
-                           datasets,
-                           merge_function = "dplyr::full_join",
-                           anl_name = "ANL") {
-  lifecycle::deprecate_stop("0.3.1", "data_merge_srv()")
-}
diff --git a/R/filter_spec.R b/R/filter_spec.R
index 4ea59354..a54afacf 100644
--- a/R/filter_spec.R
+++ b/R/filter_spec.R
@@ -258,10 +258,12 @@ filter_spec_internal <- function(vars_choices,
   checkmate::assert_string(sep)
   checkmate::assert_flag(drop_keys)
 
-  if (inherits(vars_choices, "delayed_data") ||
-    inherits(vars_selected, "delayed_data") ||
-    inherits(choices, "delayed_data") ||
-    inherits(selected, "delayed_data")) {
+  if (
+    inherits(vars_choices, "delayed_data") ||
+      inherits(vars_selected, "delayed_data") ||
+      inherits(choices, "delayed_data") ||
+      inherits(selected, "delayed_data")
+  ) {
     filter_spec_internal.delayed_data(
       vars_choices = vars_choices,
       vars_selected = vars_selected,
@@ -380,7 +382,7 @@ filter_spec_internal.default <- function(vars_choices,
     checkmate::check_numeric(vars_choices, min.len = 1, any.missing = FALSE),
     checkmate::check_logical(vars_choices, min.len = 1, any.missing = FALSE)
   )
-  stopifnot(all(!duplicated(vars_choices)))
+  checkmate::assert_vector(vars_choices, unique = TRUE)
 
   if (!is.null(vars_selected)) {
     stopifnot(vars_multiple || length(vars_selected) == 1)
@@ -389,12 +391,12 @@ filter_spec_internal.default <- function(vars_choices,
       checkmate::check_numeric(vars_selected, min.len = 1, any.missing = FALSE),
       checkmate::check_logical(vars_selected, min.len = 1, any.missing = FALSE)
     )
-    stopifnot(all(!duplicated(vars_selected)))
-    stopifnot(all(vars_selected %in% vars_choices))
+    checkmate::assert_vector(vars_selected, unique = TRUE)
+    checkmate::assert_subset(vars_selected, vars_choices)
   }
 
   if (!is.null(choices)) {
-    stopifnot(all(!duplicated(choices)))
+    checkmate::assert_vector(choices, unique = TRUE)
     split_choices <- split_by_sep(choices, sep)
     stopifnot(all(vapply(split_choices, length, integer(1)) == length(vars_selected)))
   }
@@ -406,8 +408,8 @@ filter_spec_internal.default <- function(vars_choices,
       checkmate::check_numeric(selected, min.len = 1, any.missing = FALSE),
       checkmate::check_logical(selected, min.len = 1, any.missing = FALSE)
     )
-    stopifnot(all(!duplicated(selected)))
-    stopifnot(all(selected %in% choices))
+    checkmate::assert_vector(selected, unique = TRUE)
+    checkmate::assert_subset(selected, choices)
   }
 
   res <- list(
diff --git a/R/format_data_extract.R b/R/format_data_extract.R
index e516f798..4f378e1a 100644
--- a/R/format_data_extract.R
+++ b/R/format_data_extract.R
@@ -13,12 +13,6 @@
 #'   select = select_spec(choices = c("Petal.Length", "Species"))
 #' )
 #'
-#' sample_filtered_data <- {
-#'   teal.slice::init_filtered_data(
-#'     list(iris = list(dataset = iris))
-#'   )
-#' }
-#'
 #' if (interactive()) {
 #'   shiny::shinyApp(
 #'     ui = shiny::fluidPage(
@@ -33,7 +27,7 @@
 #'     server = function(input, output, session) {
 #'       extracted_input <- data_extract_srv(
 #'         id = "extract",
-#'         datasets = sample_filtered_data,
+#'         datasets = list(iris = iris),
 #'         data_extract_spec = simple_des
 #'       )
 #'       output$formatted_extract <- shiny::renderPrint({
diff --git a/R/get_dplyr_call.R b/R/get_dplyr_call.R
index e74a37b9..a50fcd06 100644
--- a/R/get_dplyr_call.R
+++ b/R/get_dplyr_call.R
@@ -135,7 +135,7 @@ get_dplyr_call_data <- function(selector_list, join_keys = teal.data::join_keys(
 #'     dataname = "ADSL",
 #'     filters = NULL,
 #'     select = character(0),
-#'     keys = teal.data::get_cdisc_keys("ADSL"),
+#'     keys = c("STUDYID", "USUBJID"),
 #'     reshape = FALSE,
 #'     internal_id = "test1"
 #'   ))
@@ -145,7 +145,7 @@ get_dplyr_call_data <- function(selector_list, join_keys = teal.data::join_keys(
 #'     dataname = "ADSL",
 #'     filters = list(list(columns = "SEX", selected = list("F", "M"))),
 #'     select = character(0),
-#'     keys = teal.data::get_cdisc_keys("ADSL"),
+#'     keys = c("STUDYID", "USUBJID"),
 #'     reshape = FALSE,
 #'     internal_id = "test1"
 #'   ))
@@ -155,7 +155,7 @@ get_dplyr_call_data <- function(selector_list, join_keys = teal.data::join_keys(
 #'     dataname = "ADSL",
 #'     filters = list(list(columns = "SEX", selected = list("F", "M"))),
 #'     select = c("AVAL"),
-#'     keys = teal.data::get_cdisc_keys("ADSL"),
+#'     keys = c("STUDYID", "USUBJID"),
 #'     reshape = FALSE,
 #'     internal_id = "test1"
 #'   ))
@@ -168,7 +168,7 @@ get_dplyr_call_data <- function(selector_list, join_keys = teal.data::join_keys(
 #'       dataname = "ADSL",
 #'       filters = NULL,
 #'       select = c("COL_1", "COL_2"),
-#'       keys = teal.data::get_cdisc_keys("ADSL"),
+#'       keys = c("STUDYID", "USUBJID"),
 #'       reshape = FALSE,
 #'       internal_id = "test1"
 #'     ),
@@ -176,7 +176,7 @@ get_dplyr_call_data <- function(selector_list, join_keys = teal.data::join_keys(
 #'       dataname = "ADSL",
 #'       filters = NULL,
 #'       select = c("COL_2", "COL_3"),
-#'       keys = teal.data::get_cdisc_keys("ADSL"),
+#'       keys = c("STUDYID", "USUBJID"),
 #'       reshape = FALSE,
 #'       internal_id = "test2"
 #'     )
@@ -193,7 +193,7 @@ get_dplyr_call_data <- function(selector_list, join_keys = teal.data::join_keys(
 #'       selected = list(c("ALBCV", "SCREENING"), c("ALBCV", "BASELINE"))
 #'     )),
 #'     select = c("AVAL"),
-#'     keys = teal.data::get_cdisc_keys("ADLB"),
+#'     keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
 #'     reshape = TRUE,
 #'     internal_id = "test1"
 #'   ))
@@ -414,7 +414,7 @@ rename_duplicated_cols <- function(x, internal_id, selected_cols, all_cols) {
 #'     dataname = "ADSL",
 #'     filters = NULL,
 #'     select = utils::head(letters, 3),
-#'     keys = teal.data::get_cdisc_keys("ADSL"),
+#'     keys = c("STUDYID", "USUBJID"),
 #'     reshape = FALSE,
 #'     internal_id = "test1"
 #'   ),
@@ -422,7 +422,7 @@ rename_duplicated_cols <- function(x, internal_id, selected_cols, all_cols) {
 #'     dataname = "ADSL",
 #'     filters = NULL,
 #'     select = letters,
-#'     keys = teal.data::get_cdisc_keys("ADSL"),
+#'     keys = c("STUDYID", "USUBJID"),
 #'     reshape = FALSE,
 #'     internal_id = "test2"
 #'   ),
@@ -430,7 +430,7 @@ rename_duplicated_cols <- function(x, internal_id, selected_cols, all_cols) {
 #'     dataname = "ADSL",
 #'     filters = NULL,
 #'     select = utils::tail(letters, 3),
-#'     keys = teal.data::get_cdisc_keys("ADSL"),
+#'     keys = c("STUDYID", "USUBJID"),
 #'     reshape = FALSE,
 #'     internal_id = "test3"
 #'   ),
@@ -438,7 +438,7 @@ rename_duplicated_cols <- function(x, internal_id, selected_cols, all_cols) {
 #'     dataname = "ADSL",
 #'     filters = NULL,
 #'     select = c("aa", "bb"),
-#'     keys = teal.data::get_cdisc_keys("ADSL"),
+#'     keys = c("STUDYID", "USUBJID"),
 #'     reshape = FALSE,
 #'     internal_id = "test4"
 #'   )
@@ -499,7 +499,7 @@ get_rename_call <- function(selector_list = list(),
 #'       multiple = FALSE
 #'     )),
 #'     select = "AVAL",
-#'     keys = teal.data::get_cdisc_keys("ADLB"),
+#'     keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
 #'     reshape = TRUE,
 #'     internal_id = "test"
 #'   )
diff --git a/R/merge_expression_module.R b/R/merge_expression_module.R
index 9fb186ea..6696671d 100644
--- a/R/merge_expression_module.R
+++ b/R/merge_expression_module.R
@@ -139,8 +139,37 @@ merge_expression_module <- function(datasets,
                                     merge_function = "dplyr::full_join",
                                     anl_name = "ANL",
                                     id = "merge_id") {
+  UseMethod("merge_expression_module", datasets)
+}
+
+#' @rdname merge_expression_module
+#' @export
+merge_expression_module.reactive <- function(datasets,
+                                             join_keys = NULL,
+                                             data_extract,
+                                             merge_function = "dplyr::full_join",
+                                             anl_name = "ANL",
+                                             id = "merge_id") {
+  checkmate::assert_class(isolate(datasets()), "teal_data")
+  datasets_new <- convert_teal_data(datasets)
+  if (is.reactive(datasets) && inherits(isolate(datasets()), "teal_data")) {
+    join_keys <- isolate(teal.data::join_keys(datasets()))
+  }
+  merge_expression_module(datasets_new, join_keys, data_extract, merge_function, anl_name, id)
+}
+
+#' @rdname merge_expression_module
+#' @export
+merge_expression_module.list <- function(datasets,
+                                         join_keys = NULL,
+                                         data_extract,
+                                         merge_function = "dplyr::full_join",
+                                         anl_name = "ANL",
+                                         id = "merge_id") {
   logger::log_trace("merge_expression_module called with: { paste(names(datasets), collapse = ', ') } datasets.")
+  checkmate::assert_list(datasets, names = "named")
   checkmate::assert_list(data_extract, names = "named", types = c("list", "data_extract_spec", "NULL"))
+  checkmate::assert_class(join_keys, "join_keys")
   lapply(data_extract, function(x) {
     if (is.list(x) && !inherits(x, "data_extract_spec")) {
       checkmate::assert_list(x, "data_extract_spec")
@@ -311,10 +340,37 @@ merge_expression_srv <- function(id = "merge_id",
                                  join_keys,
                                  merge_function = "dplyr::full_join",
                                  anl_name = "ANL") {
+  UseMethod("merge_expression_srv", datasets)
+}
+
+#' @rdname merge_expression_srv
+#' @export
+merge_expression_srv.reactive <- function(id = "merge_id",
+                                          selector_list,
+                                          datasets,
+                                          join_keys,
+                                          merge_function = "dplyr::full_join",
+                                          anl_name = "ANL") {
+  checkmate::assert_class(isolate(datasets()), "teal_data")
+  datasets_new <- convert_teal_data(datasets)
+  if (is.reactive(datasets) && inherits(isolate(datasets()), "teal_data")) {
+    join_keys <- isolate(teal.data::join_keys(datasets()))
+  }
+  merge_expression_srv(id, selector_list, datasets_new, join_keys, merge_function, anl_name)
+}
+
+#' @rdname merge_expression_srv
+#' @export
+merge_expression_srv.list <- function(id = "merge_id",
+                                      selector_list,
+                                      datasets,
+                                      join_keys,
+                                      merge_function = "dplyr::full_join",
+                                      anl_name = "ANL") {
+  checkmate::assert_list(datasets, names = "named")
   checkmate::assert_string(anl_name)
   stopifnot(make.names(anl_name) == anl_name)
   checkmate::assert_class(selector_list, "reactive")
-  checkmate::assert_list(datasets, types = c("reactive", "data.frame"), names = "named")
   checkmate::assert_class(join_keys, "join_keys")
 
   moduleServer(
@@ -324,11 +380,6 @@ merge_expression_srv <- function(id = "merge_id",
         "merge_expression_srv initialized with: { paste(names(datasets), collapse = ', ') } datasets."
       )
 
-      # convert to list of reactives
-      datasets <- sapply(X = datasets, simplify = FALSE, FUN = function(x) {
-        if (is.reactive(x)) x else reactive(x)
-      })
-
       reactive({
         checkmate::assert_list(selector_list(), names = "named", types = "reactive")
         merge_fun_name <- if (inherits(merge_function, "reactive")) merge_function() else merge_function
diff --git a/R/resolve.R b/R/resolve.R
index afd4607e..b3986d76 100644
--- a/R/resolve.R
+++ b/R/resolve.R
@@ -11,7 +11,7 @@
 #'
 #' @examples
 #' ADSL <- teal.transform::rADSL
-#' attr(ADSL, "keys") <- teal.data::get_cdisc_keys("ADSL")
+#' attr(ADSL, "keys") <- c("STUDYID", "USUBJID")
 #' data_list <- list(ADSL = shiny::reactive(ADSL))
 #' keys <- list(ADSL = attr(ADSL, "keys"))
 #' shiny::isolate({
@@ -175,7 +175,7 @@ resolve.default <- function(x, datasets, keys) {
 #'
 #' @param x (`function`) Function that is applied on dataset.
 #' It must take only a single argument "data" and return character vector with columns / values.
-#' @param ds (`data.frame`) `TealDataset` on which the function is applied to.
+#' @param ds (`data.frame`) Dataset.
 #' @param is_value_choices (`logical`) Determines which check of the returned value will be applied.
 #'
 #' @return Character vector - result of calling function `x` on dataset `ds`.
diff --git a/R/resolve_delayed.R b/R/resolve_delayed.R
index 74f361f4..0ae03fba 100644
--- a/R/resolve_delayed.R
+++ b/R/resolve_delayed.R
@@ -14,19 +14,17 @@
 #' @examples
 #' ADSL <- teal.transform::rADSL
 #' shiny::isolate({
-#'   ds <- teal.slice::init_filtered_data(
-#'     list(ADSL = list(dataset = ADSL))
-#'   )
+#'   data_list <- list(ADSL = shiny::reactive(ADSL))
 #'
 #'   # value_choices example
 #'   v1 <- value_choices("ADSL", "SEX", "SEX")
 #'   v1
-#'   resolve_delayed(v1, ds)
+#'   resolve_delayed(v1, data_list)
 #'
 #'   # variable_choices example
 #'   v2 <- variable_choices("ADSL", c("BMRKR1", "BMRKR2"))
 #'   v2
-#'   resolve_delayed(v2, ds)
+#'   resolve_delayed(v2, data_list)
 #'
 #'   # data_extract_spec example
 #'   adsl_filter <- filter_spec(
@@ -52,9 +50,9 @@
 #'     filter = adsl_filter
 #'   )
 #'
-#'   resolve_delayed(adsl_filter, ds)
-#'   resolve_delayed(adsl_select, ds)
-#'   resolve_delayed(adsl_de, ds)
+#'   resolve_delayed(adsl_filter, datasets = data_list)
+#'   resolve_delayed(adsl_select, datasets = data_list)
+#'   resolve_delayed(adsl_de, datasets = data_list)
 #'
 #'   # nested list (arm_ref_comp)
 #'   arm_ref_comp <- list(
@@ -64,7 +62,7 @@
 #'     )
 #'   )
 #'
-#'   resolve_delayed(arm_ref_comp, ds)
+#'   resolve_delayed(arm_ref_comp, datasets = data_list)
 #' })
 resolve_delayed <- function(x, datasets, keys) {
   UseMethod("resolve_delayed", datasets)
diff --git a/R/select_spec.R b/R/select_spec.R
index f559d90f..6da0d183 100644
--- a/R/select_spec.R
+++ b/R/select_spec.R
@@ -156,7 +156,7 @@ select_spec.default <- function(choices, # nolint
   # Deal with selected
   if (length(selected) > 0) {
     stopifnot(is.atomic(selected))
-    stopifnot(all(selected %in% choices))
+    checkmate::assert_subset(selected, choices)
     stopifnot(multiple || length(selected) == 1)
     if (is.null(names(selected))) {
       names(selected) <- as.character(selected)
diff --git a/R/utils.R b/R/utils.R
index 67495a91..ca3d9189 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -156,3 +156,21 @@ compose_and_enable_validators <- function(iv, selector_list, validator_names = N
   iv$enable()
   iv
 }
+
+convert_teal_data <- function(datasets) {
+  if (is.list(datasets)) {
+    sapply(X = datasets, simplify = FALSE, FUN = function(x) {
+      if (is.reactive(x)) x else reactive(x)
+    })
+  } else if (is.reactive(datasets) && inherits(isolate(datasets()), "teal_data")) {
+    sapply(
+      isolate(teal.data::datanames(datasets())),
+      function(dataname) {
+        reactive(datasets()[[dataname]])
+      },
+      simplify = FALSE
+    )
+  } else {
+    stop("datasets must be a list of reactive dataframes or a teal_data object")
+  }
+}
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 2fc44dca..d547d427 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -46,8 +46,6 @@ reference:
       - data_extract_multiple_srv
       - data_extract_ui
       - data_extract_srv
-      - data_merge_srv
-      - data_merge_module
       - datanames_input
       - merge_expression_module
       - merge_expression_srv
diff --git a/man/data_extract_multiple_srv.Rd b/man/data_extract_multiple_srv.Rd
index 0e7e679a..353c7b01 100644
--- a/man/data_extract_multiple_srv.Rd
+++ b/man/data_extract_multiple_srv.Rd
@@ -2,12 +2,15 @@
 % Please edit documentation in R/data_extract_module.R
 \name{data_extract_multiple_srv}
 \alias{data_extract_multiple_srv}
+\alias{data_extract_multiple_srv.reactive}
 \alias{data_extract_multiple_srv.FilteredData}
 \alias{data_extract_multiple_srv.list}
 \title{Creates a named list of \code{data_extract_srv} output}
 \usage{
 data_extract_multiple_srv(data_extract, datasets, ...)
 
+\method{data_extract_multiple_srv}{reactive}(data_extract, datasets, ...)
+
 \method{data_extract_multiple_srv}{FilteredData}(data_extract, datasets, ...)
 
 \method{data_extract_multiple_srv}{list}(
@@ -32,7 +35,7 @@ The names of the elements in the list need to correspond to the \code{ids} passe
 See example for details.}
 
 \item{datasets}{(\code{FilteredData} or \code{list} of \code{reactive} or non-\code{reactive} \code{data.frame})\cr
-object containing data either in the form of \link[teal.slice:FilteredData]{teal.slice::FilteredData} or as a list of \code{data.frame}.
+object containing data either in the form of \code{FilteredData} or as a list of \code{data.frame}.
 When passing a list of non-reactive \code{data.frame} objects, they are converted to reactive \code{data.frame}s internally.
 When passing a list of reactive or non-reactive \code{data.frame} objects, the argument \code{join_keys} is required also.}
 
@@ -62,7 +65,6 @@ names are the same as \code{data_extract} input argument.
 \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#experimental}{\figure{lifecycle-experimental.svg}{options: alt='[Experimental]'}}}{\strong{[Experimental]}}
 \code{data_extract_multiple_srv} loops over the list of \code{data_extract} given and
 runs \code{data_extract_srv} for each one returning a list of reactive objects.
-This was suitable as input for (deprecated) \code{\link[=data_merge_srv]{data_merge_srv()}}.
 }
 \examples{
 library(shiny)
diff --git a/man/data_extract_srv.Rd b/man/data_extract_srv.Rd
index 75d228ee..9205291d 100644
--- a/man/data_extract_srv.Rd
+++ b/man/data_extract_srv.Rd
@@ -32,7 +32,7 @@ data_extract_srv(id, datasets, data_extract_spec, ...)
 UI function.}
 
 \item{datasets}{(\code{FilteredData} or \code{list} of \code{reactive} or non-\code{reactive} \code{data.frame})\cr
-object containing data either in the form of \link[teal.slice:FilteredData]{teal.slice::FilteredData} or as a list of \code{data.frame}.
+object containing data either in the form of \code{FilteredData} or as a list of \code{data.frame}.
 When passing a list of non-reactive \code{data.frame} objects, they are converted to reactive \code{data.frame}s internally.
 When passing a list of reactive or non-reactive \code{data.frame} objects, the argument \code{join_keys} is required also.}
 
