Gdr 3286

DESCRIPTION

@@ -2,8 +2,8 @@ Type: Package
 Package: gDRcore
 Title: Processing functions and interface to process and analyze drug
     dose-response data
-Version: 1.9.4
-Date: 2026-02-02
+Version: 1.9.5
+Date: 2026-02-16
 Authors@R: c(
     person("Bartosz", "Czech", , "bartosz.czech@contractors.roche.com", role = "aut",
            comment = c(ORCID = "0000-0002-9908-3007")),

NEWS.md

@@ -1,3 +1,6 @@
+## gDRcore 1.9.5 - 2026-02-16
+* fix stack imbalance warnings during byte-compilation
+
 ## gDRcore 1.9.4 - 2026-02-02
 * remove duplicated code from `map_references` in `map_untreated`
 

R/packages.R

@@ -4,58 +4,4 @@
 
 # data.table awareness
 .datatable.aware <- TRUE
-patterns <- data.table:::patterns
-
-#' onload function
-#'
-#' @param libname library name
-#' @param pkgname package name
-#' @noRd
-.onLoad <- function(libname, pkgname) {
-  # scientific notation was disabled due to the problem with unit tests
-  options(scipen = 999) 
-
-  cores <- Sys.getenv("NUM_CORES")
-  # based on https://github.com/Bioconductor/BiocParallel/issues/98
-  if (.Platform$OS.type != "windows" && cores != "") {
-    BiocParallel::register(
-      BiocParallel::MulticoreParam(workers = as.numeric(cores)), 
-      default = TRUE
-    )
-  } else { 
-    BiocParallel::register(
-      BiocParallel::SerialParam(), 
-      default = TRUE
-    )
-  } 
-}
-
-# Prevent R CMD check from complaining about the use of pipe expressions
-# standard data.table variables
-if (getRversion() >= "2.15.1") {
-  utils::globalVariables(
-    c(
-      "normalization_type",
-      ".",
-      "rn",
-      "column",
-      "CorrectedReadout",
-      "cotrt_value",
-      "x",
-      "Duration",
-      "isDay0",
-      "record_id",
-      "ratio",
-      "smooth",
-      "priority1",
-      "priority2",
-      "x.N",
-      "..cotrt_var",
-      "..present_ref_cols",
-      "..y",
-      "LogFoldChange",
-      "ReadoutValue"
-    ), 
-    utils::packageName())
-}
 

R/zzz.R

@@ -0,0 +1,71 @@
+
+.drugNameRegex <- NULL
+.untreated_tag_patterns <- NULL
+.untreatedDrugNameRegex <- NULL
+patterns <- NULL
+
+#' onload function
+#'
+#' @param libname library name
+#' @param pkgname package name
+#' @noRd
+.onLoad <- function(libname, pkgname) {
+  # scientific notation was disabled due to the problem with unit tests
+  options(scipen = 999) 
+
+  cores <- Sys.getenv("NUM_CORES")
+  # based on https://github.com/Bioconductor/BiocParallel/issues/98
+  if (.Platform$OS.type != "windows" && cores != "") {
+    BiocParallel::register(
+      BiocParallel::MulticoreParam(workers = as.numeric(cores)), 
+      default = TRUE
+    )
+  } else { 
+    BiocParallel::register(
+      BiocParallel::SerialParam(), 
+      default = TRUE
+    )
+  } 
+  # CONS
+  drugs_id <- gDRutils::get_env_identifiers("drug_name")
+  utils::assignInNamespace(".drugNameRegex", sprintf("^%s$|^%s_[[:digit:]]+$", drugs_id, drugs_id), ns = pkgname)
+
+  untreated_tag_patterns <- vapply(
+    gDRutils::get_env_identifiers("untreated_tag"),
+    sprintf,
+    fmt = "^%s$",
+    character(1)
+  )
+  utils::assignInNamespace(".untreated_tag_patterns", untreated_tag_patterns, ns = pkgname)
+  utils::assignInNamespace(".untreatedDrugNameRegex", paste(untreated_tag_patterns, collapse = "|"), ns = pkgname)
+
+  # data.table compatible
+  utils::assignInNamespace("patterns", data.table:::patterns, ns = pkgname)
+  utils::globalVariables(
+    c(
+      ".",
+      "..cotrt_var",
+      "..present_ref_cols",
+      "..y",
+      "bliss_score",
+      "column",
+      "CorrectedReadout",
+      "cotrt_value",
+      "Duration",
+      "hsa_score",
+      "isDay0",
+      "LogFoldChange",
+      "normalization_type",
+      "priority1",
+      "priority2",
+      "ratio",
+      "ReadoutValue",
+      "ReadoutValue_T0",
+      "record_id",
+      "rn",
+      "smooth",
+      "x",
+      "x.N"
+    ), 
+    pkgname)
+}

vignettes/gDR-annotation.Rmd

@@ -8,7 +8,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-```{r, include = FALSE}
+```{r knitr-setup, include = FALSE}
 knitr::opts_chunk$set(
   collapse = TRUE,
   comment = "#>"
@@ -36,7 +36,7 @@ Alternatively, users can use other annotation files stored outside of this packa
 - `GDR_CELLLINE_ANNOTATION`: Represents the path to the cell line annotation CSV file.
 - `GDR_DRUG_ANNOTATION`: Represents the path to the drug annotation CSV file.
 
