[GDR-2530] Switch to get_supported_experiments

DESCRIPTION

@@ -2,8 +2,8 @@ Type: Package
 Package: gDRcore
 Title: Processing functions and interface to process and analyze drug
     dose-response data
-Version: 1.3.1
-Date: 2024-05-27
+Version: 1.3.2
+Date: 2024-06-04
 Authors@R: c(
     person("Bartosz", "Czech", , "[email protected]", role = "aut",
            comment = c(ORCID = "0000-0002-9908-3007")),

NEWS.md

@@ -1,3 +1,6 @@
+## gDRcore 1.3.2 - 2024-06-04
+* switch to `get_supported_experiments`
+
 ## gDRcore 1.3.1 - 2024-05-27
 * synchronize Bioconductor and GitHub versioning
 

R/convert_se_to_raw_data.R

@@ -22,8 +22,8 @@ convert_mae_to_raw_data <- function(mae) {
 
   # Remove duplicates shared between assays to keep only original single-agent
   common_records <- Reduce(intersect, lapply(data, "[[", "record_id"))
-  sa_name <- gDRutils::get_experiment_groups("single-agent")[["single-agent"]]
-  combo_name <- gDRutils::get_experiment_groups("combination")
+  sa_name <- gDRutils::get_supported_experiments("sa")
+  combo_name <- gDRutils::get_supported_experiments("combo")
   # check if data contains combination data and shared single-agent records are unique (true for internal data)
   if (length(names(data)) > 1 && max(table(unique(data[[combo_name]])[record_id %in% common_records]$record_id)) == 1) {
     data[[sa_name]] <- data[[sa_name]][!record_id %in% common_records]

R/data_type.R

@@ -68,7 +68,7 @@ identify_data_type <- function(df,
   df[, record_id := .I]
   df[, type := NA_character_]
 
-  sa_name <- gDRutils::get_experiment_groups("single-agent")[["single-agent"]]
+  sa_name <- gDRutils::get_supported_experiments("sa")
 
   controls <- rowSums(df[, conc_ids, with = FALSE] == 0) == length(conc_ids)
   single_agent <- rowSums(df[, conc_ids, with = FALSE] != 0) == 1
@@ -86,8 +86,8 @@ identify_data_type <- function(df,
     conc_ratio <- conc_ratio[!names(conc_ratio) %in% c("Inf", "-Inf")]
 
     type <- ifelse(length(conc_ratio) <= codilution_conc,
-                   gDRutils::get_experiment_groups("single-agent")[["co-dilution"]],
-                   gDRutils::get_experiment_groups("combination"))
+                   gDRutils::get_supported_experiments("cd"),
+                   gDRutils::get_supported_experiments("combo"))
     df$type[missing_type_rows] <- type
   }
   df
@@ -167,7 +167,7 @@ split_raw_data <- function(df,
     simplify = FALSE)
   )
 
-  sa_name <- gDRutils::get_experiment_groups("single-agent")[["single-agent"]]
+  sa_name <- gDRutils::get_supported_experiments("sa")
 
   drug_ids <- drug_ids[which(drug_ids %in% names(df))]
   codrug_ids <- drug_ids[grep("[0-9]", names(drug_ids))]
@@ -205,7 +205,7 @@ split_raw_data <- function(df,
       df_merged <- rbind(
         df_list[[x]], 
         cotrt_matching[control, on = intersect(names(cotrt_matching), names(control))])
-      if (x == gDRutils::get_experiment_groups("combination")) {
+      if (x == gDRutils::get_supported_experiments("combo")) {
         matrix_data <- rbind(df_merged, df_list[[sa_name]])
         for (j in conc_idx)
           data.table::set(matrix_data, which(is.na(matrix_data[[j]])), j, 0)

R/fit_SE.R

@@ -16,7 +16,7 @@ fit_SE <- function(se,
   # Assertions:
   checkmate::assert_class(se, "SummarizedExperiment")
   checkmate::assert_string(data_type)
-  checkmate::assert_choice(data_type, gDRutils::get_experiment_groups("single-agent"))
+  checkmate::assert_choice(data_type, choices = gDRutils::get_experiment_groups("single-agent"))
   checkmate::assert_character(nested_identifiers, null.ok = TRUE)
   checkmate::assert_string(averaged_assay)
   checkmate::assert_string(metrics_assay)

R/fit_SE.combinations.R

@@ -21,7 +21,7 @@
 #' @examples 
 #' fmae_cms <- gDRutils::get_synthetic_data("finalMAE_combo_matrix_small")
 #' 
-#' se1 <- fmae_cms[[gDRutils::get_experiment_groups("combination")]]
+#' se1 <- fmae_cms[[gDRutils::get_supported_experiments("combo")]]
 #' SummarizedExperiment::assays(se1) <- 
 #'   SummarizedExperiment::assays(se1)["Averaged"]
 #' fit_SE.combinations(se1[1, 1])
@@ -33,7 +33,7 @@
 #' @export
 #'
 fit_SE.combinations <- function(se,
-                                data_type = gDRutils::get_experiment_groups("combination"),
+                                data_type = gDRutils::get_supported_experiments("combo"),
                                 series_identifiers = NULL,
                                 normalization_types = c("GR", "RV"),
                                 averaged_assay = "Averaged",