@@ -147,13 +147,6 @@ if (interactive()) {
   shinyApp(app$ui, app$server)
 }
 
-# Using FilteredData - Note this method will be deprecated
-datasets <- teal.slice::init_filtered_data(
-  list(ADSL = list(dataset = ADSL)),
-  join_keys = teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", c("USUBJID", "STUDYID"))
-  )
-)
 
 app <- shinyApp(
   ui = fluidPage(
diff --git a/man/data_merge_module.Rd b/man/data_merge_module.Rd
deleted file mode 100644
index 2171f895..00000000
--- a/man/data_merge_module.Rd
+++ /dev/null
@@ -1,43 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/data_merge_module.R
-\name{data_merge_module}
-\alias{data_merge_module}
-\title{Data merge module}
-\usage{
-data_merge_module(
-  datasets,
-  data_extract,
-  merge_function = "dplyr::full_join",
-  anl_name = "ANL",
-  id = "merge_id"
-)
-}
-\arguments{
-\item{datasets}{(\code{FilteredData})\cr
-object containing data, see \link[teal.slice:FilteredData]{teal.slice::FilteredData} for more.}
-
-\item{data_extract}{(named \code{list} of \code{data_extract_spec})\cr}
-
-\item{merge_function}{(\code{character(1)})\cr
-A character string of a function that
-accepts the arguments \code{x}, \code{y} and \code{by} to perform the merging of datasets.}
-
-\item{anl_name}{(\code{character(1)})\cr
-Name of the analysis dataset.}
-
-\item{id}{An ID string that corresponds with the ID used to call the module's
-UI function.}
-}
-\value{
-reactive expression with output from \code{\link[=data_merge_srv]{data_merge_srv()}}.
-}
-\description{
-\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}
-}
-\details{
-This function was a convenient wrapper to combine \code{data_extract_multiple_srv()} and
-\code{data_merge_srv()} when no additional processing is required.
-}
-\seealso{
-\code{\link[=data_merge_srv]{data_merge_srv()}}
-}
diff --git a/man/data_merge_srv.Rd b/man/data_merge_srv.Rd
deleted file mode 100644
index 392660ae..00000000
--- a/man/data_merge_srv.Rd
+++ /dev/null
@@ -1,46 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/data_merge_module.R
-\name{data_merge_srv}
-\alias{data_merge_srv}
-\title{Data merge module server}
-\usage{
-data_merge_srv(
-  id = "merge_id",
-  selector_list,
-  datasets,
-  merge_function = "dplyr::full_join",
-  anl_name = "ANL"
-)
-}
-\arguments{
-\item{id}{An ID string that corresponds with the ID used to call the module's
-UI function.}
-
-\item{selector_list}{(\code{reactive})\cr
-output from \code{\link[=data_extract_multiple_srv]{data_extract_multiple_srv()}} or a reactive named list of outputs from \code{\link[=data_extract_srv]{data_extract_srv()}}.
-When using a reactive named list, the names must be identical to the shiny ids of the
-respective \code{\link[=data_extract_ui]{data_extract_ui()}}.}
-
-\item{datasets}{(\code{FilteredData})\cr
-object containing data (see \code{teal.slice::FilteredData}).}
-
-\item{merge_function}{(\code{character(1)} or \code{reactive})\cr
-A character string of a function that accepts the arguments
-\code{x}, \code{y} and \code{by} to perform the merging of datasets.}
-
-\item{anl_name}{(\code{character(1)})\cr
-Name of the analysis dataset.}
-}
-\value{
-reactive expression with output from \link{merge_datasets}.
-}
-\description{
-\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}
-}
-\details{
-When additional processing of the \code{data_extract} list input was required, \code{data_merge_srv()} could be
-combined with \code{data_extract_multiple_srv()} or \code{data_extract_srv()} to influence the \code{selector_list} input.
-}
-\seealso{
-\code{\link[=data_extract_srv]{data_extract_srv()}}
-}
diff --git a/man/format_data_extract.Rd b/man/format_data_extract.Rd
index a73100c5..fb82af7f 100644
--- a/man/format_data_extract.Rd
+++ b/man/format_data_extract.Rd
@@ -25,12 +25,6 @@ simple_des <- data_extract_spec(
   select = select_spec(choices = c("Petal.Length", "Species"))
 )
 
-sample_filtered_data <- {
-  teal.slice::init_filtered_data(
-    list(iris = list(dataset = iris))
-  )
-}
-
 if (interactive()) {
   shiny::shinyApp(
     ui = shiny::fluidPage(
@@ -45,7 +39,7 @@ if (interactive()) {
     server = function(input, output, session) {
       extracted_input <- data_extract_srv(
         id = "extract",
-        datasets = sample_filtered_data,
+        datasets = list(iris = iris),
         data_extract_spec = simple_des
       )
       output$formatted_extract <- shiny::renderPrint({
diff --git a/man/get_dplyr_call.Rd b/man/get_dplyr_call.Rd
index ce688c49..9c228814 100644
--- a/man/get_dplyr_call.Rd
+++ b/man/get_dplyr_call.Rd
@@ -40,7 +40,7 @@ teal.transform:::get_dplyr_call(
     dataname = "ADSL",
     filters = NULL,
     select = character(0),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   ))
@@ -50,7 +50,7 @@ teal.transform:::get_dplyr_call(
     dataname = "ADSL",
     filters = list(list(columns = "SEX", selected = list("F", "M"))),
     select = character(0),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   ))
@@ -60,7 +60,7 @@ teal.transform:::get_dplyr_call(
     dataname = "ADSL",
     filters = list(list(columns = "SEX", selected = list("F", "M"))),
     select = c("AVAL"),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   ))
@@ -73,7 +73,7 @@ teal.transform:::get_dplyr_call(
       dataname = "ADSL",
       filters = NULL,
       select = c("COL_1", "COL_2"),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test1"
     ),
@@ -81,7 +81,7 @@ teal.transform:::get_dplyr_call(
       dataname = "ADSL",
       filters = NULL,
       select = c("COL_2", "COL_3"),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test2"
     )
@@ -98,7 +98,7 @@ teal.transform:::get_dplyr_call(
       selected = list(c("ALBCV", "SCREENING"), c("ALBCV", "BASELINE"))
     )),
     select = c("AVAL"),
-    keys = teal.data::get_cdisc_keys("ADLB"),
+    keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
     reshape = TRUE,
     internal_id = "test1"
   ))
diff --git a/man/get_rename_call.Rd b/man/get_rename_call.Rd
index 2e0c036f..0ee5db6a 100644
--- a/man/get_rename_call.Rd
+++ b/man/get_rename_call.Rd
@@ -36,7 +36,7 @@ x <- list(
     dataname = "ADSL",
     filters = NULL,
     select = utils::head(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   ),
@@ -44,7 +44,7 @@ x <- list(
     dataname = "ADSL",
     filters = NULL,
     select = letters,
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test2"
   ),
@@ -52,7 +52,7 @@ x <- list(
     dataname = "ADSL",
     filters = NULL,
     select = utils::tail(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test3"
   ),
@@ -60,7 +60,7 @@ x <- list(
     dataname = "ADSL",
     filters = NULL,
     select = c("aa", "bb"),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test4"
   )
diff --git a/man/get_reshape_call.Rd b/man/get_reshape_call.Rd
index 3e447d66..24208368 100644
--- a/man/get_reshape_call.Rd
+++ b/man/get_reshape_call.Rd
@@ -47,7 +47,7 @@ x <- list(
       multiple = FALSE
     )),
     select = "AVAL",
-    keys = teal.data::get_cdisc_keys("ADLB"),
+    keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
     reshape = TRUE,
     internal_id = "test"
   )
diff --git a/man/merge_expression_module.Rd b/man/merge_expression_module.Rd
index ae3cec30..e46090b7 100644
--- a/man/merge_expression_module.Rd
+++ b/man/merge_expression_module.Rd
@@ -2,6 +2,8 @@
 % Please edit documentation in R/merge_expression_module.R
 \name{merge_expression_module}
 \alias{merge_expression_module}
+\alias{merge_expression_module.reactive}
+\alias{merge_expression_module.list}
 \title{Merge expression module}
 \usage{
 merge_expression_module(
@@ -12,6 +14,24 @@ merge_expression_module(
   anl_name = "ANL",
   id = "merge_id"
 )
+
+\method{merge_expression_module}{reactive}(
+  datasets,
+  join_keys = NULL,
+  data_extract,
+  merge_function = "dplyr::full_join",
+  anl_name = "ANL",
+  id = "merge_id"
+)
+
+\method{merge_expression_module}{list}(
+  datasets,
+  join_keys = NULL,
+  data_extract,
+  merge_function = "dplyr::full_join",
+  anl_name = "ANL",
+  id = "merge_id"
+)
 }
 \arguments{
 \item{datasets}{(named \code{list} of \code{reactive} or non-\code{reactive} \code{data.frame})\cr
diff --git a/man/merge_expression_srv.Rd b/man/merge_expression_srv.Rd
index b38870f9..58235caa 100644
--- a/man/merge_expression_srv.Rd
+++ b/man/merge_expression_srv.Rd
@@ -2,6 +2,8 @@
 % Please edit documentation in R/merge_expression_module.R
 \name{merge_expression_srv}
 \alias{merge_expression_srv}
+\alias{merge_expression_srv.reactive}
+\alias{merge_expression_srv.list}
 \title{Data merge module server}
 \usage{
 merge_expression_srv(
@@ -12,6 +14,24 @@ merge_expression_srv(
   merge_function = "dplyr::full_join",
   anl_name = "ANL"
 )
+
+\method{merge_expression_srv}{reactive}(
+  id = "merge_id",
+  selector_list,
+  datasets,
+  join_keys,
+  merge_function = "dplyr::full_join",
+  anl_name = "ANL"
+)
+
+\method{merge_expression_srv}{list}(
+  id = "merge_id",
+  selector_list,
+  datasets,
+  join_keys,
+  merge_function = "dplyr::full_join",
+  anl_name = "ANL"
+)
 }
 \arguments{
 \item{id}{An ID string that corresponds with the ID used to call the module's
diff --git a/man/resolve.Rd b/man/resolve.Rd
index 7a8f6c1e..c5676855 100644
--- a/man/resolve.Rd
+++ b/man/resolve.Rd
@@ -22,7 +22,7 @@ Resolved object.
 }
 \examples{
 ADSL <- teal.transform::rADSL
-attr(ADSL, "keys") <- teal.data::get_cdisc_keys("ADSL")
+attr(ADSL, "keys") <- c("STUDYID", "USUBJID")
 data_list <- list(ADSL = shiny::reactive(ADSL))
 keys <- list(ADSL = attr(ADSL, "keys"))
 shiny::isolate({
diff --git a/man/resolve_delayed.Rd b/man/resolve_delayed.Rd
index a3ea4ecb..9cfb16e8 100644
--- a/man/resolve_delayed.Rd
+++ b/man/resolve_delayed.Rd
@@ -23,19 +23,17 @@ Resolved object.
 \examples{
 ADSL <- teal.transform::rADSL
 shiny::isolate({
-  ds <- teal.slice::init_filtered_data(
-    list(ADSL = list(dataset = ADSL))
-  )
+  data_list <- list(ADSL = shiny::reactive(ADSL))
 
   # value_choices example
   v1 <- value_choices("ADSL", "SEX", "SEX")
   v1
-  resolve_delayed(v1, ds)
+  resolve_delayed(v1, data_list)
 
   # variable_choices example
   v2 <- variable_choices("ADSL", c("BMRKR1", "BMRKR2"))
   v2
-  resolve_delayed(v2, ds)
+  resolve_delayed(v2, data_list)
 
   # data_extract_spec example
   adsl_filter <- filter_spec(
@@ -61,9 +59,9 @@ shiny::isolate({
     filter = adsl_filter
   )
 
-  resolve_delayed(adsl_filter, ds)
-  resolve_delayed(adsl_select, ds)
-  resolve_delayed(adsl_de, ds)
+  resolve_delayed(adsl_filter, datasets = data_list)
+  resolve_delayed(adsl_select, datasets = data_list)
+  resolve_delayed(adsl_de, datasets = data_list)
 
   # nested list (arm_ref_comp)
   arm_ref_comp <- list(
@@ -73,6 +71,6 @@ shiny::isolate({
     )
   )
 
-  resolve_delayed(arm_ref_comp, ds)
+  resolve_delayed(arm_ref_comp, datasets = data_list)
 })
 }
diff --git a/man/resolve_delayed_expr.Rd b/man/resolve_delayed_expr.Rd
index e14043aa..45b36a90 100644
--- a/man/resolve_delayed_expr.Rd
+++ b/man/resolve_delayed_expr.Rd
@@ -10,7 +10,7 @@ resolve_delayed_expr(x, ds, is_value_choices)
 \item{x}{(\code{function}) Function that is applied on dataset.
 It must take only a single argument "data" and return character vector with columns / values.}
 
-\item{ds}{(\code{data.frame}) \code{TealDataset} on which the function is applied to.}
+\item{ds}{(\code{data.frame}) Dataset.}
 
 \item{is_value_choices}{(\code{logical}) Determines which check of the returned value will be applied.}
 }
diff --git a/man/value_choices.Rd b/man/value_choices.Rd
index 0e892169..aa48f870 100644
--- a/man/value_choices.Rd
+++ b/man/value_choices.Rd
@@ -4,8 +4,6 @@
 \alias{value_choices}
 \alias{value_choices.character}
 \alias{value_choices.data.frame}
-\alias{value_choices.TealDataset}
-\alias{value_choices.TealDatasetConnector}
 \title{Wrapper on \link{choices_labeled} to label variable values basing on other variable values}
 \usage{
 value_choices(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")
@@ -13,16 +11,11 @@ value_choices(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")
 \method{value_choices}{character}(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")
 
 \method{value_choices}{data.frame}(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")
-
-\method{value_choices}{TealDataset}(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")
-
-\method{value_choices}{TealDatasetConnector}(data, var_choices, var_label = NULL, subset = NULL, sep = " - ")
 }
 \arguments{
-\item{data}{(\code{data.frame}, \code{character}, \code{TealDataset}, \code{TealDatasetConnector})
-If \code{data.frame}, then data to extract labels from
-If \code{character}, then name of the dataset to extract data from once available
-If \code{TealDataset} or \code{TealDatasetConnector}, then raw data to extract labels from.}
+\item{data}{(\code{data.frame}, \code{character})
+If \code{data.frame}, then data to extract labels from.
+If \code{character}, then name of the dataset to extract data from once available.}
 
 \item{var_choices}{(\code{character} or \code{NULL}) vector with choices column names}
 
diff --git a/man/variable_choices.Rd b/man/variable_choices.Rd
index d6b06447..fb738701 100644
--- a/man/variable_choices.Rd
+++ b/man/variable_choices.Rd
@@ -4,8 +4,6 @@
 \alias{variable_choices}
 \alias{variable_choices.character}
 \alias{variable_choices.data.frame}
-\alias{variable_choices.TealDataset}
-\alias{variable_choices.TealDatasetConnector}
 \title{Wrapper on \link{choices_labeled} to label variables basing on existing labels in data}
 \usage{
 variable_choices(data, subset = NULL, fill = FALSE, key = NULL)
@@ -13,26 +11,11 @@ variable_choices(data, subset = NULL, fill = FALSE, key = NULL)
 \method{variable_choices}{character}(data, subset = NULL, fill = FALSE, key = NULL)
 
 \method{variable_choices}{data.frame}(data, subset = NULL, fill = TRUE, key = NULL)
-
-\method{variable_choices}{TealDataset}(
-  data,
-  subset = NULL,
-  fill = FALSE,
-  key = teal.data::get_keys(data)
-)
-
-\method{variable_choices}{TealDatasetConnector}(
-  data,
-  subset = NULL,
-  fill = FALSE,
-  key = teal.data::get_keys(data)
-)
 }
 \arguments{
-\item{data}{(\code{data.frame}, \code{character}, \code{TealDataset}, \code{TealDatasetConnector})
+\item{data}{(\code{data.frame}, \code{character})
 If \code{data.frame}, then data to extract labels from
-If \code{character}, then name of the dataset to extract data from once available
-If \code{TealDataset} or \code{TealDatasetConnector}, then raw data to extract labels from.}
+If \code{character}, then name of the dataset to extract data from once available}
 
 \item{subset}{(\code{character} or \code{function})
 If \code{character}, then a vector of column names.
@@ -59,22 +42,15 @@ ADRS <- teal.transform::rADRS
 variable_choices(ADRS)
 variable_choices(ADRS, subset = c("PARAM", "PARAMCD"))
 variable_choices(ADRS, subset = c("", "PARAM", "PARAMCD"))
-variable_choices(ADRS, subset = c("", "PARAM", "PARAMCD"), key = teal.data::get_cdisc_keys("ADRS"))
+variable_choices(
+  ADRS,
+  subset = c("", "PARAM", "PARAMCD"),
+  key = teal.data::default_cdisc_join_keys["ADRS", "ADRS"]
+)
 
 # delayed version
 variable_choices("ADRS", subset = c("USUBJID", "STUDYID"))
 
-# also works with [teal.data::TealDataset] and [teal.data::TealDatasetConnector]
-ADRS_dataset <- teal.data::dataset("ADRS", ADRS, key = teal.data::get_cdisc_keys("ADRS"))
-variable_choices(ADRS_dataset)
-
-ADRS_conn <- teal.data::dataset_connector(
-  "ADRS",
-  pull_callable = teal.data::callable_code("radrs(cached = TRUE)"),
-  key = teal.data::get_cdisc_keys("ADRS")
-)
-variable_choices(ADRS_conn)
-
 # functional subset (with delayed data) - return only factor variables
 variable_choices("ADRS", subset = function(data) {
   idx <- vapply(data, is.factor, logical(1))
diff --git a/tests/testthat/shinytest/format_data_extract/app.R b/tests/testthat/shinytest/format_data_extract/app.R
deleted file mode 100644
index c517f5da..00000000
--- a/tests/testthat/shinytest/format_data_extract/app.R
+++ /dev/null
@@ -1,24 +0,0 @@
-simple_des <- teal.transform::data_extract_spec(
-  dataname = "iris",
-  filter = teal.transform::filter_spec(vars = "Petal.Length", choices = c("1.4", "1.5")),
-  select = teal.transform::select_spec(choices = c("Petal.Length", "Species"))
-)
-
-sample_filtered_data <- {
-  teal.slice::init_filtered_data(
-    list(iris = list(dataset = iris))
-  )
-}
-
-ui <- shiny::fluidPage(
-  teal.transform::data_extract_ui(id = "des", label = "test des ui", data_extract_spec = simple_des),
-  shiny::verbatimTextOutput(outputId = "formatted_des"),
-)
-srv <- function(input, output, session) {
-  extracted_des <- teal.transform::data_extract_srv(
-    id = "des", datasets = sample_filtered_data, data_extract_spec = simple_des
-  )
-  output$formatted_des <- shiny::renderPrint(cat(teal.transform::format_data_extract(extracted_des())))
-}
-
-shiny::shinyApp(ui, srv)
diff --git a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/001.json b/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/001.json
deleted file mode 100644
index 39a24bfd..00000000
--- a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/001.json
+++ /dev/null
@@ -1,5 +0,0 @@
-{
-  "output": {
-    "formatted_des": "<Data Extract for dataset: iris>\nFilters:\n  Columns: Petal.Length Selected: 1.4\nSelected columns:\n  Petal.Length"
-  }
-}
diff --git a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/002.json b/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/002.json
deleted file mode 100644
index 51452966..00000000
--- a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/002.json
+++ /dev/null
@@ -1,5 +0,0 @@
-{
-  "output": {
-    "formatted_des": "<Data Extract for dataset: iris>\nFilters:\n  Columns:  Selected: \nSelected columns:\n  Petal.Length"
-  }
-}
diff --git a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/003.json b/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/003.json
deleted file mode 100644
index 4224e973..00000000
--- a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test-expected/003.json
+++ /dev/null
@@ -1,5 +0,0 @@
-{
-  "output": {
-    "formatted_des": "<Data Extract for dataset: iris>\nFilters:\n  Columns: Petal.Length Selected: 4.7\nSelected columns:\n  Species"
-  }
-}
diff --git a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test.R b/tests/testthat/shinytest/format_data_extract/tests/shinytest/test.R
deleted file mode 100644
index 163b83c3..00000000
--- a/tests/testthat/shinytest/format_data_extract/tests/shinytest/test.R
+++ /dev/null
@@ -1,10 +0,0 @@
-app <- ShinyDriver$new("../../")
-app$snapshotInit("test")
-
-app$snapshot(list(output = "formatted_des"))
-app$setInputs(`des-dataset_iris_singleextract-filter1-col` = character(0))
-app$snapshot(list(output = "formatted_des"))
-app$setInputs(`des-dataset_iris_singleextract-filter1-col` = "Petal.Length")
-app$setInputs(`des-dataset_iris_singleextract-filter1-vals` = "4.7")
-app$setInputs(`des-dataset_iris_singleextract-select` = "Species")
-app$snapshot(list(output = "formatted_des"))
diff --git a/tests/testthat/test-choices_selected.R b/tests/testthat/test-choices_selected.R
index 592c3e6a..e71bd18e 100644
--- a/tests/testthat/test-choices_selected.R
+++ b/tests/testthat/test-choices_selected.R
@@ -1,5 +1,5 @@
-adsl <- as.data.frame(as.list(setNames(nm = teal.data::get_cdisc_keys("ADSL"))))
-adtte <- as.data.frame(as.list(setNames(nm = teal.data::get_cdisc_keys("ADTTE"))))
+adsl <- as.data.frame(as.list(setNames(nm = c("STUDYID", "USUBJID"))))
+adtte <- as.data.frame(as.list(setNames(nm = c("STUDYID", "USUBJID", "PARAMCD"))))
 
 vc_hard <- variable_choices("ADSL", subset = c("STUDYID", "USUBJID"))
 vc_hard_exp <- structure(
@@ -37,12 +37,12 @@ testthat::test_that("delayed version of choices_selected", {
   )
 
   data_list <- list(ADSL = reactive(adsl), ADTTE = reactive(adtte))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
   res_obj <- isolate(resolve(obj, datasets = data_list, keys = key_list))
   exp_obj <- choices_selected(
-    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-    selected = variable_choices(adsl, subset = c("STUDYID"), key = teal.data::get_cdisc_keys("ADSL"))
+    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+    selected = variable_choices(adsl, subset = c("STUDYID"), key = c("STUDYID", "USUBJID"))
   )
   testthat::expect_equal(res_obj, exp_obj, check.attributes = TRUE)
 
@@ -61,14 +61,14 @@ testthat::test_that("delayed version of choices_selected", {
 })
 
 testthat::test_that("choices_selected throws error when selected is not found in choices", {
-  testthat::expect_error(choices_selected(choices = c("a"), selected = "b"), "b 'selected' but not in 'choices'")
+  testthat::expect_error(choices_selected(choices = c("a"), selected = "b"), "Must be a subset of \\{'a'\\}")
   testthat::expect_error(
     choices_selected(choices = c("a"), selected = c("a", "b")),
-    "b 'selected' but not in 'choices'"
+    "Must be a subset of \\{'a'\\}"
   )
   testthat::expect_error(
     choices_selected(choices = c("a"), selected = c("c", "b")),
-    "c, b 'selected' but not in 'choices'"
+    "Must be a subset of \\{'a'\\}"
   )
 })
 
@@ -147,12 +147,10 @@ testthat::test_that("choices_selected remove duplicates", {
   )
 })
 
-
-# With resolve_delayed
-data <- teal.data::cdisc_data(teal.data::cdisc_dataset("ADSL", adsl), teal.data::cdisc_dataset("ADTTE", adtte))
-ds <- teal.slice::init_filtered_data(data)
-
 testthat::test_that("delayed version of choices_selected - resolve_delayed", {
+  data_list <- list(ADSL = reactive(adsl), ADTTE = reactive(adtte))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
+
   # hard-coded choices and selected
   obj <- choices_selected(vc_hard, selected = vc_hard_short)
   testthat::expect_equal(
@@ -163,10 +161,10 @@ testthat::test_that("delayed version of choices_selected - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = key_list))
   exp_obj <- choices_selected(
-    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-    selected = variable_choices(adsl, subset = c("STUDYID"), key = teal.data::get_cdisc_keys("ADSL"))
+    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+    selected = variable_choices(adsl, subset = c("STUDYID"), key = c("STUDYID", "USUBJID"))
   )
   testthat::expect_equal(res_obj, exp_obj, check.attributes = TRUE)
 