-```{r, eval=FALSE}
+```{r set-external-annotations, eval=FALSE}
 Sys.setenv(GDR_CELLLINE_ANNOTATION = "some/path/to/cell_line_annotation.csv")
 Sys.setenv(GDR_DRUG_ANNOTATION = "some/path/to/drug_annotation.csv")
 ```
@@ -45,7 +45,7 @@ Sys.setenv(GDR_DRUG_ANNOTATION = "some/path/to/drug_annotation.csv")
 
 To turn off the usage of external paths for data annotation, please set these two environmental variables to empty.
 
-```{r, eval=FALSE}
+```{r unset-external-annotations, eval=FALSE}
 Sys.setenv(GDR_CELLLINE_ANNOTATION = "")
 Sys.setenv(GDR_DRUG_ANNOTATION = "")
 ```
@@ -76,7 +76,7 @@ If some information is not known for the cell line or drug, the corresponding fi
 
 To annotate `SummarizedExperiment` and `MultiAssayExperiment` objects, use the functions `annotate_se_with_drug`, `annotate_mae_with_drug`, `annotate_se_with_cell_line`, and `annotate_mae_with_cell_line`. These functions take the experiment objects and the corresponding annotation tables as input and return the annotated objects.
 
-```{r, eval=FALSE}
+```{r annotate-experiment-objects, eval=FALSE}
 # Example for SummarizedExperiment
 se <- SummarizedExperiment::SummarizedExperiment(
   rowData = data.table::data.table(Gnumber = c("D1", "D2", "D3"))
@@ -104,6 +104,6 @@ Proper annotation of drug and cell line data is crucial for running the gDR pipe
 
 # SessionInfo {-}
 
-```{r sessionInfo}
+```{r session-info}
 sessionInfo()
 ```

vignettes/gDR-data-model.Rmd

@@ -9,7 +9,7 @@ output:
 abstract: |
   This vignette comprehensively describes the data model used in the gDRsuite.
 vignette: |
-  %\VignetteIndexEntry{Vignette Title}
+  %\VignetteIndexEntry{gDRcore}
   %\VignetteEngine{knitr::rmarkdown}
   %\VignetteEncoding{UTF-8}
 ---
@@ -110,6 +110,6 @@ In gDR `r Biocpkg("BumpyMatrix")` objects can be easily transformed into the `r
 
 # Session info {.unnumbered}
 
-```{r sessionInfo, echo=FALSE}
+```{r session-info, echo=FALSE}
 sessionInfo()
 ```

vignettes/gDRcore.Rmd

@@ -8,14 +8,14 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-```{r, include = FALSE}
+```{r knitr-config, include = FALSE}
 knitr::opts_chunk$set(
   collapse = TRUE,
   comment = "#>"
 )
 ```
 
-```{r setup, echo = FALSE}
+```{r load-gdr-libraries, echo = FALSE}
 library(gDRtestData)
 library(gDRcore)
 log_level <- futile.logger::flog.threshold("ERROR")
@@ -87,13 +87,13 @@ Please familiarize yourself with the `gDRimport` package, which contains a varie
 
 This example is based on the artificial dataset called `data1` available within the `gDRimport` package. `gDR` requires three types of data that should be used as the raw input: Template, Manifest, and RawData. More information about these three types of data can be found in our general documentation.
 
-```{r}
+```{r fetch-import-test-data}
 td <- gDRimport::get_test_data()
 ```
 
 The provided dataset needs to be merged into one `data.table` object to be able to run the gDR pipeline. This process can be done using two functions: `gDRimport::load_data()` and `gDRcore::merge_data()`.
 
-```{r, include=FALSE}
+```{r merge-manifest-templates-results, include=FALSE}
 loaded_data <-
   suppressMessages(
     gDRimport::load_data(
@@ -110,16 +110,16 @@ head(input_df)
 
 We provide an all-in-one function that splits data into appropriate data types, creates the SummarizedExperiment object for each data type, splits data into treatment and control assays, normalizes, averages, calculates gDR metrics, and finally, creates the MultiAssayExperiment object. This function is called `runDrugResponseProcessingPipeline`.
 
-```{r, message = FALSE, results = FALSE, warning = FALSE}
+```{r execute-processing-pipeline, message = FALSE, results = FALSE, warning = FALSE}
 mae <- runDrugResponseProcessingPipeline(input_df)
 ```
 
-```{r}
+```{r inspect-mae-output}
 mae
 ```
 And we can subset the MultiAssayExperiment to receive the SummarizedExperiment specific to any data type, e.g.
 
-```{r}
+```{r subset-single-agent-experiment}
 mae[["single-agent"]]
 ```
 
@@ -128,6 +128,6 @@ Extraction of the data from either `MultiAssayExperiment` or `SummarizedExperime
 
 # SessionInfo {-}
 
-```{r sessionInfo}
+```{r session-info}
 sessionInfo()
 ```