R/runDrugResponseProcessingPipeline.R

@@ -234,8 +234,7 @@ runDrugResponseProcessingPipeline <- function(x,
   checkmate::assert_choice(start_from, get_pipeline_steps())
   checkmate::assert_character(selected_experiments, null.ok = TRUE)
   checkmate::assert_subset(selected_experiments,
-                           names(gDRutils::get_experiment_groups()),
-  )
+                           gDRutils::get_supported_experiments())
 
   if (!is.null(selected_experiments) && !partial_run) {
     stop("Selected experiments are only supported with partial_run enabled")
@@ -347,7 +346,7 @@ runDrugResponseProcessingPipeline <- function(x,
       )
 
       # 4th step - Fit SE
-      if (data_type == gDRutils::get_experiment_groups("combination")) {
+      if (data_type == gDRutils::get_supported_experiments("combo")) {
         step_args <- list(
           se = se$result,
           data_type = data_type,

R/utils.R

@@ -199,7 +199,7 @@ data_model.data.table <- function(x) {
             %in% gDRutils::get_env_identifiers("untreated_tag"))) {
       "single-agent"
     } else {
-        "combination"
+      "combination"
     }
   } else if (.get_default_single_agent_nested_identifiers() %in% colnames(x)) {
     "single-agent"
@@ -208,17 +208,6 @@ data_model.data.table <- function(x) {
   }
 }
 
-
-#' @keywords utils
-get_data_type_to_data_model_mapping <- function() {
-  c(
-    `single-agent` = "single-agent",
-    "co-dilution" = "single-agent",
-    "combination" = "combination"
-  )
-}
-
-
 #' Detect model of data from experiment name
 #'
 #' @param x character with experiment name
@@ -228,22 +217,27 @@ get_data_type_to_data_model_mapping <- function() {
 #' @keywords utils
 #' @export
 data_model.character <- function(x) {
-  # TODO: switch to gDRutils::get_experiment_groups()
-  # once we clean-up single-agent/combination assignemnts
-  exp_v <- get_data_type_to_data_model_mapping()
-
-  checkmate::assert_subset(x, names(exp_v))
-
-  exp_v[[x]]
+  checkmate::assert_subset(x, gDRutils::get_supported_experiments())
 
+  exp_v <- gDRutils::get_experiment_groups()
+  names(exp_v[grep(x, exp_v)])
 }
 
+
+#' Validate availability of data models
+#' 
+#' @param d_types character vector with experiment names in \code{MultiAssayExperiment} object
+#' @param s_d_models character vector with names of supported experiment
+#'
+#' @keywords internal
 validate_data_models_availability <- function(d_types, s_d_models) {
+  checkmate::assert_character(d_types)
+  checkmate::assert_character(s_d_models, null.ok = TRUE)
 
-  dm_v <- get_data_type_to_data_model_mapping()
-  
+  dm_v <- gDRutils::get_experiment_groups()
+
   req_d_models <-
-    unique(as.character(dm_v[names(dm_v) %in% d_types]))
+    unique(names(dm_v)[vapply(d_types, function(i) grep(i, dm_v), integer(1))])
   f_models <- req_d_models[!req_d_models %in% s_d_models]
   if (length(f_models)) {
     msg1 <-
@@ -258,7 +252,7 @@ validate_data_models_availability <- function(d_types, s_d_models) {
 
 #' Get default nested identifiers
 #'
-#' @param x data.table with raw data or SummarizedExperiment object 
+#' @param x data.table with raw data or \code{SummarizedExperiment} object 
 #' with gDR assays
 #' @param data_model single-agent vs combination
 #' 

tests/testthat/test-data_type.R

@@ -25,8 +25,8 @@ test_that("identify_data_type and split_raw_data works as expected", {
 
   df_list <- split_raw_data(df)
   expect_true(inherits(df_list, "list"))
-  expect_true(all(names(df_list) %in% c(gDRutils::get_experiment_groups("combination"),
-                                        gDRutils::get_experiment_groups("single-agent")[["single-agent"]])))
+  expect_true(all(names(df_list) %in% c(gDRutils::get_supported_experiments("combo"),
+                                        gDRutils::get_supported_experiments("sa"))))
 
 
   df2 <- data.table::data.table(Gnumber = c(rep("DrugA", 9), "DrugB"),

tests/testthat/test-fit_SE.R

@@ -50,7 +50,7 @@ test_that("fit_SE.combinations works as expected", {
 
   # combo data 
   fmae_cms <- gDRutils::get_synthetic_data("finalMAE_combo_matrix_small")
-  se1 <- fmae_cms[[gDRutils::get_experiment_groups("combination")]]
+  se1 <- fmae_cms[[gDRutils::get_supported_experiments("combo")]]
   SummarizedExperiment::assays(se1) <- SummarizedExperiment::assays(se1)["Averaged"]
 
   new_se1 <- purrr::quietly(fit_SE.combinations)(se1[1, 1])