@@ -180,6 +178,6 @@ testthat::test_that("delayed version of choices_selected - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = key_list))
   testthat::expect_equal(res_obj, exp_obj)
 })
diff --git a/tests/testthat/test-data_extract_datanames.R b/tests/testthat/test-data_extract_datanames.R
index 51f605a2..226f7f04 100644
--- a/tests/testthat/test-data_extract_datanames.R
+++ b/tests/testthat/test-data_extract_datanames.R
@@ -63,14 +63,16 @@ testthat::test_that(
   }
 )
 
-testthat::test_that("get_extract_datanames throws error when no data_extract_spec nor list  (of lists)
-          of data_extract_spec is passed", {
-  testthat::expect_error(get_extract_datanames(1))
-  testthat::expect_error(get_extract_datanames("A"))
-  testthat::expect_error(get_extract_datanames(TRUE))
-  testthat::expect_error(get_extract_datanames(list(des, 1)))
-  testthat::expect_error(get_extract_datanames(list(des, "A")))
-})
+testthat::test_that(
+  "get_extract_datanames throws error when no data_extract_spec nor list  (of lists) of data_extract_spec is passed",
+  {
+    testthat::expect_error(get_extract_datanames(1))
+    testthat::expect_error(get_extract_datanames("A"))
+    testthat::expect_error(get_extract_datanames(TRUE))
+    testthat::expect_error(get_extract_datanames(list(des, 1)))
+    testthat::expect_error(get_extract_datanames(list(des, "A")))
+  }
+)
 
 testthat::test_that("get_extract_datanames throws error with empty list", {
   testthat::expect_error(get_extract_datanames(list()), "length(data_extracts) > 0 is not TRUE", fixed = TRUE)
diff --git a/tests/testthat/test-data_extract_module.R b/tests/testthat/test-data_extract_module.R
index 65a85cb9..2a3bef53 100644
--- a/tests/testthat/test-data_extract_module.R
+++ b/tests/testthat/test-data_extract_module.R
@@ -31,7 +31,6 @@ testthat::test_that("Single filter", {
   # check also colummns selected
 })
 
-
 testthat::test_that("Multiple filters", {
   data_extract <- data_extract_spec(
     dataname = "ADLB",
@@ -74,7 +73,6 @@ testthat::test_that("Multiple filters", {
   # number of column inputs
 })
 
-
 testthat::test_that("Multiple datasets", {
   data_extract_adtte <- data_extract_spec(
     dataname = "ADTTE",
@@ -139,37 +137,3 @@ testthat::test_that("Multiple datasets", {
     )
   )
 })
-
-testthat::test_that("get_initial_filters_values returns empty strings if vars_selected is NULL", {
-  filtered_data <- teal.slice::init_filtered_data(list(iris = list(dataset = utils::head(iris))))
-  filter <- filter_spec(vars = "test")
-  filter$vars_selected <- NULL
-  testthat::expect_equal(
-    get_initial_filter_values(filter = filter, datasets = filtered_data),
-    list(choices = character(0), selected = character(0))
-  )
-})
-
-testthat::test_that("get_initial_filters_values returns all column values and the selected option if choices is NULL", { # nolint
-  data_list <- list(iris = reactive(utils::head(iris)))
-
-  filter <- filter_spec(vars = colnames(iris)[1])
-  filter$choices <- NULL
-  filter$dataname <- "iris"
-  filter$selected <- "test"
-  testthat::expect_equal(
-    isolate(get_initial_filter_values(filter = filter, datasets = data_list)),
-    list(choices = value_choices(utils::head(iris), colnames(iris)[1]), selected = "test")
-  )
-})
-
-testthat::test_that("get_initial_filters_values returns the selected and choices if they are not null", {
-  filtered_data <- teal.slice::init_filtered_data(list(iris = list(dataset = utils::head(iris))))
-  filter <- filter_spec(vars = colnames(iris)[length(colnames(iris))])
-  filter$choices <- "setosa"
-  filter$selected <- "setosa"
-  testthat::expect_equal(
-    isolate(get_initial_filter_values(filter = filter, datasets = filtered_data)),
-    list(choices = "setosa", selected = "setosa")
-  )
-})
diff --git a/tests/testthat/test-data_extract_multiple_srv.R b/tests/testthat/test-data_extract_multiple_srv.R
index 494f02d7..6db3efc1 100644
--- a/tests/testthat/test-data_extract_multiple_srv.R
+++ b/tests/testthat/test-data_extract_multiple_srv.R
@@ -1,39 +1,32 @@
-datasets <- teal.slice::init_filtered_data(
-  list(iris = list(dataset = iris))
-)
-
-data_list <- sapply(X = datasets$datanames(), simplify = FALSE, FUN = function(x) {
-  shiny::reactive(datasets$get_data(dataname = x, filtered = FALSE))
-})
-
-nr_data_list <- sapply(X = datasets$datanames(), simplify = FALSE, FUN = function(x) {
-  shiny::isolate(datasets$get_data(dataname = x, filtered = FALSE))
-})
+ADSL <- teal.transform::rADSL # nolint
+ADLB <- teal.transform::rADLB # nolint
+ADTTE <- teal.transform::rADTTE # nolint
 
-key_list <- datasets$get_join_keys()
+data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE), ADLB = reactive(ADLB))
+join_keys <- teal.data::default_cdisc_join_keys[c("ADSL", "ADTTE", "ADLB")]
 
 testthat::test_that("data_extract_multiple_srv accepts a named list of `data_extract_spec`", {
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
-    expr = testthat::expect_error(
+    expr = testthat::expect_no_error(
       data_extract_multiple_srv(
         data_extract = list(test = data_extract_spec(dataname = "iris")),
         datasets = data_list,
-        join_keys = key_list
-      ),
-      NA
+        join_keys = teal.data::join_keys()
+      )
     )
   )
 })
 
 testthat::test_that("data_extract_multiple_srv returns a named reactive list with reactives", {
+  data_list <- list(iris = reactive(iris))
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
     expr = {
       selector_list <- data_extract_multiple_srv(
         list(test = data_extract_spec(dataname = "iris")),
         datasets = data_list,
-        join_keys = key_list
+        join_keys = teal.data::join_keys()
       )
       testthat::expect_equal(names(isolate(selector_list())), "test")
       testthat::expect_true(inherits(selector_list, "reactive"))
@@ -45,7 +38,7 @@ testthat::test_that("data_extract_multiple_srv returns a named reactive list wit
 testthat::test_that("data_extract_multiple_srv accepts an empty list", {
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
-    expr = testthat::expect_error(data_extract_multiple_srv(list(), datasets = data_list, join_keys = key_list), NA)
+    expr = testthat::expect_no_error(data_extract_multiple_srv(list(), datasets = data_list, join_keys = join_keys))
   )
 })
 
@@ -53,52 +46,54 @@ testthat::test_that("data_extract_multiple_srv returns an empty list if passed a
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
     expr = {
-      selector_list <- data_extract_multiple_srv(list(), datasets = data_list, join_keys = key_list)
+      selector_list <- data_extract_multiple_srv(list(), datasets = data_list, join_keys = join_keys)
       testthat::expect_equal(isolate(selector_list()), list())
     }
   )
 })
 
 testthat::test_that("data_extract_multiple_srv prunes `NULL` from the passed list", {
+  data_list <- list(iris = reactive(iris))
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
     expr = testthat::expect_equal(
       length(data_extract_multiple_srv(
         list(test = data_extract_spec(dataname = "iris"), test2 = NULL),
-        datasets = data_list,
-        join_keys = key_list
+        datasets = data_list
       )),
       1
     )
   )
 })
 
-testthat::test_that("data_extract_multiple_srv accepts datasets as FilteredData or list of (reactive) data.frame", {
-  shiny::withReactiveDomain(
-    domain = shiny::MockShinySession$new(),
-    expr = testthat::expect_error(
-      data_extract_multiple_srv(data_extract = list(test = NULL), datasets = datasets),
-      regexp = NA
-    )
+testthat::test_that("data_extract_multiple_srv accepts datasets as FilteredData", {
+  mock_datasets <- structure(
+    list(
+      datanames = function() names(data_list),
+      get_data = function(dataname, ...) data_list[[dataname]](),
+      get_join_keys = function(dataname, ...) join_keys
+    ),
+    class = "FilteredData"
   )
-
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
-    expr = testthat::expect_error(
-      data_extract_multiple_srv(data_extract = list(test = NULL), datasets = nr_data_list, join_keys = key_list),
-      regexp = NA
+    expr = testthat::expect_no_error(
+      data_extract_multiple_srv(data_extract = list(test = NULL), datasets = mock_datasets)
     )
   )
+})
 
+testthat::test_that("data_extract_multiple_srv accepts datasets list of reactive data.frame", {
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
-    expr = testthat::expect_error(
-      data_extract_multiple_srv(data_extract = list(test = NULL), datasets = data_list, join_keys = key_list),
-      regexp = NA
+    expr = testthat::expect_no_error(
+      data_extract_multiple_srv(data_extract = list(test = NULL), datasets = data_list, join_keys = join_keys)
     )
   )
+})
 
-  mixed_data_list <- list(IRIS = reactive(iris), IRIS2 = iris)
+testthat::test_that("data_extract_multiple_srv accepts datasets as list of data.frame", {
+  mixed_data_list <- list(IRIS = iris, IRIS2 = iris)
   mixed_join_keys_list <- teal.data::join_keys(
     teal.data::join_key("IRIS", "IRIS", "id"),
     teal.data::join_key("IRIS2", "IRIS2", "id"),
@@ -107,13 +102,12 @@ testthat::test_that("data_extract_multiple_srv accepts datasets as FilteredData
 
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
-    expr = testthat::expect_error(
+    expr = testthat::expect_no_error(
       data_extract_multiple_srv(
         data_extract = list(test = NULL),
         datasets = mixed_data_list,
         join_keys = mixed_join_keys_list
-      ),
-      NA
+      )
     )
   )
 })
@@ -135,7 +129,7 @@ testthat::test_that("data_extract_multiple_srv throws if data_extract is not a n
   shiny::withReactiveDomain(
     domain = shiny::MockShinySession$new(),
     expr = testthat::expect_error(
-      data_extract_multiple_srv(list(1), datasets = teal.slice::init_filtered_data(list(iris = list(dataset = iris)))),
+      data_extract_multiple_srv(list(1), datasets = data_list),
       regexp = "Assertion on 'data_extract' failed: Must have names"
     )
   )
diff --git a/tests/testthat/test-data_extract_spec.R b/tests/testthat/test-data_extract_spec.R
index 4a735fb0..2903081f 100644
--- a/tests/testthat/test-data_extract_spec.R
+++ b/tests/testthat/test-data_extract_spec.R
@@ -1,9 +1,5 @@
-testthat::test_that("data_extract_spec argument checking", {
-  expect_error(
-    data_extract_spec("toyDataset", select = c("A", "B")),
-    "select, \"select_spec\"",
-    fixed = TRUE
-  )
+testthat::test_that("data_extract_spec throws when select is not select_spec or NULL", {
+  expect_error(data_extract_spec("toyDataset", select = c("A", "B")))
 })
 
 testthat::test_that("data_extract_spec works with valid input", {
@@ -111,7 +107,7 @@ testthat::test_that("delayed data_extract_spec works", {
     BMRKR2 = sample(c("L", "M", "H"), 10, replace = TRUE),
     stringsAsFactors = FALSE
   )
-  attr(ADSL, "keys") <- teal.data::get_cdisc_keys("ADSL") # nolint
+  attr(ADSL, "keys") <- c("STUDYID", "USUBJID") # nolint
 
   filter_normal <- filter_spec(
     vars = variable_choices(ADSL, "SEX"),
@@ -187,7 +183,7 @@ testthat::test_that("delayed data_extract_spec works", {
   testthat::expect_equal(names(expected_spec), names(mix3))
 
   data_list <- list(ADSL = reactive(ADSL))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"))
 
   isolate({
     testthat::expect_identical(expected_spec, resolve(delayed_spec, data_list, key_list))
@@ -206,7 +202,7 @@ testthat::test_that("delayed data_extract_spec works", {
 ADSL <- teal.transform::rADSL # nolint
 ADTTE <- teal.transform::rADTTE # nolint
 data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
-key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
+key_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
 vc_hard <- variable_choices("ADSL", subset = c("STUDYID", "USUBJID"))
 vc_hard_exp <- structure(
@@ -248,11 +244,11 @@ testthat::test_that("delayed version of data_extract_spec", {
   res_obj <- isolate(resolve(obj, datasets = data_list, keys = key_list))
   exp_obj <- data_extract_spec(
     "ADSL",
-    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-      selected = variable_choices(ADSL, "STUDYID", key = teal.data::get_cdisc_keys("ADSL"))
+    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+      selected = variable_choices(ADSL, "STUDYID", key = c("STUDYID", "USUBJID"))
     ),
     filter = filter_spec(
-      vars = variable_choices(ADSL, subset = "ARMCD", key = teal.data::get_cdisc_keys("ADSL")),
+      vars = variable_choices(ADSL, subset = "ARMCD", key = c("STUDYID", "USUBJID")),
       choices = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B")),
       selected = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = "ARM A"),
       multiple = FALSE
@@ -288,11 +284,11 @@ testthat::test_that("delayed version of data_extract_spec", {
   res_obj <- isolate(resolve(obj, datasets = data_list, keys = key_list))
   exp_obj <- data_extract_spec(
     "ADSL",
-    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-      selected = variable_choices(ADSL, "STUDYID", key = teal.data::get_cdisc_keys("ADSL"))
+    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+      selected = variable_choices(ADSL, "STUDYID", key = c("STUDYID", "USUBJID"))
     ),
     filter = filter_spec(
-      vars = variable_choices(ADSL, subset = "ARMCD", key = teal.data::get_cdisc_keys("ADSL")),
+      vars = variable_choices(ADSL, subset = "ARMCD", key = c("STUDYID", "USUBJID")),
       choices = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B")),
       selected = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = "ARM A"),
       multiple = FALSE
@@ -339,7 +335,7 @@ testthat::test_that("delayed data_extract_spec works - resolve_delayed", {
     BMRKR2 = sample(c("L", "M", "H"), 10, replace = TRUE),
     stringsAsFactors = FALSE
   )
-  attr(ADSL, "keys") <- teal.data::get_cdisc_keys("ADSL") # nolint
+  attr(ADSL, "keys") <- c("STUDYID", "USUBJID") # nolint
 
   filter_normal <- filter_spec(
     vars = variable_choices(ADSL, "SEX"),
@@ -416,14 +412,12 @@ testthat::test_that("delayed data_extract_spec works - resolve_delayed", {
 
 
   isolate({
-    ds <- teal.slice::init_filtered_data(
-      list(ADSL = list(dataset = ADSL))
-    )
-    testthat::expect_identical(expected_spec, resolve_delayed(delayed_spec, ds))
-    testthat::expect_identical(expected_spec, resolve_delayed(mix1, ds))
-    testthat::expect_identical(expected_spec, resolve_delayed(mix2, ds))
+    data_list <- list(ADSL = reactive(ADSL))
+    testthat::expect_identical(expected_spec, resolve_delayed(delayed_spec, data_list))
+    testthat::expect_identical(expected_spec, resolve_delayed(mix1, data_list))
+    testthat::expect_identical(expected_spec, resolve_delayed(mix2, data_list))
 
-    mix3_res <- resolve_delayed(mix3, ds)
+    mix3_res <- resolve_delayed(mix3, data_list)
   })
 
   testthat::expect_identical(expected_spec$filter[[1]], mix3_res$filter[[1]])
@@ -433,14 +427,10 @@ testthat::test_that("delayed data_extract_spec works - resolve_delayed", {
   testthat::expect_identical(expected_spec, mix3_res)
 })
 
-data <- teal.data::cdisc_data(
-  teal.data::cdisc_dataset("ADSL", ADSL),
-  teal.data::cdisc_dataset("ADTTE", ADTTE)
-)
-
-ds <- teal.slice::init_filtered_data(data)
 
 testthat::test_that("delayed version of data_extract_spec - resolve_delayed", {
+  data_list <- list(ADSL = reactive(ADSL))
+  keys_list <- list(ADSL = c("STUDYID", "USUBJID"))
   # hard-coded subset
   obj <- data_extract_spec(
     "ADSL",
@@ -453,14 +443,14 @@ testthat::test_that("delayed version of data_extract_spec - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = keys_list))
   exp_obj <- data_extract_spec(
     "ADSL",
-    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-      selected = variable_choices(ADSL, "STUDYID", key = teal.data::get_cdisc_keys("ADSL"))
+    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+      selected = variable_choices(ADSL, "STUDYID", key = c("STUDYID", "USUBJID"))
     ),
     filter = filter_spec(
-      vars = variable_choices(ADSL, subset = "ARMCD", key = teal.data::get_cdisc_keys("ADSL")),
+      vars = variable_choices(ADSL, subset = "ARMCD", key = c("STUDYID", "USUBJID")),
       choices = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B")),
       selected = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = "ARM A"),
       multiple = FALSE
@@ -494,14 +484,14 @@ testthat::test_that("delayed version of data_extract_spec - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = keys_list))
   exp_obj <- data_extract_spec(
     "ADSL",
-    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-      selected = variable_choices(ADSL, "STUDYID", key = teal.data::get_cdisc_keys("ADSL"))
+    select = select_spec(variable_choices(ADSL, c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+      selected = variable_choices(ADSL, "STUDYID", key = c("STUDYID", "USUBJID"))
     ),
     filter = filter_spec(
-      vars = variable_choices(ADSL, subset = "ARMCD", key = teal.data::get_cdisc_keys("ADSL")),
+      vars = variable_choices(ADSL, subset = "ARMCD", key = c("STUDYID", "USUBJID")),
       choices = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B")),
       selected = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = "ARM A"),
       multiple = FALSE
diff --git a/tests/testthat/test-data_extract_srv.R b/tests/testthat/test-data_extract_srv.R
index cb2336cb..0ef403f5 100644
--- a/tests/testthat/test-data_extract_srv.R
+++ b/tests/testthat/test-data_extract_srv.R
@@ -1,31 +1,15 @@
-adsl_df <- as.data.frame(as.list(stats::setNames(nm = teal.data::get_cdisc_keys("ADSL"))))
-adlb_df <- as.data.frame(as.list(stats::setNames(nm = teal.data::get_cdisc_keys("ADLB"))))
+ADSL <- teal.transform::rADSL # nolint
+ADLB <- teal.transform::rADLB # nolint
+ADTTE <- teal.transform::rADTTE # nolint
 
-adsl <- teal.data::cdisc_dataset("ADSL", adsl_df)
-adlb <- teal.data::cdisc_dataset("ADLB", adlb_df)
-
-datasets <- teal.slice::init_filtered_data(
-  list(ADSL = list(dataset = adsl_df)),
-  join_keys = teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
-  )
-)
-
-data_list <- sapply(X = datasets$datanames(), simplify = FALSE, FUN = function(x) {
-  reactive(datasets$get_data(dataname = x, filtered = FALSE))
-})
-
-nr_data_list <- sapply(X = datasets$datanames(), simplify = FALSE, FUN = function(x) {
-  datasets$get_data(dataname = x, filtered = FALSE)
-})
-
-join_keys_list <- datasets$get_join_keys()
+data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE), ADLB = reactive(ADLB))
+join_keys <- teal.data::default_cdisc_join_keys[c("ADSL", "ADTTE", "ADLB")]
 
 adsl_extract <- data_extract_spec(
   dataname = "ADSL",
   select = select_spec(
     label = "Select variable:",
-    choices = variable_choices(adsl, teal.data::get_cdisc_keys("ADSL")),
+    choices = variable_choices("ADSL", c("STUDYID", "USUBJID")),
     selected = "STUDYID",
     multiple = TRUE,
     fixed = FALSE
@@ -44,58 +28,64 @@ adlb_extract <- data_extract_spec(
 )
 
 testthat::test_that(
-  desc = "data_extract_srv accepts a FilteredData object or a list of (reactive) data frames to datasets",
+  desc = "data_extract_srv datasets accepts list of (reactive) data frames",
   code = {
     shiny::withReactiveDomain(
       domain = shiny::MockShinySession$new(),
-      expr = testthat::expect_error(
-        data_extract_srv(id = "x", data_extract_spec = adsl_extract, datasets = datasets),
-        NA
+      expr = testthat::expect_no_error(
+        data_extract_srv(id = "x", data_extract_spec = adsl_extract, datasets = data_list, join_keys = join_keys)
       )
     )
+  }
+)
 
-    shiny::withReactiveDomain(
-      domain = shiny::MockShinySession$new(),
-      expr = testthat::expect_error(
-        data_extract_srv(id = "x", data_extract_spec = adsl_extract, datasets = data_list, join_keys = join_keys_list),
-        NA
-      )
+testthat::test_that("data_extract_srv datasets accepts a FilteredData", {
+  mock_datasets <- structure(
+    list(
+      datanames = function() names(data_list),
+      get_data = function(dataname, ...) data_list[[dataname]](),
+      get_join_keys = function(dataname, ...) join_keys
+    ),
+    class = "FilteredData"
+  )
+  shiny::withReactiveDomain(
+    domain = shiny::MockShinySession$new(),
+    expr = testthat::expect_no_error(
+      data_extract_srv(id = "x", data_extract_spec = adsl_extract, datasets = mock_datasets)
     )
+  )
+})
 
-    shiny::withReactiveDomain(
-      domain = shiny::MockShinySession$new(),
-      expr = testthat::expect_error(
-        data_extract_srv(
-          id = "x",
-          data_extract_spec = adsl_extract,
-          datasets = nr_data_list,
-          join_keys = join_keys_list
-        ),
-        NA
+testthat::test_that("data_extract_srv datasets accepts a list of data frames", {
+  data_list <- list(ADSL = ADSL, ADTTE = ADTTE, ADLB = ADLB)
+  shiny::withReactiveDomain(
+    domain = shiny::MockShinySession$new(),
+    expr = testthat::expect_no_error(
+      data_extract_srv(
+        id = "x",
+        data_extract_spec = adsl_extract,
+        datasets = data_list,
+        join_keys = join_keys
       )
     )
+  )
+})
 
-    mixed_data_list <- list(ADSL = reactive(datasets$get_data(dataname = "ADSL", filtered = FALSE)), ADLB = adsl_df)
-    mixed_join_keys_list <- teal.data::join_keys(
-      teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-      teal.data::join_key("ADLB", "ADLB", teal.data::get_cdisc_keys("ADLB")),
-      teal.data::join_key("ADSL", "ADLB", teal.data::get_cdisc_keys("ADSL"))
-    )
+testthat::test_that("data_extract_srv datasets accepts a mixed list of reactive and not reactive data frames", {
+  mixed_data_list <- list(ADSL = reactive(ADSL), ADLB = ADLB)
 
-    shiny::withReactiveDomain(
-      domain = shiny::MockShinySession$new(),
-      expr = testthat::expect_error(
-        data_extract_srv(
-          id = "x",
-          data_extract_spec = adsl_extract,
-          datasets = mixed_data_list,
-          join_keys = mixed_join_keys_list
-        ),
-        NA
+  shiny::withReactiveDomain(
+    domain = shiny::MockShinySession$new(),
+    expr = testthat::expect_no_error(
+      data_extract_srv(
+        id = "x",
+        data_extract_spec = adsl_extract,
+        datasets = mixed_data_list,
+        join_keys = join_keys
       )
     )
-  }
-)
+  )
+})
 
 testthat::test_that(
   desc = "data_extract_srv works with join_keys = NULL (default)",
@@ -126,7 +116,7 @@ testthat::test_that(
 testthat::test_that("data_extract_srv returns a list of elements", {
   shiny::testServer(
     data_extract_srv,
-    args = list(id = "x", data_extract_spec = adsl_extract, datasets = nr_data_list, join_keys = join_keys_list),
+    args = list(id = "x", data_extract_spec = adsl_extract, datasets = data_list, join_keys = join_keys),
     expr = {
       testthat::expect_is(session$returned(), "list")
       testthat::expect_setequal(
@@ -137,11 +127,11 @@ testthat::test_that("data_extract_srv returns a list of elements", {
   )
 })
 
-testthat::test_that("data_extract_srv throws error with missing arguments", {
+testthat::test_that("data_extract_srv throws error when data_extract_spec is missing", {
   testthat::expect_error(
     shiny::testServer(
       data_extract_srv,
-      args = list(id = "x", datasets = nr_data_list, join_keys = join_keys_list),
+      args = list(id = "x", datasets = data_list, join_keys = join_keys),
       expr = NULL
     ),
     "argument \"data_extract_spec\" is missing, with no default"
@@ -157,11 +147,11 @@ testthat::test_that("data_extract_srv throws error with missing arguments", {
   )
 })
 
-testthat::test_that("data_extract_srv throws error with wrong argument input type", {
+testthat::test_that("data_extract_srv throws when data_extract_spec don't get data_extract_spec object", {
   testthat::expect_error(
     shiny::testServer(
       data_extract_srv,
-      args = list(id = "x", data_extract_spec = c("data_extract"), datasets = nr_data_list, join_keys = join_keys_list),
+      args = list(id = "x", data_extract_spec = c("data_extract"), datasets = data_list, join_keys = join_keys),
       expr = NULL
     ),
     regexp = "has class 'character'"
@@ -170,16 +160,7 @@ testthat::test_that("data_extract_srv throws error with wrong argument input typ
   testthat::expect_error(
     shiny::testServer(
       data_extract_srv,
-      args = list(id = "x", data_extract_spec = TRUE, datasets = nr_data_list, join_keys = join_keys_list),
-      expr = NULL
-    ),
-    regexp = "has class 'logical'"
-  )
-
-  testthat::expect_error(
-    shiny::testServer(
-      data_extract_srv,
-      args = list(id = "x", data_extract_spec = adsl_extract, datasets = adsl, join_keys = join_keys_list),
+      args = list(id = "x", data_extract_spec = adsl_extract, datasets = ADSL, join_keys = join_keys),
       expr = NULL
     ),
     regexp = "Assertion on 'datasets' failed:"
@@ -191,8 +172,8 @@ testthat::test_that("data_extract_srv throws error with wrong argument input typ
       args = list(
         id = "adsl_extract",
         data_extract_spec = adsl_extract,
-        datasets = nr_data_list,
-        join_keys = join_keys_list,
+        datasets = data_list,
+        join_keys = join_keys,
         select_validation_rule = "string"
       ),
       expr = NULL
@@ -206,8 +187,8 @@ testthat::test_that("data_extract_srv throws error with wrong argument input typ
       args = list(
         id = "adsl_extract",
         data_extract_spec = adsl_extract,
-        datasets = nr_data_list,
-        join_keys = join_keys_list,
+        datasets = data_list,
+        join_keys = join_keys,
         filter_validation_rule = "string"
       ),
       expr = NULL
@@ -221,8 +202,8 @@ testthat::test_that("data_extract_srv throws error with wrong argument input typ
       args = list(
         id = "adsl_extract",
         data_extract_spec = adsl_extract,
-        datasets = nr_data_list,
-        join_keys = join_keys_list,
+        datasets = data_list,
+        join_keys = join_keys,
         dataset_validation_rule = "string"
       ),
       expr = NULL
@@ -236,8 +217,8 @@ testthat::test_that("data_extract_srv throws error with wrong argument input typ
       args = list(
         id = "adsl_extract",
         data_extract_spec = adsl_extract,
-        datasets = nr_data_list,
-        join_keys = join_keys_list,
+        datasets = data_list,
+        join_keys = join_keys,
         select_validation_rule = TRUE
       ),
       expr = NULL
@@ -251,8 +232,8 @@ testthat::test_that("data_extract_srv throws error with wrong argument input typ
       args = list(
         id = "adsl_extract",
         data_extract_spec = adsl_extract,
-        datasets = nr_data_list,
-        join_keys = join_keys_list,
+        datasets = data_list,
+        join_keys = join_keys,
         select_validation_rule = 1
       ),
       expr = NULL
@@ -267,8 +248,8 @@ testthat::test_that("data_extract_srv uses the current session id when id is mis
     args = list(
       id = "adsl_extract",
       data_extract_spec = adsl_extract,
-      datasets = nr_data_list,
-      join_keys = join_keys_list
+      datasets = data_list,
+      join_keys = join_keys
     ),
     expr = {
       testthat::expect_is(session$returned(), "list")
@@ -280,13 +261,12 @@ testthat::test_that("data_extract_srv uses the current session id when id is mis
   )
 })
 
-
 testthat::test_that("data_extract_srv returns select ordered according to selection", {
   extract_ordered <- data_extract_spec(
     dataname = "ADSL",
     select = select_spec(
       label = "Select variable:",
-      choices = variable_choices(adsl, teal.data::get_cdisc_keys("ADSL")),
+      choices = variable_choices(ADSL, c("STUDYID", "USUBJID")),
       selected = "STUDYID",
       ordered = TRUE
     )
@@ -294,7 +274,7 @@ testthat::test_that("data_extract_srv returns select ordered according to select
 
   shiny::testServer(
     data_extract_srv,
-    args = list(id = "x", data_extract_spec = extract_ordered, datasets = datasets),
+    args = list(id = "x", data_extract_spec = extract_ordered, datasets = data_list),
     expr = {
       session$setInputs(`dataset_ADSL_singleextract-select` = c("b", "c"))
       testthat::expect_identical(filter_and_select_reactive()$select, c("b", "c"))
@@ -313,7 +293,7 @@ testthat::test_that("data_extract_srv returns select ordered according to choice
     dataname = "ADSL",
     select = select_spec(
       label = "Select variable:",
-      choices = variable_choices(adsl, teal.data::get_cdisc_keys("ADSL")),
+      choices = variable_choices(ADSL, c("STUDYID", "USUBJID")),
       selected = "STUDYID",
       ordered = FALSE
     )
@@ -321,7 +301,7 @@ testthat::test_that("data_extract_srv returns select ordered according to choice
 
   shiny::testServer(
     data_extract_srv,
-    args = list(id = "x", data_extract_spec = extract_unordered, datasets = datasets),
+    args = list(id = "x", data_extract_spec = extract_unordered, datasets = data_list),
     expr = {
       session$setInputs(`dataset_ADSL_singleextract-select` = c("b", "c"))
       testthat::expect_identical(filter_and_select_reactive()$select, c("b", "c"))
@@ -335,22 +315,12 @@ testthat::test_that("data_extract_srv returns select ordered according to choice
   )
 })
 
-datasets <- teal.slice::init_filtered_data(
-  list(
-    ADSL = list(dataset = adsl_df),
-    ADLB = list(dataset = adsl_df)
-  ),
-  join_keys = teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADLB", "ADLB", teal.data::get_cdisc_keys("ADLB"))
-  )
-)
 testthat::test_that("data_extract_srv with a list of multiple data_extract_spec", {
   extract_list <- list(adsl_extract = adsl_extract, adlb_extract = adlb_extract)
 
   shiny::testServer(
     data_extract_srv,
-    args = list(id = "x", data_extract_spec = extract_list, datasets = datasets),
+    args = list(id = "x", data_extract_spec = extract_list, datasets = data_list),
     expr = {
       session$setInputs(`dataset` = "ADLB")
       testthat::expect_identical(input$dataset, "ADLB")
@@ -363,36 +333,25 @@ testthat::test_that("data_extract_srv with a list of multiple data_extract_spec"
   )
 })
 
-ADSL_val <- data.frame( # nolint
-  STUDYID = "A",
-  USUBJID = LETTERS[1:10],
-  SEX = rep(c("F", "M"), 5),
-  AGE = rpois(10, 30),
-  BMRKR1 = rlnorm(10)
-)
-
-adsl_extract_val <- data_extract_spec(
-  dataname = "ADSL",
-  filter = filter_spec(vars = "SEX", choices = c("F", "M"), selected = "F"),
-  select = select_spec(
-    label = "Select variable:",
-    choices = variable_choices(ADSL_val, c("AGE", "BMRKR1")),
-    selected = "AGE",
-    multiple = TRUE,
-    fixed = FALSE
-  )
-)
-
-data_list_val <- list(ADSL = reactive(ADSL_val))
-join_keys_val <- teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
 
 testthat::test_that("select validation", {
+  adsl_extract <- data_extract_spec(
+    dataname = "ADSL",
+    filter = filter_spec(vars = "SEX", choices = c("F", "M"), selected = "F"),
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(ADSL, c("AGE", "BMRKR1")),
+      selected = "AGE",
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
   server <- function(input, output, session) {
     adsl_reactive_input <- data_extract_srv(
       id = "adsl_var",
-      datasets = data_list_val,
-      data_extract_spec = adsl_extract_val,
-      join_keys = join_keys_val,
+      datasets = data_list,
+      data_extract_spec = adsl_extract,
+      join_keys = join_keys,
       select_validation_rule = shinyvalidate::sv_required("Please select a variable.")
     )
 
@@ -423,7 +382,7 @@ testthat::test_that("select validation", {
 })
 
 testthat::test_that("validation only runs on currently selected dataset's data extract spec", {
-  iris_extract_val <- data_extract_spec(
+  iris_extract <- data_extract_spec(
     dataname = "IRIS",
     select = select_spec(
       label = "Select variable:",
@@ -434,13 +393,12 @@ testthat::test_that("validation only runs on currently selected dataset's data e
     )
   )
 
-
   server <- function(input, output, session) {
     adsl_reactive_input <- data_extract_srv(
       id = "adsl_var",
-      datasets = data_list_val,
-      data_extract_spec = list(adsl_extract_val, iris_extract_val),
-      join_keys = join_keys_val,
+      datasets = data_list,
+      data_extract_spec = list(iris_extract, iris_extract),
+      join_keys = join_keys,
       select_validation_rule = shinyvalidate::sv_required("Please select a variable.")
     )
 
@@ -470,12 +428,23 @@ testthat::test_that("validation only runs on currently selected dataset's data e
 })
 
 testthat::test_that("filter validation", {
+  adsl_extract <- data_extract_spec(
+    dataname = "ADSL",
+    filter = filter_spec(vars = "SEX", choices = c("F", "M"), selected = "F"),
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(ADSL, c("AGE", "BMRKR1")),
+      selected = "AGE",
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
   server <- function(input, output, session) {
     adsl_reactive_input <- data_extract_srv(
       id = "adsl_var",
-      datasets = data_list_val,
-      data_extract_spec = adsl_extract_val,
-      join_keys = join_keys_val,
+      datasets = data_list,
+      data_extract_spec = adsl_extract,
+      join_keys = join_keys,
       filter_validation_rule = shinyvalidate::sv_required("Please select a variable.")
     )
 
@@ -507,12 +476,23 @@ testthat::test_that("filter validation", {
 
 
 testthat::test_that("select validation accepts function as validator", {
+  adsl_extract <- data_extract_spec(
+    dataname = "ADSL",
+    filter = filter_spec(vars = "SEX", choices = c("F", "M"), selected = "F"),
+    select = select_spec(
+      label = "Select variable:",
+      choices = variable_choices(ADSL, c("AGE", "BMRKR1")),
+      selected = "AGE",
+      multiple = TRUE,
+      fixed = FALSE
+    )
+  )
   server <- function(input, output, session) {
     adsl_reactive_input <- data_extract_srv(
       id = "adsl_var",
-      datasets = data_list_val,
-      data_extract_spec = adsl_extract_val,
-      join_keys = join_keys_val,
+      datasets = data_list,
+      data_extract_spec = adsl_extract,
+      join_keys = join_keys,
       select_validation_rule = ~ if (nchar(.) == 0) "error"
     )
 
diff --git a/tests/testthat/test-delayed_data_extract.R b/tests/testthat/test-delayed_data_extract.R
index 3f2af641..d698ed8b 100644
--- a/tests/testthat/test-delayed_data_extract.R
+++ b/tests/testthat/test-delayed_data_extract.R
@@ -2,12 +2,12 @@
 # the objects responsible for loading, pulling and filtering the data
 ADSL <- teal.transform::rADSL # nolint
 ADTTE <- teal.transform::rADTTE # nolint
-data <- teal.data::cdisc_data(
-  teal.data::cdisc_dataset("ADSL", ADSL),
-  teal.data::cdisc_dataset("ADTTE", ADTTE)
-)
+ADAE <- teal.transform::rADAE # nolint
+ADRS <- teal.transform::rADRS # nolint
 
-ds <- teal.slice::init_filtered_data(data)
+data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE), ADAE = reactive(ADAE), ADRS = reactive(ADRS))
+join_keys <- teal.data::default_cdisc_join_keys[c("ADSL", "ADTTE", "ADAE", "ADRS")]
+primary_keys_list <- lapply(join_keys, function(x) x[[1]])
 
 vc_hard <- variable_choices("ADSL", subset = c("STUDYID", "USUBJID"))
 vc_hard_exp <- structure(
@@ -36,15 +36,10 @@ vc_fun_short_exp <- structure(
 # Delayed data extract - single data connector with two scda dataset connectors ----
 get_continuous <- function(data) {
   # example function to show selections from delayed data
-  idx <- vapply(data, function(x) is.numeric(x) && length(unique(x)) > 6, logical(1))
-  colnames(data)[idx]
+  names(Filter(is.numeric, data))
 }
 
 testthat::test_that("Delayed data extract - single data connector with two scda dataset connectors", {
-  ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-  ADAE <- teal.data::cdisc_dataset(dataname = "ADAE", x = teal.transform::rADAE) # nolint
-  data <- teal.data::cdisc_data(ADSL, ADAE)
-
   x <- data_extract_spec(
     dataname = "ADSL",
     select = select_spec(
@@ -59,32 +54,29 @@ testthat::test_that("Delayed data extract - single data connector with two scda
     )
   )
 
-  # test delayed data extract
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adae <- data$get_dataset("ADAE")$get_raw_data() # nolint
   x_expected <- data_extract_spec(
     dataname = "ADSL",
     select = select_spec(
-      choices = variable_choices(adsl, subset = get_continuous, key = teal.data::get_cdisc_keys("ADSL")),
+      choices = variable_choices(ADSL, subset = get_continuous, key = c("STUDYID", "USUBJID")),
       selected = NULL
     )
   )
   y_expected <- data_extract_spec(
     dataname = "ADAE",
     select = select_spec(
-      choices = variable_choices(adae, subset = get_continuous, key = teal.data::get_cdisc_keys("ADAE"))
+      choices = variable_choices(
+        ADAE,
+        subset = get_continuous, key = c("STUDYID", "USUBJID", "ASTDTM", "AETERM", "AESEQ")
+      )
     )
   )
-  data_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    reactive(ds$get_data(dataname = x, filtered = TRUE))
-  })
-  key_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    isolate(ds$get_keys(dataname = x))
-  })
-  x_result <- isolate(resolve(x, datasets = data_list, keys = key_list))
-  y_result <- isolate(resolve(y, datasets = data_list, keys = key_list))
+  data_list <- list(ADSL = reactive(ADSL), ADAE = reactive(ADAE))
+  primary_keys_list <- list(
+    ADSL = c("STUDYID", "USUBJID"),
+    ADAE = c("STUDYID", "USUBJID", "ASTDTM", "AETERM", "AESEQ")
+  )
+  x_result <- isolate(resolve(x, datasets = data_list, keys = primary_keys_list))
+  y_result <- isolate(resolve(y, datasets = data_list, keys = primary_keys_list))
   testthat::expect_identical(x_result, x_expected)
   testthat::expect_identical(y_result, y_expected)
 })
@@ -92,104 +84,27 @@ testthat::test_that("Delayed data extract - single data connector with two scda
 # Delayed choices selected - single data connector with two scda dataset connectors ----
 
 testthat::test_that("Delayed choices selected - single data connector with two scda dataset connectors", {
-  ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-  ADAE <- teal.data::cdisc_dataset(dataname = "ADAE", x = teal.transform::rADAE) # nolint
-
-  data <- teal.data::cdisc_data(ADSL, ADAE)
-
+  data_list <- list(ADSL = reactive(ADSL), ADAE = reactive(ADAE))
+  primary_keys_list <- list(
+    ADSL = c("STUDYID", "USUBJID"),
+    ADAE = c("STUDYID", "USUBJID", "ASTDTM", "AETERM", "AESEQ")
+  )
   choices <- variable_choices("ADSL")
-  ds <- teal.slice::init_filtered_data(data)
+  choices_result <- isolate(resolve(choices, datasets = data_list, keys = primary_keys_list))
 
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  choices_expected <- variable_choices(adsl, key = teal.data::get_cdisc_keys("ADSL"))
-  data_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    reactive(ds$get_data(dataname = x, filtered = TRUE))
-  })
-  key_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    isolate(ds$get_keys(dataname = x))
-  })
-  choices_result <- isolate(resolve(choices, datasets = data_list, keys = key_list))
+  choices_expected <- variable_choices(ADSL, key = c("STUDYID", "USUBJID"))
   testthat::expect_identical(choices_result, choices_expected)
 })
 
 # Delayed data extract - filtered ----
 
 testthat::test_that("Delayed data extract - filtered", {
-  ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-  ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = rADRS) # nolint
-  data <- teal.data::cdisc_data(ADSL, ADRS)
-
-  x <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices("ADSL", subset = get_continuous)
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices("ADSL",
-        var_choices = "ARMCD",
-        var_label = "ARM",
-        subset = function(data) levels(data$ARMCD)[1:2]
-      ),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices("ADRS", subset = get_continuous),
-      selected = c("AGE: Age" = "AGE")
-    )
+  data_list <- list(ADSL = reactive(ADSL), ADRS = reactive(ADRS))
+  primary_keys_list <- list(
+    ADSL = c("STUDYID", "USUBJID"),
+    ADRS = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
   )
 
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
-  x_expected <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices(adsl, subset = get_continuous),
-      selected = NULL
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices(adsl,
-        var_choices = "ARMCD",
-        var_label = "ARM",
-        subset = function(data) levels(data$ARMCD)[1:2]
-      ),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y_expected <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices(adrs, subset = get_continuous)
-    )
-  )
-  data_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    reactive(ds$get_data(dataname = x, filtered = TRUE))
-  })
-  key_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    isolate(ds$get_keys(dataname = x))
-  })
-  x_result <- isolate(resolve(x, datasets = data_list, key_list))
-  y_result <- isolate(resolve(y, datasets = data_list, key_list))
-  testthat::expect_identical(x_result, x_expected)
-  testthat::expect_identical(y_result, y_expected)
-})
-
-# Delayed extract filter concatenated - single data connector with two scda dataset connectors ----
-testthat::test_that("Delayed extract filter concatenated - single data connector with two scda dataset connectors", {
-  ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-  ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = rADRS) # nolint
-  data <- teal.data::teal_data(ADSL, ADRS)
-
   x <- data_extract_spec(
     dataname = "ADSL",
     select = select_spec(
@@ -212,31 +127,9 @@ testthat::test_that("Delayed extract filter concatenated - single data connector
     select = select_spec(
       choices = variable_choices("ADRS", subset = get_continuous),
       selected = c("AGE: Age" = "AGE")
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = c("PARAMCD", "AVISIT"),
-      choices = value_choices(
-        data = "ADRS",
-        var_choices = c("PARAMCD", "AVISIT"),
-        var_label = c("PARAMCD", "AVISIT"),
-        subset = function(data) {
-          paste(
-            levels(data$PARAMCD),
-            levels(data$AVISIT)[4:6],
-            sep = " - "
-          )
-        }
-      ),
-      selected = "INVET - END OF INDUCTION",
-      multiple = TRUE
     )
   )
 
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
   x_expected <- data_extract_spec(
     dataname = "ADSL",
     select = select_spec(
@@ -246,406 +139,7 @@ testthat::test_that("Delayed extract filter concatenated - single data connector
     filter = filter_spec(
       label = "Select endpoints:",
       vars = "ARMCD",
-      choices = value_choices(adsl,
-        var_choices = "ARMCD",
-        var_label = "ARM",
-        subset = function(data) levels(data$ARMCD)[1:2]
-      ),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y_expected <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices(adrs, subset = get_continuous)
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = c("PARAMCD", "AVISIT"),
-      choices = value_choices(
-        data = ADRS,
-        var_choices = c("PARAMCD", "AVISIT"),
-        var_label = c("PARAMCD", "AVISIT"),
-        subset = function(data) {
-          paste(
-            levels(data$PARAMCD),
-            levels(data$AVISIT)[4:6],
-            sep = " - "
-          )
-        }
-      ),
-      selected = "INVET - END OF INDUCTION",
-      multiple = TRUE
-    )
-  )
-  data_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    reactive(ds$get_data(dataname = x, filtered = TRUE))
-  })
-  key_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    isolate(ds$get_keys(dataname = x))
-  })
-  x_result <- isolate(resolve(x, datasets = data_list, key_list))
-  y_result <- isolate(resolve(y, datasets = data_list, key_list))
-  testthat::expect_identical(x_result, x_expected)
-  testthat::expect_identical(y_result, y_expected)
-})
-
-# Delayed extract two filters - single data connector with two scda dataset connectors ----
-testthat::test_that("Delayed extract two filters - single data connector with two scda dataset connectors", {
-  ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-  ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = rADRS) # nolint
-  data <- teal.data::teal_data(ADSL, ADRS)
-
-  x <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices("ADSL", subset = get_continuous)
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices("ADSL",
-        var_choices = "ARMCD",
-        var_label = "ARM",
-        subset = function(data) levels(data$ARMCD)[1:2]
-      ),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices("ADRS", subset = get_continuous),
-      selected = c("AGE: Age" = "AGE")
-    ),
-    filter = list(
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "PARAMCD",
-        choices = value_choices(
-          data = "ADRS",
-          var_choices = "PARAMCD",
-          var_label = "PARAMCD",
-          subset = function(data) levels(data$PARAMCD)[2:3]
-        ),
-        selected = "OVRINV",
-        multiple = TRUE
-      ),
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "AVISIT",
-        choices = value_choices(
-          data = "ADRS",
-          var_choices = "AVISIT",
-          var_label = "AVISIT",
-          subset = function(data) levels(data$AVISIT)[5:6]
-        ),
-        selected = "END OF INDUCTION",
-        multiple = TRUE
-      )
-    )
-  )
-
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
-  x_expected <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices(adsl, subset = get_continuous),
-      selected = NULL
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices(adsl,
-        var_choices = "ARMCD",
-        var_label = "ARM",
-        subset = function(data) levels(data$ARMCD)[1:2]
-      ),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y_expected <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices(adrs, subset = get_continuous)
-    ),
-    filter = list(
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "PARAMCD",
-        choices = value_choices(
-          data = adrs,
-          var_choices = "PARAMCD",
-          var_label = "PARAMCD",
-          subset = function(data) levels(data$PARAMCD)[2:3]
-        ),
-        selected = "OVRINV",
-        multiple = TRUE
-      ),
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "AVISIT",
-        choices = value_choices(
-          data = adrs,
-          var_choices = "AVISIT",
-          var_label = "AVISIT",
-          subset = function(data) levels(data$AVISIT)[5:6]
-        ),
-        selected = "END OF INDUCTION",
-        multiple = TRUE
-      )
-    )
-  )
-  data_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    reactive(ds$get_data(dataname = x, filtered = TRUE))
-  })
-  key_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    isolate(ds$get_keys(dataname = x))
-  })
-  x_result <- isolate(resolve(x, datasets = data_list, key_list))
-  y_result <- isolate(resolve(y, datasets = data_list, key_list))
-  testthat::expect_identical(x_result, x_expected)
-  testthat::expect_identical(y_result, y_expected)
-})
-
-# Delayed extract - dataset & connector ----
-testthat::test_that("Delayed extract - TealData with single dataset and multiple connectors", {
-  ADSL <- teal.data::dataset( # nolint
-    dataname = "ADSL",
-    teal.transform::rADSL,
-    keys = teal.data::get_cdisc_keys("ADSL"),
-    code = "ADSL <- teal.transform::rADSL",
-    label = "ADSL"
-  )
-
-  ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = teal.transform::rADRS) # nolint
-  ADTTE <- teal.data::cdisc_dataset(dataname = "ADTTE", x = teal.transform::rADTTE) # nolint
-  data <- teal.data::cdisc_data(ADSL, ADRS, ADTTE)
-
-  x <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices("ADSL", subset = get_continuous)
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices(ADSL$get_raw_data(), var_choices = "ARMCD", var_label = "ARM"),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices("ADRS", subset = get_continuous),
-      selected = c("AGE: Age" = "AGE")
-    ),
-    filter = list(
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "PARAMCD",
-        choices = value_choices(
-          data = "ADRS",
-          var_choices = "PARAMCD",
-          var_label = "PARAMCD",
-          subset = function(data) levels(data$PARAMCD)[2:3]
-        ),
-        selected = "OVRINV",
-        multiple = TRUE
-      ),
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "AVISIT",
-        choices = value_choices(
-          data = "ADRS",
-          var_choices = "AVISIT",
-          var_label = "AVISIT",
-          subset = function(data) levels(data$AVISIT)[5:6]
-        ),
-        selected = "END OF INDUCTION",
-        multiple = TRUE
-      )
-    )
-  )
-
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
-  x_expected <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices(adsl, subset = get_continuous, key = teal.data::get_cdisc_keys("ADSL")),
-      NULL
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices(ADSL$get_raw_data(), var_choices = "ARMCD", var_label = "ARM"),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y_expected <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices(adrs, subset = get_continuous, key = teal.data::get_cdisc_keys("ADRS"))
-    ),
-    filter = list(
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "PARAMCD",
-        choices = value_choices(
-          data = adrs,
-          var_choices = "PARAMCD",
-          var_label = "PARAMCD",
-          subset = function(data) levels(data$PARAMCD)[2:3]
-        ),
-        selected = "OVRINV",
-        multiple = TRUE
-      ),
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "AVISIT",
-        choices = value_choices(
-          data = adrs,
-          var_choices = "AVISIT",
-          var_label = "AVISIT",
-          subset = function(data) levels(data$AVISIT)[5:6]
-        ),
-        selected = "END OF INDUCTION",
-        multiple = TRUE
-      )
-    )
-  )
-  data_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    reactive(ds$get_data(dataname = x, filtered = TRUE))
-  })
-  key_list <- sapply(X = ds$datanames(), simplify = FALSE, FUN = function(x) {
-    isolate(ds$get_keys(dataname = x))
-  })
-  x_result <- isolate(resolve(x, datasets = data_list, key_list))
-  y_result <- isolate(resolve(y, datasets = data_list, key_list))
-  testthat::expect_identical(x_result, x_expected)
-  testthat::expect_identical(y_result, y_expected)
-})
-
-# with resolve_delayed
-testthat::test_that("Delayed data extract - single data connector with two scda dataset connectors - resolve_delayed", {
-  ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-  ADAE <- teal.data::cdisc_dataset(dataname = "ADAE", x = teal.transform::rADAE) # nolint
-
-  data <- teal.data::cdisc_data(ADSL, ADAE)
-
-  x <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices("ADSL", subset = get_continuous)
-    )
-  )
-  y <- data_extract_spec(
-    dataname = "ADAE",
-    select = select_spec(
-      choices = variable_choices("ADAE", subset = get_continuous),
-      selected = c("AGE: Age" = "AGE")
-    )
-  )
-
-  # test delayed data extract
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adae <- data$get_dataset("ADAE")$get_raw_data() # nolint
-  x_expected <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices(adsl, subset = get_continuous, key = teal.data::get_cdisc_keys("ADSL")),
-      selected = NULL
-    )
-  )
-  y_expected <- data_extract_spec(
-    dataname = "ADAE",
-    select = select_spec(
-      choices = variable_choices(adae, subset = get_continuous, key = teal.data::get_cdisc_keys("ADAE"))
-    )
-  )
-  x_result <- isolate(resolve_delayed(x, datasets = ds))
-  y_result <- isolate(resolve_delayed(y, datasets = ds))
-  testthat::expect_identical(x_result, x_expected)
-  testthat::expect_identical(y_result, y_expected)
-})
-
-# Delayed choices selected - single data connector with two scda dataset connectors ----
-testthat::test_that(
-  desc = "Delayed choices selected - single data connector with two scda dataset connectors - resolve_delayed",
-  code = {
-    ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-    ADAE <- teal.data::cdisc_dataset(dataname = "ADAE", x = teal.transform::rADAE) # nolint
-    data <- teal.data::cdisc_data(ADSL, ADAE)
-
-    choices <- variable_choices("ADSL")
-    ds <- teal.slice::init_filtered_data(data)
-
-    adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-    choices_expected <- variable_choices(adsl, key = teal.data::get_cdisc_keys("ADSL"))
-    choices_result <- isolate(resolve_delayed(choices, datasets = ds))
-    testthat::expect_identical(choices_result, choices_expected)
-  }
-)
-
-# Delayed data extract - filtered ----
-
-testthat::test_that("Delayed data extract - filtered", {
-  ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-  ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = rADRS) # nolint
-  data <- teal.data::cdisc_data(ADSL, ADRS)
-
-  x <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices("ADSL", subset = get_continuous)
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices("ADSL",
-        var_choices = "ARMCD",
-        var_label = "ARM",
-        subset = function(data) levels(data$ARMCD)[1:2]
-      ),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices("ADRS", subset = get_continuous),
-      selected = c("AGE: Age" = "AGE")
-    )
-  )
-
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
-  x_expected <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices(adsl, subset = get_continuous),
-      selected = NULL
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices(adsl,
+      choices = value_choices(ADSL,
         var_choices = "ARMCD",
         var_label = "ARM",
         subset = function(data) levels(data$ARMCD)[1:2]
@@ -657,351 +151,12 @@ testthat::test_that("Delayed data extract - filtered", {
   y_expected <- data_extract_spec(
     dataname = "ADRS",
     select = select_spec(
-      choices = variable_choices(adrs, subset = get_continuous)
-    )
-  )
-  x_result <- isolate(resolve_delayed(x, datasets = ds))
-  y_result <- isolate(resolve_delayed(y, datasets = ds))
-  testthat::expect_identical(x_result, x_expected)
-  testthat::expect_identical(y_result, y_expected)
-})
-
-# Delayed extract filter concatenated - single data connector with two scda dataset connectors ----
-testthat::test_that(
-  desc = "Delayed extract filter concatenated - single data connector with two scda dataset connectors - res_delayed",
-  code = {
-    ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-    ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = rADRS) # nolint
-    data <- teal.data::teal_data(ADSL, ADRS)
-
-    x <- data_extract_spec(
-      dataname = "ADSL",
-      select = select_spec(
-        choices = variable_choices("ADSL", subset = get_continuous)
-      ),
-      filter = filter_spec(
-        label = "Select endpoints:",
-        vars = "ARMCD",
-        choices = value_choices("ADSL",
-          var_choices = "ARMCD",
-          var_label = "ARM",
-          subset = function(data) levels(data$ARMCD)[1:2]
-        ),
-        selected = "ARM A",
-        multiple = TRUE
-      )
-    )
-    y <- data_extract_spec(
-      dataname = "ADRS",
-      select = select_spec(
-        choices = variable_choices("ADRS", subset = get_continuous),
-        selected = c("AGE: Age" = "AGE")
-      ),
-      filter = filter_spec(
-        label = "Select endpoints:",
-        vars = c("PARAMCD", "AVISIT"),
-        choices = value_choices(
-          data = "ADRS",
-          var_choices = c("PARAMCD", "AVISIT"),
-          var_label = c("PARAMCD", "AVISIT"),
-          subset = function(data) {
-            paste(
-              levels(data$PARAMCD),
-              levels(data$AVISIT)[4:6],
-              sep = " - "
-            )
-          }
-        ),
-        selected = "INVET - END OF INDUCTION",
-        multiple = TRUE
-      )
-    )
-
-    ds <- teal.slice::init_filtered_data(data)
-
-    adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-    adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
-    x_expected <- data_extract_spec(
-      dataname = "ADSL",
-      select = select_spec(
-        choices = variable_choices(adsl, subset = get_continuous),
-        selected = NULL
-      ),
-      filter = filter_spec(
-        label = "Select endpoints:",
-        vars = "ARMCD",
-        choices = value_choices(adsl,
-          var_choices = "ARMCD",
-          var_label = "ARM",
-          subset = function(data) levels(data$ARMCD)[1:2]
-        ),
-        selected = "ARM A",
-        multiple = TRUE
-      )
-    )
-    y_expected <- data_extract_spec(
-      dataname = "ADRS",
-      select = select_spec(
-        choices = variable_choices(adrs, subset = get_continuous)
-      ),
-      filter = filter_spec(
-        label = "Select endpoints:",
-        vars = c("PARAMCD", "AVISIT"),
-        choices = value_choices(
-          data = adrs,
-          var_choices = c("PARAMCD", "AVISIT"),
-          var_label = c("PARAMCD", "AVISIT"),
-          subset = function(data) {
-            paste(
-              levels(data$PARAMCD),
-              levels(data$AVISIT)[4:6],
-              sep = " - "
-            )
-          }
-        ),
-        selected = "INVET - END OF INDUCTION",
-        multiple = TRUE
-      )
-    )
-    x_result <- isolate(resolve_delayed(x, datasets = ds))
-    y_result <- isolate(resolve_delayed(y, datasets = ds))
-    testthat::expect_identical(x_result, x_expected)
-    testthat::expect_identical(y_result, y_expected)
-  }
-)
-
-# Delayed extract two filters - single data connector with two scda dataset connectors ----
-testthat::test_that(
-  desc = "Delayed extract two filters - single data connector with two scda dataset connectors - resolve_delayed",
-  code = {
-    ADSL <- teal.data::cdisc_dataset(dataname = "ADSL", x = rADSL) # nolint
-    ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = rADRS) # nolint
-    data <- teal.data::teal_data(ADSL, ADRS)
-
-    x <- data_extract_spec(
-      dataname = "ADSL",
-      select = select_spec(
-        choices = variable_choices("ADSL", subset = get_continuous)
-      ),
-      filter = filter_spec(
-        label = "Select endpoints:",
-        vars = "ARMCD",
-        choices = value_choices("ADSL",
-          var_choices = "ARMCD",
-          var_label = "ARM",
-          subset = function(data) levels(data$ARMCD)[1:2]
-        ),
-        selected = "ARM A",
-        multiple = TRUE
-      )
-    )
-    y <- data_extract_spec(
-      dataname = "ADRS",
-      select = select_spec(
-        choices = variable_choices("ADRS", subset = get_continuous),
-        selected = c("AGE: Age" = "AGE")
-      ),
-      filter = list(
-        filter_spec(
-          label = "Select endpoints:",
-          vars = "PARAMCD",
-          choices = value_choices(
-            data = "ADRS",
-            var_choices = "PARAMCD",
-            var_label = "PARAMCD",
-            subset = function(data) levels(data$PARAMCD)[2:3]
-          ),
-          selected = "OVRINV",
-          multiple = TRUE
-        ),
-        filter_spec(
-          label = "Select endpoints:",
-          vars = "AVISIT",
-          choices = value_choices(
-            data = "ADRS",
-            var_choices = "AVISIT",
-            var_label = "AVISIT",
-            subset = function(data) levels(data$AVISIT)[5:6]
-          ),
-          selected = "END OF INDUCTION",
-          multiple = TRUE
-        )
-      )
-    )
-
-    ds <- teal.slice::init_filtered_data(data)
-
-    adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-    adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
-    x_expected <- data_extract_spec(
-      dataname = "ADSL",
-      select = select_spec(
-        choices = variable_choices(adsl, subset = get_continuous),
-        selected = NULL
-      ),
-      filter = filter_spec(
-        label = "Select endpoints:",
-        vars = "ARMCD",
-        choices = value_choices(adsl,
-          var_choices = "ARMCD",
-          var_label = "ARM",
-          subset = function(data) levels(data$ARMCD)[1:2]
-        ),
-        selected = "ARM A",
-        multiple = TRUE
-      )
-    )
-    y_expected <- data_extract_spec(
-      dataname = "ADRS",
-      select = select_spec(
-        choices = variable_choices(adrs, subset = get_continuous)
-      ),
-      filter = list(
-        filter_spec(
-          label = "Select endpoints:",
-          vars = "PARAMCD",
-          choices = value_choices(
-            data = adrs,
-            var_choices = "PARAMCD",
-            var_label = "PARAMCD",
-            subset = function(data) levels(data$PARAMCD)[2:3]
-          ),
-          selected = "OVRINV",
-          multiple = TRUE
-        ),
-        filter_spec(
-          label = "Select endpoints:",
-          vars = "AVISIT",
-          choices = value_choices(
-            data = adrs,
-            var_choices = "AVISIT",
-            var_label = "AVISIT",
-            subset = function(data) levels(data$AVISIT)[5:6]
-          ),
-          selected = "END OF INDUCTION",
-          multiple = TRUE
-        )
-      )
-    )
-    x_result <- isolate(resolve_delayed(x, datasets = ds))
-    y_result <- isolate(resolve_delayed(y, datasets = ds))
-    testthat::expect_identical(x_result, x_expected)
-    testthat::expect_identical(y_result, y_expected)
-  }
-)
-
-# Delayed extract - dataset & connector ----
-testthat::test_that("Delayed extract - TealData with single dataset and multiple connectors - resolve_delayed", {
-  ADSL <- teal.data::dataset( # nolint
-    dataname = "ADSL",
-    teal.transform::rADSL,
-    keys = teal.data::get_cdisc_keys("ADSL"),
-    code = "ADSL <- teal.transform::rADSL",
-    label = "ADSL"
-  )
-  ADRS <- teal.data::cdisc_dataset(dataname = "ADRS", x = teal.transform::rADRS) # nolint
-  ADTTE <- teal.data::cdisc_dataset(dataname = "ADTTE", x = teal.transform::rADTTE) # nolint
-  data <- teal.data::cdisc_data(ADSL, ADRS, ADTTE)
-
-  x <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices("ADSL", subset = get_continuous)
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices(ADSL$get_raw_data(), var_choices = "ARMCD", var_label = "ARM"),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices("ADRS", subset = get_continuous),
-      selected = c("AGE: Age" = "AGE")
-    ),
-    filter = list(
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "PARAMCD",
-        choices = value_choices(
-          data = "ADRS",
-          var_choices = "PARAMCD",
-          var_label = "PARAMCD",
-          subset = function(data) levels(data$PARAMCD)[2:3]
-        ),
-        selected = "OVRINV",
-        multiple = TRUE
-      ),
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "AVISIT",
-        choices = value_choices(
-          data = "ADRS",
-          var_choices = "AVISIT",
-          var_label = "AVISIT",
-          subset = function(data) levels(data$AVISIT)[5:6]
-        ),
-        selected = "END OF INDUCTION",
-        multiple = TRUE
-      )
+      choices = variable_choices(ADRS, subset = get_continuous)
     )
   )
 
-  ds <- teal.slice::init_filtered_data(data)
-
-  adsl <- data$get_dataset("ADSL")$get_raw_data() # nolint
-  adrs <- data$get_dataset("ADRS")$get_raw_data() # nolint
-  x_expected <- data_extract_spec(
-    dataname = "ADSL",
-    select = select_spec(
-      choices = variable_choices(adsl, subset = get_continuous, key = teal.data::get_cdisc_keys("ADSL")),
-      NULL
-    ),
-    filter = filter_spec(
-      label = "Select endpoints:",
-      vars = "ARMCD",
-      choices = value_choices(ADSL$get_raw_data(), var_choices = "ARMCD", var_label = "ARM"),
-      selected = "ARM A",
-      multiple = TRUE
-    )
-  )
-  y_expected <- data_extract_spec(
-    dataname = "ADRS",
-    select = select_spec(
-      choices = variable_choices(adrs, subset = get_continuous, key = teal.data::get_cdisc_keys("ADRS"))
-    ),
-    filter = list(
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "PARAMCD",
-        choices = value_choices(
-          data = adrs,
-          var_choices = "PARAMCD",
-          var_label = "PARAMCD",
-          subset = function(data) levels(data$PARAMCD)[2:3]
-        ),
-        selected = "OVRINV",
-        multiple = TRUE
-      ),
-      filter_spec(
-        label = "Select endpoints:",
-        vars = "AVISIT",
-        choices = value_choices(
-          data = adrs,
-          var_choices = "AVISIT",
-          var_label = "AVISIT",
-          subset = function(data) levels(data$AVISIT)[5:6]
-        ),
-        selected = "END OF INDUCTION",
-        multiple = TRUE
-      )
-    )
-  )
-  x_result <- isolate(resolve_delayed(x, datasets = ds))
-  y_result <- isolate(resolve_delayed(y, datasets = ds))
+  x_result <- isolate(resolve(x, datasets = data_list, primary_keys_list))
+  y_result <- isolate(resolve(y, datasets = data_list, primary_keys_list))
   testthat::expect_identical(x_result, x_expected)
   testthat::expect_identical(y_result, y_expected)
 })
diff --git a/tests/testthat/test-dplyr_call_examples.R b/tests/testthat/test-dplyr_call_examples.R
index 3a0a6794..5deaf32d 100644
--- a/tests/testthat/test-dplyr_call_examples.R
+++ b/tests/testthat/test-dplyr_call_examples.R
@@ -1,3 +1,4 @@
+# nolint start
 # Different join keys ------
 testthat::test_that("Different join types", {
   merged_selectors1 <- merge_selectors(
@@ -6,7 +7,7 @@ testthat::test_that("Different join types", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -14,16 +15,16 @@ testthat::test_that("Different join types", {
         dataname = "ADSL2",
         filters = NULL,
         select = c("SEX", "STRATA"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )
   jk1 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL2", "ADSL2", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL2", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL2", "ADSL2", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL2", c("STUDYID", "USUBJID"))
   )
 
 
@@ -71,7 +72,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         select = "AGE",
         internal_id = "x1"
@@ -79,7 +80,7 @@ testthat::test_that("Single wide dataset", {
     )
   )[[1]]
   jk1 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -102,14 +103,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("USUBJID", "AGE", "SEX"), # adding USUBJID doesn"t affect result - keys are selected always
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk2 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -132,7 +133,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -140,14 +141,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk3 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -170,7 +171,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -178,7 +179,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -186,7 +187,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("STRATA", "ARMCD", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -194,14 +195,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("COUNTRY"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x4"
       )
     )
   )[[1]]
   jk4 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -224,7 +225,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -232,7 +233,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -240,7 +241,7 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("STRATA", "ARMCD", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -248,14 +249,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("COUNTRY"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x4"
       )
     )
   )[[1]]
   jk5 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -278,14 +279,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = list(list(columns = "SEX", selected = "F", multiple = TRUE, drop_keys = FALSE)),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk6 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -309,14 +310,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = list(list(columns = "STUDYID", selected = "STUDY1", multiple = TRUE, drop_keys = FALSE)),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk7 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -340,14 +341,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = list(list(columns = "STUDYID", selected = "STUDY1", multiple = TRUE, drop_keys = TRUE)),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk8 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -371,14 +372,14 @@ testthat::test_that("Single wide dataset", {
         dataname = "ADSL",
         filters = list(list(columns = "STUDYID", selected = "STUDY1", multiple = TRUE, drop_keys = TRUE)),
         select = c("AGE", "STUDYID"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk9 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -405,7 +406,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -413,16 +414,16 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = c("SEX", "STRATA"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )
   jk1 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL2", "ADSL2", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL2", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL2", "ADSL2", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL2", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -457,7 +458,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -465,15 +466,15 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk2 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL2", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL2", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -508,7 +509,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -516,7 +517,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = c("AGE", "SEX"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -524,7 +525,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL3",
         filters = NULL,
         select = c("AGE", "SEX", "STRATA"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -532,16 +533,16 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = c("AGE", "STRATA", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x4"
       )
     )
   )[[1]]
   jk3 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL2", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL3", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL2", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL3", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -585,7 +586,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -593,7 +594,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = c("AGE", "SEX"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -601,7 +602,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL3",
         filters = NULL,
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -609,16 +610,16 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x4"
       )
     )
   )[[1]]
   jk4 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL2", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL3", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL2", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL3", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -661,7 +662,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = c("STUDYID", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -669,7 +670,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = c("STUDYID", "AGE", "SEX"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -677,7 +678,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL",
         filters = NULL,
         select = "STUDYID",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -685,7 +686,7 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL3",
         filters = NULL,
         select = c("USUBJID", "AGE", "SEX", "STRATA"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x4"
       ),
@@ -693,16 +694,16 @@ testthat::test_that("Multiple wide dataset", {
         dataname = "ADSL2",
         filters = NULL,
         select = c("AGE", "STRATA", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x5"
       )
     )
   )[[1]]
   jk5 <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL2", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADSL3", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL2", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADSL3", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -749,14 +750,14 @@ testthat::test_that("Single long dataset", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE, drop_keys = FALSE)),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk1 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_identical(
@@ -780,14 +781,14 @@ testthat::test_that("Single long dataset", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE, drop_keys = TRUE)),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk1 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_identical(
@@ -814,22 +815,21 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE, drop_keys = TRUE)
         ),
         select = c("AGE", "SEX"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk2 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
     get_dplyr_call(merged_selectors2, join_keys = jk2),
     quote(
       ADRS %>%
-        dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-          c("BASELINE", "SCREENING")) %>%
+        dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("BASELINE", "SCREENING")) %>%
         dplyr::select(STUDYID, USUBJID, AVISIT, AGE, SEX)
     )
   ) # AVISIT should be in select - filter is not complete (two levels selected)
@@ -849,7 +849,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE, drop_keys = FALSE)
         ),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -860,14 +860,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE, drop_keys = FALSE)
         ),
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk3 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -895,7 +895,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE, drop_keys = TRUE)
         ),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -906,14 +906,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE, drop_keys = FALSE)
         ),
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk3 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   # failure:
@@ -958,7 +958,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = "BASELINE", multiple = TRUE, drop_keys = TRUE)
         ),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -969,14 +969,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE, drop_keys = TRUE)
         ),
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk4 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1018,7 +1018,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE"), multiple = TRUE)
         ),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -1026,14 +1026,14 @@ testthat::test_that("Single long dataset", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE)),
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk5 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1075,7 +1075,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE)
         ),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -1086,14 +1086,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk6 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1104,15 +1104,13 @@ testthat::test_that("Single long dataset", {
     list(
       deparse(quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" &
-            AVISIT %in% c("BASELINE", "SCREENING")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("BASELINE", "SCREENING")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, AGE) %>%
           dplyr::rename(x1.AGE = AGE)
       ), 120),
       deparse(quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("SCREENING", "FOLLOW UP")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("SCREENING", "FOLLOW UP")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, SEX, AGE, BMRKR1) %>%
           dplyr::rename(x2.AGE = AGE)
       ), 120)
@@ -1138,7 +1136,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "SEX", selected = c("F", "M"), multiple = TRUE)
         ),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -1149,14 +1147,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = c("SEX", "AGE", "BMRKR1"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk7 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1167,15 +1165,13 @@ testthat::test_that("Single long dataset", {
     list(
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("BASELINE", "SCREENING") & SEX %in% c("F", "M")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("BASELINE", "SCREENING") & SEX %in% c("F", "M")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, AGE) %>%
           dplyr::rename(x1.AGE = AGE)
       ),
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "INVET" & AVISIT %in%
-            c("SCREENING", "FOLLOW UP")) %>%
+          dplyr::filter(PARAMCD == "INVET" & AVISIT %in% c("SCREENING", "FOLLOW UP")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, SEX, AGE, BMRKR1) %>%
           dplyr::rename(x2.AGE = AGE)
       )
@@ -1202,7 +1198,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "SEX", selected = c("F", "M"), multiple = TRUE)
         ),
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -1213,7 +1209,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -1224,14 +1220,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x3"
       )
     )
   )[[1]]
   jk8 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1243,8 +1239,7 @@ testthat::test_that("Single long dataset", {
     list(
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "INVET" & AVISIT %in%
-            c("BASELINE", "SCREENING") & SEX %in% c("F", "M")) %>%
+          dplyr::filter(PARAMCD == "INVET" & AVISIT %in% c("BASELINE", "SCREENING") & SEX %in% c("F", "M")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, AGE) %>%
           dplyr::rename(x1.AGE = AGE)
       ),
@@ -1255,8 +1250,7 @@ testthat::test_that("Single long dataset", {
       ),
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("SCREENING", "FOLLOW UP")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("SCREENING", "FOLLOW UP")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, AVAL, AGE) %>%
           dplyr::rename(x3.AGE = AGE)
       )
@@ -1279,14 +1273,14 @@ testthat::test_that("Single long dataset", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE, drop_keys = TRUE)),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk9 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_identical(
@@ -1321,22 +1315,21 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk10 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
     get_dplyr_call(merged_selectors10, join_keys = jk10),
     quote(
       ADRS %>%
-        dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-          c("BASELINE", "SCREENING")) %>%
+        dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("BASELINE", "SCREENING")) %>%
         dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
         tidyr::pivot_longer(cols = "AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
         tidyr::unite(KEY, MEASURE, PARAMCD, AVISIT) %>%
@@ -1365,22 +1358,21 @@ testthat::test_that("Single long dataset", {
           list(columns = "SEX", selected = c("M", "F"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk11 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
     get_dplyr_call(merged_selectors11, join_keys = jk11),
     quote(
       ADRS %>%
-        dplyr::filter(PARAMCD == "BESRSPI" & SEX %in%
-          c("M", "F")) %>%
+        dplyr::filter(PARAMCD == "BESRSPI" & SEX %in% c("M", "F")) %>%
         dplyr::select(STUDYID, USUBJID, AVISIT, PARAMCD, AVAL) %>%
         tidyr::pivot_longer(cols = "AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
         tidyr::unite(KEY, MEASURE, PARAMCD) %>%
@@ -1408,7 +1400,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -1419,14 +1411,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk12 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1461,7 +1453,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -1472,14 +1464,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk13 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1490,8 +1482,7 @@ testthat::test_that("Single long dataset", {
     list(
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "INVET" & AVISIT %in%
-            c("BASELINE", "SCREENING")) %>%
+          dplyr::filter(PARAMCD == "INVET" & AVISIT %in% c("BASELINE", "SCREENING")) %>%
           dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
           dplyr::rename(x1.AVAL = AVAL) %>%
           tidyr::pivot_longer(cols = "x1.AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
@@ -1500,8 +1491,7 @@ testthat::test_that("Single long dataset", {
       ),
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("SCREENING", "FOLLOW UP")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("SCREENING", "FOLLOW UP")) %>%
           dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
           dplyr::rename(x2.AVAL = AVAL) %>%
           tidyr::pivot_longer(cols = "x2.AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
@@ -1535,7 +1525,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("BASELINE", "SCREENING"), multiple = TRUE)
         ),
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         select = character(0),
         internal_id = "x1"
@@ -1547,14 +1537,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk14 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1565,8 +1555,7 @@ testthat::test_that("Single long dataset", {
     list(
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("BASELINE", "SCREENING")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("BASELINE", "SCREENING")) %>%
           dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT) %>%
           tidyr::pivot_longer(cols = tidyselect::everything(), names_to = "MEASURE", values_to = "VALUE") %>%
           tidyr::unite(KEY, MEASURE, PARAMCD, AVISIT) %>%
@@ -1574,8 +1563,7 @@ testthat::test_that("Single long dataset", {
       ),
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("SCREENING", "FOLLOW UP")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("SCREENING", "FOLLOW UP")) %>%
           dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
           tidyr::pivot_longer(cols = "AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
           tidyr::unite(KEY, MEASURE, PARAMCD, AVISIT) %>%
@@ -1606,7 +1594,7 @@ testthat::test_that("Single long dataset", {
         dataname = "ADRS",
         filters = list(list(columns = "SEX", selected = c("M", "F"), multiple = TRUE)),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -1617,14 +1605,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk15 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1644,8 +1632,7 @@ testthat::test_that("Single long dataset", {
       ),
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("SCREENING", "FOLLOW UP")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("SCREENING", "FOLLOW UP")) %>%
           dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
           dplyr::rename(x2.AVAL = AVAL) %>%
           tidyr::pivot_longer(cols = "x2.AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
@@ -1678,7 +1665,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "SEX", selected = c("F", "M"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -1689,7 +1676,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x2"
       ),
@@ -1700,14 +1687,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x3"
       )
     )
   )[[1]]
   jk16 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1728,8 +1715,7 @@ testthat::test_that("Single long dataset", {
       ), 120),
       deparse(quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "INVET" & AVISIT ==
-            "SCREENING") %>%
+          dplyr::filter(PARAMCD == "INVET" & AVISIT == "SCREENING") %>%
           dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
           dplyr::rename(x2.AVAL = AVAL) %>%
           tidyr::pivot_longer(cols = "x2.AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
@@ -1778,7 +1764,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "SEX", selected = c("F", "M"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -1789,7 +1775,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x2"
       ),
@@ -1800,14 +1786,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x3"
       )
     )
   )[[1]]
   jk17 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1819,9 +1805,9 @@ testthat::test_that("Single long dataset", {
     list(
       deparse(quote(
         ADRS %>%
-          dplyr::filter(PARAMCD %in% c("BESRSPI", "INVET") &
-            AVISIT %in% c("BASELINE", "SCREENING") &
-            SEX %in% c("F", "M")) %>%
+          dplyr::filter(
+            PARAMCD %in% c("BESRSPI", "INVET") & AVISIT %in% c("BASELINE", "SCREENING") & SEX %in% c("F", "M")
+          ) %>%
           dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
           dplyr::rename(x1.AVAL = AVAL) %>%
           tidyr::pivot_longer(cols = "x1.AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
@@ -1879,14 +1865,14 @@ testthat::test_that("Single long dataset", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE)),
         select = c("AVAL", "STUDYID"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk18 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_identical(
@@ -1923,7 +1909,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "SEX", selected = c("F", "M"), multiple = TRUE)
         ),
         select = c("STUDYID", "PARAMCD", "AVISIT", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -1934,7 +1920,7 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = c("STUDYID", "PARAMCD", "AVISIT"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -1945,14 +1931,14 @@ testthat::test_that("Single long dataset", {
           list(columns = "AVISIT", selected = c("SCREENING", "FOLLOW UP"), multiple = TRUE)
         ),
         select = c("STUDYID", "PARAMCD", "AVISIT", "AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x3"
       )
     )
   )[[1]]
   jk20 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -1964,9 +1950,7 @@ testthat::test_that("Single long dataset", {
     list(
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" &
-            AVISIT %in% c("BASELINE", "SCREENING") &
-            SEX %in% c("F", "M")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("BASELINE", "SCREENING") & SEX %in% c("F", "M")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, PARAMCD, AGE) %>%
           dplyr::rename(x1.PARAMCD = PARAMCD, x1.AGE = AGE)
       ),
@@ -1978,8 +1962,7 @@ testthat::test_that("Single long dataset", {
       ),
       quote(
         ADRS %>%
-          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in%
-            c("SCREENING", "FOLLOW UP")) %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT %in% c("SCREENING", "FOLLOW UP")) %>%
           dplyr::select(STUDYID, USUBJID, AVISIT, PARAMCD, AVAL, AGE) %>%
           dplyr::rename(x3.PARAMCD = PARAMCD, x3.AGE = AGE)
       )
@@ -2015,14 +1998,14 @@ testthat::test_that("Single long dataset", {
           )
         ),
         select = c("AGE", "SEX"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       )
     )
   )[[1]]
   jk21 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -2059,7 +2042,7 @@ testthat::test_that("Single long dataset", {
           )
         ),
         select = c("AGE", "PARAMCD"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2080,7 +2063,7 @@ testthat::test_that("Single long dataset", {
           )
         ),
         select = c("AGE", "AVISIT"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -2101,7 +2084,7 @@ testthat::test_that("Single long dataset", {
           )
         ),
         select = c("COUNTRY", "AVISIT"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -2122,14 +2105,14 @@ testthat::test_that("Single long dataset", {
           )
         ),
         select = c("STUDYID", "AVAL", "AGE", "PARAMCD", "AVISIT"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x4"
       )
     )
   )[[1]]
   jk22 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -2184,7 +2167,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADRS",
         filters = NULL,
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2192,14 +2175,14 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = NULL,
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk1 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -2237,7 +2220,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADRS",
         filters = NULL,
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2295,7 +2278,7 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         select = "AVAL",
         internal_id = "x1"
@@ -2304,14 +2287,14 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = NULL,
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk3 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -2352,7 +2335,7 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2360,14 +2343,14 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk4 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -2410,7 +2393,7 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2418,14 +2401,14 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk5 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -2466,7 +2449,7 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2474,14 +2457,14 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = TRUE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk6 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -2531,7 +2514,7 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -2539,14 +2522,14 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = TRUE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk7 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -2599,7 +2582,7 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "AVISIT", selected = "SCREENING", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -2607,7 +2590,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = TRUE,
         internal_id = "x2"
       ),
@@ -2615,15 +2598,15 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       )
     )
   )[[1]]
   jk8 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADSL", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADSL", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_identical(
@@ -2633,27 +2616,36 @@ testthat::test_that("Multiple long datasets", {
       deparse(get_dplyr_call(merged_selectors8, 3L, jk8), width.cutoff = 120)
     ),
     list(
-      deparse(quote(ADRS %>%
-        dplyr::filter(PARAMCD == "BESRSPI" & AVISIT == "SCREENING") %>%
-        dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
-        dplyr::rename(x1.AVAL = AVAL) %>%
-        tidyr::pivot_longer(cols = "x1.AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
-        tidyr::unite(KEY, MEASURE, PARAMCD, AVISIT) %>%
-        tidyr::pivot_wider(names_from = "KEY", values_from = "VALUE")), width.cutoff = 120),
-      deparse(quote(
-        ADTTE %>%
-          dplyr::filter(PARAMCD %in% c("EFS", "PFS")) %>%
-          dplyr::select(STUDYID, USUBJID, PARAMCD, AVAL, AGE) %>%
-          dplyr::rename(x2.AVAL = AVAL, x2.AGE = AGE) %>%
-          tidyr::pivot_longer(cols = c("x2.AVAL", "x2.AGE"), names_to = "MEASURE", values_to = "VALUE") %>%
-          tidyr::unite(KEY, MEASURE, PARAMCD) %>%
-          tidyr::pivot_wider(names_from = "KEY", values_from = "VALUE")
-      ), width.cutoff = 120),
-      deparse(quote(
-        ADSL %>%
-          dplyr::select(STUDYID, USUBJID, AGE) %>%
-          dplyr::rename(x3.AGE = AGE)
-      ), width.cutoff = 120)
+      deparse(
+        quote(ADRS %>%
+          dplyr::filter(PARAMCD == "BESRSPI" & AVISIT == "SCREENING") %>%
+          dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
+          dplyr::rename(x1.AVAL = AVAL) %>%
+          tidyr::pivot_longer(cols = "x1.AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
+          tidyr::unite(KEY, MEASURE, PARAMCD, AVISIT) %>%
+          tidyr::pivot_wider(names_from = "KEY", values_from = "VALUE")),
+        width.cutoff = 120
+      ),
+      deparse(
+        quote(
+          ADTTE %>%
+            dplyr::filter(PARAMCD %in% c("EFS", "PFS")) %>%
+            dplyr::select(STUDYID, USUBJID, PARAMCD, AVAL, AGE) %>%
+            dplyr::rename(x2.AVAL = AVAL, x2.AGE = AGE) %>%
+            tidyr::pivot_longer(cols = c("x2.AVAL", "x2.AGE"), names_to = "MEASURE", values_to = "VALUE") %>%
+            tidyr::unite(KEY, MEASURE, PARAMCD) %>%
+            tidyr::pivot_wider(names_from = "KEY", values_from = "VALUE")
+        ),
+        width.cutoff = 120
+      ),
+      deparse(
+        quote(
+          ADSL %>%
+            dplyr::select(STUDYID, USUBJID, AGE) %>%
+            dplyr::rename(x3.AGE = AGE)
+        ),
+        width.cutoff = 120
+      )
     )
   )
 
@@ -2687,7 +2679,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE)),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2695,7 +2687,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = TRUE,
         internal_id = "x2"
       ),
@@ -2703,7 +2695,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -2714,16 +2706,16 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "AVISIT", selected = c("SCREENING", "BASELINE"), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x4"
       )
     )
   )[[1]]
   jk9 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -2794,7 +2786,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE)),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2802,7 +2794,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = TRUE,
         internal_id = "x2"
       ),
@@ -2810,7 +2802,7 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADSL",
         filters = NULL,
         select = "AGE",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "x3"
       ),
@@ -2818,16 +2810,16 @@ testthat::test_that("Multiple long datasets", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "BESRSPI", multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x4"
       )
     )
   )[[1]]
   jk10 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
 
@@ -2881,7 +2873,7 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "SEX", selected = "F", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2892,14 +2884,14 @@ testthat::test_that("Multiple long datasets", {
           list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk11 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
 
@@ -2963,7 +2955,7 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           )
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -2974,15 +2966,15 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE, drop_keys = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk12 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS")),
-    teal.data::join_key("ADTTE", "ADRS", teal.data::get_cdisc_keys("ADTTE")),
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")),
+    teal.data::join_key("ADTTE", "ADRS", c("STUDYID", "USUBJID", "PARAMCD")),
     teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID", "PARAMCD")) # non-stadard keys set for example purpose
   )
 
@@ -3033,7 +3025,7 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           list(columns = c("PARAMCD", "AVISIT"), selected = list(c("BESRSPI", "SCREENING")), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -3041,14 +3033,14 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
         dataname = "ADTTE",
         filters = list(list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = TRUE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk13 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
 
@@ -3108,7 +3100,7 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           list(columns = "SEX", selected = "F", multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -3119,7 +3111,7 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -3129,15 +3121,15 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           list(columns = c("PARAMCD", "AVISIT"), selected = list(c("OVRINV", "FOLLOW UP")), multiple = TRUE)
         ),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x3"
       )
     )
   )[[1]]
   jk14 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -3188,7 +3180,7 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           multiple = TRUE
         )),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x1"
       ),
@@ -3199,7 +3191,7 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       ),
@@ -3211,15 +3203,15 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           multiple = TRUE
         )),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "x3"
       )
     )
   )[[1]]
   jk15 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   testthat::expect_equal(
@@ -3273,7 +3265,7 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           multiple = TRUE
         )),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "x1"
       ),
@@ -3284,14 +3276,14 @@ testthat::test_that("Multiple long - combined/concatenated filters", {
           list(columns = "PARAMCD", selected = c("EFS", "PFS"), multiple = TRUE)
         ),
         select = c("AVAL", "AGE"),
-        keys = teal.data::get_cdisc_keys("ADTTE"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD"),
         reshape = FALSE,
         internal_id = "x2"
       )
     )
   )[[1]]
   jk16 <- teal.data::join_keys(
-    teal.data::join_key("ADRS", "ADTTE", teal.data::get_cdisc_keys("ADSL"))
+    teal.data::join_key("ADRS", "ADTTE", c("STUDYID", "USUBJID"))
   )
 
   testthat::expect_equal(
@@ -3391,3 +3383,4 @@ testthat::test_that("Universal example", {
     )
   )
 })
+# nolint end
diff --git a/tests/testthat/test-filter_spec.R b/tests/testthat/test-filter_spec.R
index bd38e1e7..a5b53f05 100644
--- a/tests/testthat/test-filter_spec.R
+++ b/tests/testthat/test-filter_spec.R
@@ -1,3 +1,9 @@
+ADSL <- teal.transform::rADSL # nolint
+ADTTE <- teal.transform::rADTTE # nolint
+data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE), ADLB = reactive(ADLB))
+join_keys <- teal.data::default_cdisc_join_keys[c("ADSL", "ADTTE", "ADLB")]
+primary_keys_list <- lapply(join_keys, function(x) x[[1]])
+
 choices <- c("val1", "val2", "val3")
 choices_d <- c("val1", "val1", "val2", "val3")
 choices_f <- as.factor(choices)
@@ -173,7 +179,7 @@ testthat::test_that("delayed filter_spec", {
   expect_equal(names(expected_spec), names(delayed))
 
   data_list <- list(ADSL = reactive(ADSL))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"))
 
   result_spec <- isolate(resolve(delayed, data_list, key_list))
   testthat::expect_identical(expected_spec, isolate(resolve(delayed, data_list, key_list)))
@@ -288,13 +294,6 @@ testthat::test_that("delayed filter_spec works", {
   testthat::expect_identical(expected_spec, isolate(resolve(delayed, data_list, key_list)))
 })
 
-
-ADSL <- teal.transform::rADSL # nolint
-ADTTE <- teal.transform::rADTTE # nolint
-
-data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
-key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
-
 vc_hard <- variable_choices("ADSL", subset = c("STUDYID", "USUBJID"))
 vc_hard_exp <- structure(
   list(data = "ADSL", subset = c("STUDYID", "USUBJID"), key = NULL),
@@ -355,7 +354,7 @@ testthat::test_that("delayed version of filter_spec", {
     )
   )
 
-  res_obj <- isolate(resolve(obj, datasets = data_list, key_list))
+  res_obj <- isolate(resolve(obj, datasets = data_list, key = primary_keys_list))
   exp_obj <- filter_spec(
     vars = variable_choices(ADSL, subset = "ARMCD"),
     choices = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B")),
@@ -427,7 +426,7 @@ testthat::test_that("delayed version of filter_spec", {
     )
   )
 
-  res_obj <- isolate(resolve(obj, datasets = data_list, key_list))
+  res_obj <- isolate(resolve(obj, datasets = data_list, key = primary_keys_list))
 
   # comparison not implemented, must be done individually
   testthat::expect_equal(res_obj$choices, exp_obj$choices)
@@ -448,13 +447,6 @@ testthat::test_that("all_choices passed to selected identical to all choices", {
 
 # With resolve_delayed
 testthat::test_that("delayed filter_spec - resolve_delayed", {
-  set.seed(1)
-  ADSL <- data.frame( # nolint
-    USUBJID = letters[1:10],
-    SEX = sample(c("F", "M", "U"), 10, replace = TRUE),
-    stringsAsFactors = FALSE
-  )
-
   expected_spec <- filter_spec(
     vars = variable_choices(ADSL, "SEX"),
     sep = "-",
@@ -473,15 +465,8 @@ testthat::test_that("delayed filter_spec - resolve_delayed", {
   )
 
   testthat::expect_equal(names(expected_spec), names(delayed))
-
-  ds <- teal.slice::init_filtered_data(
-    list(ADSL = list(dataset = ADSL)),
-    join_keys = teal.data::join_keys(
-      teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
-    )
-  )
-  result_spec <- isolate(resolve_delayed(delayed, ds))
-  testthat::expect_identical(expected_spec, isolate(resolve_delayed(delayed, ds)))
+  result_spec <- isolate(resolve_delayed(delayed, datasets = data_list, keys = primary_keys_list))
+  testthat::expect_identical(expected_spec, result_spec)
 })
 
 
@@ -497,13 +482,6 @@ testthat::test_that(
 )
 
 testthat::test_that("delayed filter_spec works - resolve_delayed", {
-  set.seed(1)
-  ADSL <- data.frame( # nolint
-    USUBJID = letters[1:10],
-    SEX = sample(c("F", "M", "U"), 10, replace = TRUE),
-    stringsAsFactors = FALSE
-  )
-
   expected_spec <- filter_spec_internal(
     vars_choices = variable_choices(ADSL),
     vars_selected = "SEX"
@@ -515,26 +493,8 @@ testthat::test_that("delayed filter_spec works - resolve_delayed", {
     vars_selected = "SEX"
   )
 
-  testthat::expect_equal(
-    class(delayed),
-    c(
-      "delayed_filter_spec",
-      "filter_spec",
-      "delayed_data"
-    )
-  )
-
-  testthat::expect_equal(names(expected_spec), names(delayed))
-  ds <- teal.slice::init_filtered_data(
-    list(ADSL = list(dataset = ADSL))
-  )
-
-  delayed$dataname <- "ADSL"
-  expected_spec$dataname <- "ADSL"
-  testthat::expect_identical(
-    expected_spec,
-    isolate(resolve_delayed(delayed, ds))
-  )
+  resolved <- isolate(resolve_delayed(delayed, datasets = data_list))
+  testthat::expect_identical(expected_spec, resolved)
 
   expected_spec <- data_extract_spec(
     dataname = "ADSL",
@@ -552,17 +512,12 @@ testthat::test_that("delayed filter_spec works - resolve_delayed", {
     )
   )
 
-  testthat::expect_identical(expected_spec, isolate(resolve_delayed(delayed, ds)))
+  testthat::expect_identical(
+    expected_spec,
+    isolate(resolve_delayed(delayed, datasets = data_list))
+  )
 })
 
-ADSL <- teal.transform::rADSL # nolint
-ADTTE <- teal.transform::rADTTE # nolint
-data <- teal.data::cdisc_data(
-  teal.data::cdisc_dataset("ADSL", ADSL),
-  teal.data::cdisc_dataset("ADTTE", ADTTE)
-)
-ds <- teal.slice::init_filtered_data(data)
-
 testthat::test_that("delayed version of filter_spec - resolve_delayed", {
   # hard-coded vars & choices & selected
   obj <- filter_spec(
@@ -599,7 +554,7 @@ testthat::test_that("delayed version of filter_spec - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   exp_obj <- filter_spec(
     vars = variable_choices(ADSL, subset = "ARMCD"),
     choices = value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B")),
@@ -671,7 +626,7 @@ testthat::test_that("delayed version of filter_spec - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
 
   # comparison not implemented, must be done individually
   testthat::expect_equal(res_obj$choices, exp_obj$choices)
diff --git a/tests/testthat/test-format_data_extract.R b/tests/testthat/test-format_data_extract.R
index 96e55b97..22d9e7d9 100644
--- a/tests/testthat/test-format_data_extract.R
+++ b/tests/testthat/test-format_data_extract.R
@@ -50,10 +50,3 @@ testthat::test_that("format_data_extract integrates with data_extract_srv", {
     }
   )
 })
-
-testthat::test_that("format_data_extract integrates with data_extract_srv and the filtered data object", {
-  skip_if_too_deep(4)
-  shinytest::expect_pass(
-    shinytest::testApp(testthat::test_path("shinytest/format_data_extract"), compareImages = FALSE)
-  )
-})
diff --git a/tests/testthat/test-get_dplyr_call.R b/tests/testthat/test-get_dplyr_call.R
index 61386ada..adb10646 100644
--- a/tests/testthat/test-get_dplyr_call.R
+++ b/tests/testthat/test-get_dplyr_call.R
@@ -57,7 +57,7 @@ testthat::test_that("get_rename_call", {
       dataname = "ADSL",
       filters = NULL,
       select = utils::head(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test1"
     ),
@@ -65,7 +65,7 @@ testthat::test_that("get_rename_call", {
       dataname = "ADSL",
       filters = NULL,
       select = letters,
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test2"
     ),
@@ -73,7 +73,7 @@ testthat::test_that("get_rename_call", {
       dataname = "ADSL",
       filters = NULL,
       select = utils::tail(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test3"
     ),
@@ -81,7 +81,7 @@ testthat::test_that("get_rename_call", {
       dataname = "ADSL",
       filters = NULL,
       select = c("aa", "bb"),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test4"
     )
@@ -112,7 +112,7 @@ testthat::test_that("get_reshape_call", {
         multiple = FALSE
       )),
       select = "AVAL",
-      keys = teal.data::get_cdisc_keys("ADLB"),
+      keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
       reshape = TRUE,
       internal_id = "test"
     )
@@ -136,7 +136,7 @@ testthat::test_that("get_reshape_call", {
         multiple = TRUE
       )),
       select = "AVAL",
-      keys = teal.data::get_cdisc_keys("ADLB"),
+      keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
       reshape = TRUE,
       internal_id = "test"
     )
@@ -160,11 +160,11 @@ testthat::test_that("get_dplyr_call - single filter and single select", {
         dataname = "ADSL",
         filters = NULL,
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(ADSL %>% dplyr::select(STUDYID, USUBJID))
   )
@@ -176,11 +176,11 @@ testthat::test_that("get_dplyr_call - single filter and single select", {
         dataname = "ADSL",
         filters = list(list(columns = "SEX", selected = list("F", "M"))),
         select = character(0),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADSL %>%
@@ -196,11 +196,11 @@ testthat::test_that("get_dplyr_call - single filter and single select", {
         dataname = "ADSL",
         filters = list(list(columns = "SEX", selected = list("F", "M"))),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADSL %>%
@@ -216,11 +216,11 @@ testthat::test_that("get_dplyr_call - single filter and single select", {
         dataname = "ADSL",
         filters = list(list(columns = "SEX", selected = list("F"))),
         select = c("AVAL", "SEX"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADSL %>%
@@ -237,11 +237,11 @@ testthat::test_that("get_dplyr_call - single filter and single select", {
         dataname = "ADSL",
         filters = list(list(columns = "SEX", selected = list("F"), drop_keys = TRUE)),
         select = c("AVAL", "SEX"),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADSL %>%
@@ -257,11 +257,11 @@ testthat::test_that("get_dplyr_call - single filter and single select", {
         dataname = "ADSL",
         filters = list(list(columns = "STUDYID", selected = list("ANY"), drop_keys = TRUE)),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADSL %>%
@@ -277,11 +277,11 @@ testthat::test_that("get_dplyr_call - single filter and single select", {
         dataname = "ADSL",
         filters = list(list(columns = "STUDYID", selected = list("ANY"), drop_keys = FALSE)),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADSL %>%
@@ -300,7 +300,7 @@ testthat::test_that("get_dplyr_call - multiple filter(s) or multiple select(s)",
           dataname = "ADSL",
           filters = NULL,
           select = c("COL_1", "COL_2"),
-          keys = teal.data::get_cdisc_keys("ADSL"),
+          keys = c("STUDYID", "USUBJID"),
           reshape = FALSE,
           internal_id = "test1"
         ),
@@ -308,13 +308,13 @@ testthat::test_that("get_dplyr_call - multiple filter(s) or multiple select(s)",
           dataname = "ADSL",
           filters = NULL,
           select = c("COL_2", "COL_3"),
-          keys = teal.data::get_cdisc_keys("ADSL"),
+          keys = c("STUDYID", "USUBJID"),
           reshape = FALSE,
           internal_id = "test2"
         )
       ),
       idx = 1L,
-      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADSL %>%
@@ -326,26 +326,32 @@ testthat::test_that("get_dplyr_call - multiple filter(s) or multiple select(s)",
   # multiple variable filters, single selection, reshape by all keys even if filtered out (to keep proper label)
   testthat::expect_equal(
     get_dplyr_call(
-      list(list(
-        dataname = "ADLB",
-        filters = list(list(
-          columns = c("PARAMCD", "AVISIT"),
-          selected = list(c("ALBCV", "SCREENING"), c("ALBCV", "BASELINE")),
-          multiple = TRUE
-        )),
-        select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADLB"),
-        reshape = TRUE,
-        internal_id = "test1"
-      )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADLB", "ADLB", teal.data::get_cdisc_keys("ADSL")))
+      list(
+        list(
+          dataname = "ADLB",
+          filters = list(
+            list(
+              columns = c("PARAMCD", "AVISIT"),
+              selected = list(c("ALBCV", "SCREENING"), c("ALBCV", "BASELINE")),
+              multiple = TRUE
+            )
+          ),
+          select = "AVAL",
+          keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
+          reshape = TRUE,
+          internal_id = "test1"
+        )
+      ),
+      join_keys = teal.data::join_keys(teal.data::join_key("ADLB", "ADLB", c("STUDYID", "USUBJID")))
     ),
-    quote(ADLB %>%
-      dplyr::filter((PARAMCD == "ALBCV" & AVISIT == "SCREENING") | (PARAMCD == "ALBCV" & AVISIT == "BASELINE")) %>%
-      dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
-      tidyr::pivot_longer(cols = "AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
-      tidyr::unite(KEY, MEASURE, PARAMCD, AVISIT) %>%
-      tidyr::pivot_wider(names_from = "KEY", values_from = "VALUE"))
+    quote(
+      ADLB %>%
+        dplyr::filter((PARAMCD == "ALBCV" & AVISIT == "SCREENING") | (PARAMCD == "ALBCV" & AVISIT == "BASELINE")) %>%
+        dplyr::select(STUDYID, USUBJID, PARAMCD, AVISIT, AVAL) %>%
+        tidyr::pivot_longer(cols = "AVAL", names_to = "MEASURE", values_to = "VALUE") %>%
+        tidyr::unite(KEY, MEASURE, PARAMCD, AVISIT) %>%
+        tidyr::pivot_wider(names_from = "KEY", values_from = "VALUE")
+    )
   )
 
   # multiple variable filters, single select - one key filtered out and dropped from select
@@ -359,11 +365,11 @@ testthat::test_that("get_dplyr_call - multiple filter(s) or multiple select(s)",
           multiple = TRUE
         )),
         select = "AVAL",
-        keys = teal.data::get_cdisc_keys("ADLB"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       )),
-      join_keys = teal.data::join_keys(teal.data::join_key("ADLB", "ADLB", teal.data::get_cdisc_keys("ADSL")))
+      join_keys = teal.data::join_keys(teal.data::join_key("ADLB", "ADLB", c("STUDYID", "USUBJID")))
     ),
     quote(
       ADLB %>%
diff --git a/tests/testthat/test-get_filter_call-datasets.R b/tests/testthat/test-get_filter_call-datasets.R
index 4148afd5..fbdc6709 100644
--- a/tests/testthat/test-get_filter_call-datasets.R
+++ b/tests/testthat/test-get_filter_call-datasets.R
@@ -91,8 +91,10 @@ testthat::test_that("get_filter_call - data - trunc POSIX and two columns", {
       ))
     ), dataname = "ADAMSET", data = data_list)),
     quote(
-      dplyr::filter((trunc(TRTSDTM) == "2020-03-08 06:28:11" & AGE == "33") |
-        (trunc(TRTSDTM) == "2020-03-09 06:28:11" & is.na(AGE)))
+      dplyr::filter(
+        (trunc(TRTSDTM) == "2020-03-08 06:28:11" & AGE == "33") |
+          (trunc(TRTSDTM) == "2020-03-09 06:28:11" & is.na(AGE))
+      )
     )
   )
 })
@@ -120,8 +122,7 @@ testthat::test_that("get_filter_call - data - three columns", {
       ))
     ), dataname = "ADAMSET", data = data_list)),
     quote(
-      dplyr::filter((SEX == "F" & AGE == "33" & is.na(DCSREAS)) | (SEX ==
-        "M" & is.na(AGE) & is.na(DCSREAS)))
+      dplyr::filter((SEX == "F" & AGE == "33" & is.na(DCSREAS)) | (SEX == "M" & is.na(AGE) & is.na(DCSREAS)))
     )
   )
 })
diff --git a/tests/testthat/test-merge_expression_module.R b/tests/testthat/test-merge_expression_module.R
index 09fabc0f..ef7d89e9 100644
--- a/tests/testthat/test-merge_expression_module.R
+++ b/tests/testthat/test-merge_expression_module.R
@@ -1,6 +1,6 @@
-adsl <- as.data.frame(as.list(stats::setNames(nm = c(teal.data::get_cdisc_keys("ADSL"), "AGE"))))
+adsl <- as.data.frame(as.list(stats::setNames(nm = c(c("STUDYID", "USUBJID"), "AGE"))))
 adlb <- as.data.frame(
-  as.list(stats::setNames(nm = c(teal.data::get_cdisc_keys("ADLB"), "AVAL", "CHG", "CHG2", "ABLFL")))
+  as.list(stats::setNames(nm = c(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "AVAL", "CHG", "CHG2", "ABLFL")))
 )
 
 data_list <- list(ADSL = reactive(adsl), ADLB = reactive(adlb))
diff --git a/tests/testthat/test-merge_expression_srv.R b/tests/testthat/test-merge_expression_srv.R
index ceff634f..69ea5501 100644
--- a/tests/testthat/test-merge_expression_srv.R
+++ b/tests/testthat/test-merge_expression_srv.R
@@ -1,19 +1,12 @@
-adsl_df <- as.data.frame(as.list(stats::setNames(nm = c(teal.data::get_cdisc_keys("ADSL"), "AGE"))))
-adlb_df <- as.data.frame(
-  as.list(stats::setNames(nm = c(teal.data::get_cdisc_keys("ADLB"), "AVAL", "CHG", "CHG2", "ABLFL")))
+adsl <- as.data.frame(as.list(stats::setNames(nm = c(c("STUDYID", "USUBJID"), "AGE"))))
+adlb <- as.data.frame(
+  as.list(stats::setNames(nm = c(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "AVAL", "CHG", "CHG2", "ABLFL")))
 )
 
-adsl <- teal.data::cdisc_dataset("ADSL", adsl_df)
-adlb <- teal.data::cdisc_dataset("ADLB", adlb_df)
+data_list <- list(ADSL = reactive(adsl), ADLB = reactive(adlb))
+data_list_nr <- list(ADSL = adsl, ADLB = adlb)
 
-data_list <- list(ADSL = reactive(adsl_df), ADLB = reactive(adlb_df))
-data_list_nr <- list(ADSL = adsl_df, ADLB = adlb_df)
-
-join_keys <- teal.data::join_keys(
-  teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
-  teal.data::join_key("ADSL", "ADLB", c("STUDYID", "USUBJID")),
-  teal.data::join_key("ADLB", "ADLB", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
-)
+join_keys <- teal.data::default_cdisc_join_keys[c("ADSL", "ADLB")]
 
 adsl_data_extract_srv_output <-
   list(
@@ -233,11 +226,7 @@ testthat::test_that("merge_expression_srv returns merge expression when passing
 
 testthat::test_that("merge_expression_srv throws error if datasets is not a named list", {
   testthat::expect_error(
-    shiny::testServer(
-      merge_expression_srv,
-      args = list(selector_list = selector_list, datasets = list(adsl, adlb), join_keys = join_keys),
-      expr = NULL
-    ),
+    merge_expression_srv(selector_list = selector_list, datasets = list(adsl, adlb), join_keys = join_keys),
     "Assertion on 'datasets' failed: Must have names."
   )
 })
diff --git a/tests/testthat/test-merge_utils.R b/tests/testthat/test-merge_utils.R
index fcd382f4..1c12aa74 100644
--- a/tests/testthat/test-merge_utils.R
+++ b/tests/testthat/test-merge_utils.R
@@ -3,7 +3,7 @@ testthat::test_that("merge_selectors makes no changes when single selector is pr
     dataname = "ADSL",
     filters = NULL,
     select = utils::head(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   )
@@ -20,7 +20,7 @@ testthat::test_that(
       dataname = "ADSL",
       filters = NULL,
       select = utils::head(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test1"
     )
@@ -28,7 +28,7 @@ testthat::test_that(
       dataname = "ADSL",
       filters = NULL,
       select = utils::tail(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test2"
     )
@@ -41,7 +41,7 @@ testthat::test_that(
             dataname = "ADSL",
             filters = NULL,
             select = c(utils::head(letters, 3), utils::tail(letters, 3)),
-            keys = teal.data::get_cdisc_keys("ADSL"),
+            keys = c("STUDYID", "USUBJID"),
             reshape = FALSE,
             internal_id = "test1"
           )
@@ -57,7 +57,7 @@ testthat::test_that("merge selectors combines two selectorsdespite duplicated in
     dataname = "ADSL",
     filters = NULL,
     select = utils::head(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   )
@@ -65,7 +65,7 @@ testthat::test_that("merge selectors combines two selectorsdespite duplicated in
     dataname = "ADSL",
     filters = NULL,
     select = utils::tail(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   )
@@ -78,7 +78,7 @@ testthat::test_that("merge selectors combines two selectorsdespite duplicated in
           dataname = "ADSL",
           filters = NULL,
           select = c(utils::head(letters, 3), utils::tail(letters, 3)),
-          keys = teal.data::get_cdisc_keys("ADSL"),
+          keys = c("STUDYID", "USUBJID"),
           reshape = FALSE,
           internal_id = "test1"
         )
@@ -93,7 +93,7 @@ testthat::test_that("Two pairs of selectors combined into two selectors", {
     dataname = "ADSL",
     filters = NULL,
     select = utils::head(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   )
@@ -101,7 +101,7 @@ testthat::test_that("Two pairs of selectors combined into two selectors", {
     dataname = "ADLB",
     filters = NULL,
     select = utils::head(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test2"
   )
@@ -109,7 +109,7 @@ testthat::test_that("Two pairs of selectors combined into two selectors", {
     dataname = "ADSL",
     filters = NULL,
     select = tail(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test3"
   )
@@ -117,7 +117,7 @@ testthat::test_that("Two pairs of selectors combined into two selectors", {
     dataname = "ADLB",
     filters = NULL,
     select = utils::tail(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test4"
   )
@@ -142,7 +142,7 @@ testthat::test_that("merge does not merge when reshape differs", {
     dataname = "ADSL",
     filters = NULL,
     select = utils::head(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test1"
   )
@@ -150,7 +150,7 @@ testthat::test_that("merge does not merge when reshape differs", {
     dataname = "ADSL",
     filters = NULL,
     select = utils::tail(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = TRUE,
     internal_id = "test2"
   )
@@ -169,7 +169,7 @@ testthat::test_that("merge does not merge when filters differs", {
     dataname = "ADSL",
     filters = NULL,
     select = utils::head(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = TRUE,
     internal_id = "test1"
   )
@@ -177,7 +177,7 @@ testthat::test_that("merge does not merge when filters differs", {
     dataname = "ADSL",
     filters = list(list(columns = "a", selected = list("1", "2"))),
     select = utils::tail(letters, 3),
-    keys = teal.data::get_cdisc_keys("ADSL"),
+    keys = c("STUDYID", "USUBJID"),
     reshape = FALSE,
     internal_id = "test2"
   )
@@ -198,7 +198,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADSL",
         filters = NULL,
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -206,13 +206,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADSL",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADSL"),
+        keys = c("STUDYID", "USUBJID"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADSL")
+      c("STUDYID", "USUBJID")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADSL"))
+    rlang::set_names(c("STUDYID", "USUBJID"))
   )
 
   # this is useful when merging two subsets of long datasets -> value columns next to each other
@@ -223,7 +223,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = FALSE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -231,13 +231,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADRS"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
   # ignore "to" selector's filter
   testthat::expect_identical(
@@ -246,7 +246,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -254,13 +254,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = FALSE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADRS"))
+    rlang::set_names(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
   # subtract from keys single filter on "from" selector
   testthat::expect_identical(
@@ -269,7 +269,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = FALSE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -277,13 +277,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = FALSE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADRS"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
   # subtract if multiple filter and single selection
   testthat::expect_identical(
@@ -292,7 +292,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = TRUE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -300,13 +300,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = FALSE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADRS"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
   # ignore if multiple filter with multiple selection
   testthat::expect_identical(
@@ -315,7 +315,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = c("OS", "PFS"), multiple = TRUE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -323,13 +323,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = c("OS", "PFS"), multiple = FALSE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADRS"))
+    rlang::set_names(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
   # subtract only keys filter cols
   testthat::expect_identical(
@@ -342,7 +342,7 @@ testthat::test_that("get_merge_key_pair works", {
           list(columns = "RACE", selected = "ASIAN", multiple = FALSE)
         ),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -350,13 +350,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADRS"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
 
   # do not subtract from primary key if not reshape and multiple filter column
@@ -366,7 +366,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = c("OS", "PFS"), multiple = TRUE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -374,13 +374,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADRS"))
+    rlang::set_names(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
   testthat::expect_identical(
     get_merge_key_pair(
@@ -388,7 +388,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -396,13 +396,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = c("OS", "PFS"), multiple = TRUE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADRS"))
+    rlang::set_names(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
   testthat::expect_identical(
     get_merge_key_pair(
@@ -410,7 +410,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = c("OS", "PFS"), multiple = TRUE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -418,13 +418,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = c("OS", "PFS"), multiple = TRUE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADRS"))
+    rlang::set_names(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   ## reshape cases
@@ -439,7 +439,7 @@ testthat::test_that("get_merge_key_pair works", {
           list(columns = "RACE", selected = "ASIAN", multiple = TRUE)
         ),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -447,13 +447,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADRS"))
+    rlang::set_names(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
 
   ## reshape cases
@@ -464,7 +464,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = TRUE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test1"
       ),
@@ -472,13 +472,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADRS"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
   # no changes because only "from" filter is used
   testthat::expect_identical(
@@ -487,7 +487,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test1"
       ),
@@ -495,13 +495,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = TRUE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(teal.data::get_cdisc_keys("ADRS"))
+    rlang::set_names(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
   # subtract by filter column on "from" selector
   testthat::expect_identical(
@@ -510,7 +510,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = TRUE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test1"
       ),
@@ -518,13 +518,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = list(list(columns = "PARAMCD", selected = "OS", multiple = TRUE)),
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADRS"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
   # subtract by filter key column on "from" selector
   testthat::expect_identical(
@@ -537,7 +537,7 @@ testthat::test_that("get_merge_key_pair works", {
           list(columns = "RACE", selected = "ASIAN", multiple = TRUE)
         ),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test1"
       ),
@@ -545,13 +545,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADRS",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADRS"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = TRUE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADRS")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADRS"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
 
   testthat::expect_identical(
@@ -560,7 +560,7 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADLB",
         filters = list(list(columns = "PARAMCD", selected = "ALT", multiple = FALSE)),
         select = utils::head(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADLB"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test1"
       ),
@@ -568,13 +568,13 @@ testthat::test_that("get_merge_key_pair works", {
         dataname = "ADLB",
         filters = NULL,
         select = utils::tail(letters, 3),
-        keys = teal.data::get_cdisc_keys("ADLB"),
+        keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
         reshape = FALSE,
         internal_id = "test2"
       ),
-      teal.data::get_cdisc_keys("ADLB")
+      c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
     ),
-    rlang::set_names(setdiff(teal.data::get_cdisc_keys("ADLB"), "PARAMCD"))
+    rlang::set_names(setdiff(c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"), "PARAMCD"))
   )
 })
 
@@ -585,7 +585,7 @@ testthat::test_that("get_merge_call", {
       dataname = "ADSL",
       filters = NULL,
       select = utils::head(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test1"
     )
@@ -600,7 +600,7 @@ testthat::test_that("get_merge_call", {
       dataname = "ADSL",
       filters = NULL,
       select = utils::head(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test1"
     ),
@@ -608,12 +608,12 @@ testthat::test_that("get_merge_call", {
       dataname = "ADSL",
       filters = NULL,
       select = utils::tail(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test2"
     )
   )
-  jk <- teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")))
+  jk <- teal.data::join_keys(teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")))
   testthat::expect_identical(
     get_merge_call(x, jk),
     list(
@@ -627,7 +627,7 @@ testthat::test_that("get_merge_call", {
       dataname = "ADRS",
       filters = NULL,
       select = utils::head(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADRS"),
+      keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
       reshape = FALSE,
       internal_id = "test1"
     ),
@@ -635,12 +635,12 @@ testthat::test_that("get_merge_call", {
       dataname = "ADRS",
       filters = NULL,
       select = utils::tail(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADRS"),
+      keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
       reshape = FALSE,
       internal_id = "test2"
     )
   )
-  jk <- teal.data::join_keys(teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS")))
+  jk <- teal.data::join_keys(teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")))
   testthat::expect_identical(
     get_merge_call(x, jk),
     list(
@@ -656,7 +656,7 @@ testthat::test_that("get_merge_call", {
       dataname = "ADSL",
       filters = NULL,
       select = utils::head(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADSL"),
+      keys = c("STUDYID", "USUBJID"),
       reshape = FALSE,
       internal_id = "test1"
     ),
@@ -664,7 +664,7 @@ testthat::test_that("get_merge_call", {
       dataname = "ADRS",
       filters = NULL,
       select = utils::head(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADRS"),
+      keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
       reshape = FALSE,
       internal_id = "test2"
     ),
@@ -672,15 +672,15 @@ testthat::test_that("get_merge_call", {
       dataname = "ADRS",
       filters = NULL,
       select = utils::tail(letters, 3),
-      keys = teal.data::get_cdisc_keys("ADRS"),
+      keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"),
       reshape = FALSE,
       internal_id = "test3"
     )
   )
   jk <- teal.data::join_keys(
-    teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADSL", "ADRS", teal.data::get_cdisc_keys("ADSL")),
-    teal.data::join_key("ADRS", "ADRS", teal.data::get_cdisc_keys("ADRS"))
+    teal.data::join_key("ADSL", "ADSL", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADSL", "ADRS", c("STUDYID", "USUBJID")),
+    teal.data::join_key("ADRS", "ADRS", c("STUDYID", "USUBJID", "PARAMCD", "AVISIT"))
   )
   testthat::expect_identical(
     get_merge_call(x, jk),
diff --git a/tests/testthat/test-resolve.R b/tests/testthat/test-resolve.R
index 7620638a..296c3eb4 100644
--- a/tests/testthat/test-resolve.R
+++ b/tests/testthat/test-resolve.R
@@ -73,36 +73,15 @@ testthat::test_that("resolve_delayed_expr works correctly", {
 
 testthat::test_that("resolve.list works correctly", {
   data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
   ddl_resolved <- isolate(resolve(arm_ref_comp_ddl, data_list, key_list))
   testthat::expect_identical(arm_ref_comp, ddl_resolved)
 })
 
-
-testthat::test_that("resolving delayed choices removes selected not in choices and give a log output", {
-  iris_dataset <- teal.data::dataset("IRIS", head(iris))
-
-  c_s <- choices_selected(
-    choices = variable_choices("IRIS", c("Sepal.Length", "Sepal.Width")),
-    selected = variable_choices("IRIS", c("Petal.Length", "Sepal.Width"))
-  )
-
-  output <- testthat::capture_output({
-    data_list <- list(IRIS = reactive(head(iris)))
-    key_list <- list(IRIS = character(0))
-    resolved_cs <- isolate(resolve(c_s, data_list, key_list))
-  })
-
-  testthat::expect_equal(resolved_cs$selected, stats::setNames("Sepal.Width", "Sepal.Width: Sepal.Width"))
-  testthat::expect_true(
-    grepl("Removing Petal.Length from 'selected' as not in 'choices' when resolving delayed choices_selected", output)
-  )
-})
-
 testthat::test_that("resolve throws error with non-reactive data.frames or unnamed list as input to datasets", {
   data_list <- list(ADSL = ADSL, ADTTE = ADTTE)
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
   testthat::expect_error(
     isolate(resolve(arm_ref_comp_ddl, data_list, key_list)),
@@ -119,14 +98,14 @@ testthat::test_that("resolve throws error with non-reactive data.frames or unnam
 
 testthat::test_that("resolve throws error with unnamed list or wrong names as input to keys", {
   data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
-  key_list <- list(teal.data::get_cdisc_keys("ADSL"), teal.data::get_cdisc_keys("ADTTE"))
+  key_list <- list(c("STUDYID", "USUBJID"), c("STUDYID", "USUBJID", "PARAMCD"))
 
   testthat::expect_error(
     isolate(resolve(arm_ref_comp_ddl, data_list, key_list)),
     "Assertion on 'keys' failed: Must have names."
   )
 
-  key_list <- list(AA = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
+  key_list <- list(AA = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
   testthat::expect_error(
     isolate(resolve(arm_ref_comp_ddl, data_list, key_list)),
@@ -137,7 +116,7 @@ testthat::test_that("resolve throws error with unnamed list or wrong names as in
 
 testthat::test_that("resolve throws error with missing arguments", {
   data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
   testthat::expect_error(
     isolate(resolve(arm_ref_comp_ddl, data_list)),
diff --git a/tests/testthat/test-resolve_delayed.R b/tests/testthat/test-resolve_delayed.R
index 30bc8223..3e8ff93c 100644
--- a/tests/testthat/test-resolve_delayed.R
+++ b/tests/testthat/test-resolve_delayed.R
@@ -1,11 +1,9 @@
 adsl <- teal.transform::rADSL # nolint
 adtte <- teal.transform::rADTTE # nolint
-data <- teal.data::cdisc_data(
-  teal.data::cdisc_dataset("ADSL", adsl),
-  teal.data::cdisc_dataset("ADTTE", adtte)
-)
 
-ds <- teal.slice::init_filtered_data(data)
+data_list <- list(ADSL = reactive(adsl), ADTTE = reactive(adtte))
+join_keys <- teal.data::default_cdisc_join_keys[c("ADSL", "ADTTE")]
+primary_keys_list <- lapply(join_keys, function(keys) keys[[1]])
 
 testthat::test_that("resolve_delayed_expr works correctly", {
   # function assumptions check
@@ -77,13 +75,12 @@ testthat::test_that("resolve_delayed.FilteredData works correctly", {
     ),
     ARM2 = list(ref = "A: Drug X", comp = c("B: Placebo", "C: Combination"))
   )
-  ddl_resolved <- isolate(resolve_delayed(arm_ref_comp_ddl, ds))
+  ddl_resolved <- isolate(resolve_delayed(arm_ref_comp_ddl, datasets = data_list, keys = primary_keys_list))
   testthat::expect_identical(arm_ref_comp, ddl_resolved)
 })
 
 
 testthat::test_that("resolve_delayed.list works correctly with reactive objects", {
-  data <- list(ADSL = reactive(adsl), ADTTE = reactive(adtte))
   arm_ref_comp <- list(
     ARMCD = list(
       ref = value_choices(adtte, var_choices = "ARMCD", var_label = "ARM", subset = "ARM A"),
@@ -107,8 +104,8 @@ testthat::test_that("resolve_delayed.list works correctly with reactive objects"
   ddl_resolved <- isolate(
     resolve_delayed(
       arm_ref_comp_ddl,
-      data,
-      keys = list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
+      data_list,
+      keys = primary_keys_list
     )
   )
   testthat::expect_identical(arm_ref_comp, ddl_resolved)
@@ -155,8 +152,7 @@ testthat::test_that("resolving delayed choices removes selected not in choices a
 
   output <- testthat::capture_output({
     shiny::isolate({
-      ds <- teal.slice::init_filtered_data(list(IRIS = list(dataset = head(iris))))
-      resolved_cs <- resolve_delayed(c_s, ds)
+      resolved_cs <- resolve_delayed(c_s, datasets = list(IRIS = reactive(iris)))
     })
   })
 
diff --git a/tests/testthat/test-select_spec.R b/tests/testthat/test-select_spec.R
index 90ab79d8..7fe19317 100644
--- a/tests/testthat/test-select_spec.R
+++ b/tests/testthat/test-select_spec.R
@@ -1,3 +1,8 @@
+adsl <- teal.transform::rADSL # nolint
+adtte <- teal.transform::rADTTE # nolint
+data_list <- list(ADSL = reactive(adsl), ADTTE = reactive(adtte))
+primary_keys_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
+
 testthat::test_that("Proper argument types", {
   choices <- c("c1", "c2", "c3")
   selected <- c("c1", "c2")
@@ -80,17 +85,10 @@ testthat::test_that("Multiple choices", {
 })
 
 testthat::test_that("resolve select_spec works", {
-  set.seed(1)
-  ADSL <- data.frame( # nolint
-    USUBJID = letters[1:10],
-    BMRKR1 = rnorm(10),
-    BMRKR2 = sample(c("L", "M", "H"), 10, replace = TRUE),
-    stringsAsFactors = FALSE
-  )
-  attr(ADSL, "keys") <- teal.data::get_cdisc_keys("ADSL") # nolint
+  attr(adsl, "keys") <- c("STUDYID", "USUBJID") # nolint
 
   expected_spec <- select_spec(
-    choices = variable_choices(ADSL, c("BMRKR1", "BMRKR2")),
+    choices = variable_choices(adsl, c("BMRKR1", "BMRKR2")),
     selected = "BMRKR1",
     multiple = FALSE,
     fixed = FALSE
@@ -107,15 +105,12 @@ testthat::test_that("resolve select_spec works", {
 
   testthat::expect_equal(names(expected_spec), names(delayed_spec))
 
-  data_list <- list(ADSL = reactive(ADSL))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"))
-
-  testthat::expect_identical(expected_spec, isolate(resolve(delayed_spec, datasets = data_list, keys = key_list)))
+  testthat::expect_identical(
+    expected_spec,
+    isolate(resolve(delayed_spec, datasets = data_list, keys = primary_keys_list))
+  )
 })
 
-adsl <- teal.transform::rADSL # nolint
-adtte <- teal.transform::rADTTE # nolint
-
 vc_hard <- variable_choices("ADSL", subset = c("STUDYID", "USUBJID"))
 vc_hard_exp <- structure(
   list(data = "ADSL", subset = c("STUDYID", "USUBJID"), key = NULL),
@@ -159,13 +154,10 @@ testthat::test_that("delayed version of select_spec", {
     )
   )
 
-  data_list <- list(ADSL = reactive(adsl), ADTTE = reactive(adtte))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
-
-  res_obj <- isolate(resolve(obj, datasets = data_list, keys = key_list))
+  res_obj <- isolate(resolve(obj, datasets = data_list, keys = primary_keys_list))
   exp_obj <- select_spec(
-    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-    selected = variable_choices(adsl, "STUDYID", key = teal.data::get_cdisc_keys("ADSL"))
+    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+    selected = variable_choices(adsl, "STUDYID", key = c("STUDYID", "USUBJID"))
   )
   testthat::expect_equal(res_obj, exp_obj)
 
@@ -187,7 +179,7 @@ testthat::test_that("delayed version of select_spec", {
     )
   )
 
-  res_obj <- isolate(resolve(obj, datasets = data_list, keys = key_list))
+  res_obj <- isolate(resolve(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(res_obj, exp_obj)
 })
 
@@ -215,17 +207,10 @@ testthat::test_that("default values", {
 
 # With resolve_delayed
 testthat::test_that("resolve_delayed select_spec works - resolve_delayed", {
-  set.seed(1)
-  ADSL <- data.frame( # nolint
-    USUBJID = letters[1:10],
-    BMRKR1 = rnorm(10),
-    BMRKR2 = sample(c("L", "M", "H"), 10, replace = TRUE),
-    stringsAsFactors = FALSE
-  )
-  attr(ADSL, "keys") <- teal.data::get_cdisc_keys("ADSL") # nolint
+  attr(adsl, "keys") <- c("STUDYID", "USUBJID") # nolint
 
   expected_spec <- select_spec(
-    choices = variable_choices(ADSL, c("BMRKR1", "BMRKR2")),
+    choices = variable_choices(adsl, c("BMRKR1", "BMRKR2")),
     selected = "BMRKR1",
     multiple = FALSE,
     fixed = FALSE
@@ -242,20 +227,12 @@ testthat::test_that("resolve_delayed select_spec works - resolve_delayed", {
 
   testthat::expect_equal(names(expected_spec), names(delayed_spec))
 
-  ds <- teal.slice::init_filtered_data(
-    list(ADSL = list(dataset = ADSL)),
-    join_keys = teal.data::join_keys(
-      teal.data::join_key("ADSL", "ADSL", teal.data::get_cdisc_keys("ADSL"))
-    )
+  testthat::expect_identical(
+    expected_spec,
+    isolate(resolve_delayed(delayed_spec, datasets = data_list, keys = primary_keys_list))
   )
-  testthat::expect_identical(expected_spec, isolate(resolve_delayed(delayed_spec, ds)))
 })
 
-data <- teal.data::cdisc_data(
-  teal.data::cdisc_dataset("ADSL", adsl),
-  teal.data::cdisc_dataset("ADTTE", adtte)
-)
-ds <- teal.slice::init_filtered_data(data)
 
 testthat::test_that("delayed version of select_spec - resolve_delayed", {
   # hard-coded choices & selected
@@ -276,10 +253,10 @@ testthat::test_that("delayed version of select_spec - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   exp_obj <- select_spec(
-    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = teal.data::get_cdisc_keys("ADSL")),
-    selected = variable_choices(adsl, "STUDYID", key = teal.data::get_cdisc_keys("ADSL"))
+    variable_choices(adsl, subset = c("STUDYID", "USUBJID"), key = c("STUDYID", "USUBJID")),
+    selected = variable_choices(adsl, "STUDYID", key = c("STUDYID", "USUBJID"))
   )
   testthat::expect_equal(res_obj, exp_obj)
 
@@ -301,6 +278,7 @@ testthat::test_that("delayed version of select_spec - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(res_obj, exp_obj)
 })
diff --git a/tests/testthat/test-value_choices.R b/tests/testthat/test-value_choices.R
index bbeb05ed..c5b16843 100644
--- a/tests/testthat/test-value_choices.R
+++ b/tests/testthat/test-value_choices.R
@@ -1,5 +1,7 @@
 ADSL <- teal.transform::rADSL # nolint
 ADTTE <- teal.transform::rADTTE # nolint
+data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
+primary_keys_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
 testthat::test_that("Will output warnings when value_choices applied on datasets with missing values and / or labels", {
   data <- data.frame(
@@ -40,10 +42,8 @@ testthat::test_that("delayed version of value_choices", {
       class = c("delayed_value_choices", "delayed_data", "choices_labeled")
     )
   )
-  data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
 
-  res_obj <- isolate(resolve(obj, datasets = data_list, key_list))
+  res_obj <- isolate(resolve(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(
     res_obj,
     value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B"))
@@ -74,7 +74,7 @@ testthat::test_that("delayed version of value_choices", {
     )
   )
 
-  res_obj <- isolate(resolve(obj, datasets = data_list, key_list))
+  res_obj <- isolate(resolve(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(
     res_obj,
     value_choices(ADSL,
@@ -114,7 +114,7 @@ testthat::test_that("delayed version of value_choices", {
     )
   )
 
-  res_obj <- isolate(resolve(obj, datasets = data_list, key_list))
+  res_obj <- isolate(resolve(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(
     res_obj,
     value_choices(ADSL,
@@ -126,12 +126,7 @@ testthat::test_that("delayed version of value_choices", {
 
 
 # With resolve_delayed
-data <- teal.data::cdisc_data(
-  teal.data::cdisc_dataset("ADSL", ADSL),
-  teal.data::cdisc_dataset("ADTTE", ADTTE)
-)
 
-ds <- teal.slice::init_filtered_data(data)
 
 testthat::test_that("delayed version of value_choices - resolve_delayed", {
   # hard-coded subset
@@ -150,7 +145,7 @@ testthat::test_that("delayed version of value_choices - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(
     res_obj,
     value_choices(ADSL, var_choices = "ARMCD", var_label = "ARM", subset = c("ARM A", "ARM B"))
@@ -182,7 +177,7 @@ testthat::test_that("delayed version of value_choices - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(
     res_obj,
     value_choices(ADSL,
@@ -223,7 +218,7 @@ testthat::test_that("delayed version of value_choices - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   testthat::expect_equal(
     res_obj,
     value_choices(ADSL,
diff --git a/tests/testthat/test-variable_choices.R b/tests/testthat/test-variable_choices.R
index 6349d48e..fc06eae9 100644
--- a/tests/testthat/test-variable_choices.R
+++ b/tests/testthat/test-variable_choices.R
@@ -1,5 +1,7 @@
 ADSL <- teal.transform::rADSL # nolint
 ADTTE <- teal.transform::rADTTE # nolint
+data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
+primary_keys_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
 test_that("Can create variable_choices with datasets with no or missing labels", {
   example_data <- data.frame(USUBJID = 1:2, STUDYID = 1:1)
@@ -33,7 +35,7 @@ test_that("delayed version of variable_choices", {
   )
 
   data_list <- list(ADSL = reactive(ADSL), ADTTE = reactive(ADTTE))
-  key_list <- list(ADSL = teal.data::get_cdisc_keys("ADSL"), ADTTE = teal.data::get_cdisc_keys("ADTTE"))
+  key_list <- list(ADSL = c("STUDYID", "USUBJID"), ADTTE = c("STUDYID", "USUBJID", "PARAMCD"))
 
   res_obj <- isolate(resolve(obj, datasets = data_list, keys = key_list))
   expect_equal(
@@ -54,7 +56,7 @@ test_that("delayed version of variable_choices", {
   res_obj <- isolate(resolve(obj, datasets = data_list, keys = key_list))
   expect_equal(
     res_obj,
-    variable_choices(ADSL, subset = colnames(ADSL)[1:2], key = teal.data::get_cdisc_keys("ADSL"))
+    variable_choices(ADSL, subset = colnames(ADSL)[1:2], key = c("STUDYID", "USUBJID"))
   )
 
   # non-null key value
@@ -74,13 +76,6 @@ test_that("delayed version of variable_choices", {
   )
 })
 
-# with resolve_delayed
-data <- teal.data::cdisc_data(
-  teal.data::cdisc_dataset("ADSL", ADSL),
-  teal.data::cdisc_dataset("ADTTE", ADTTE)
-)
-
-ds <- teal.slice::init_filtered_data(data)
 
 test_that("delayed version of variable_choices - resolve_delayed", {
   # hard-coded subset
@@ -93,7 +88,7 @@ test_that("delayed version of variable_choices - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   expect_equal(
     res_obj,
     variable_choices(ADSL, subset = c("SEX", "ARMCD", "COUNTRY"))
@@ -110,10 +105,10 @@ test_that("delayed version of variable_choices - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   expect_equal(
     res_obj,
-    variable_choices(ADSL, subset = colnames(ADSL)[1:2], key = teal.data::get_cdisc_keys("ADSL"))
+    variable_choices(ADSL, subset = colnames(ADSL)[1:2], key = c("STUDYID", "USUBJID"))
   )
 
   # non-null key value
@@ -126,7 +121,7 @@ test_that("delayed version of variable_choices - resolve_delayed", {
     )
   )
 
-  res_obj <- isolate(resolve_delayed(obj, datasets = ds))
+  res_obj <- isolate(resolve_delayed(obj, datasets = data_list, keys = primary_keys_list))
   expect_equal(
     res_obj,
     variable_choices(ADSL, key = c("USUBJID", "STUDYID"))