Enhancement/run app via package installation

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: aNCA
 Title: (Pre-)Clinical NCA in a Dynamic Shiny App
-Version: 0.0.0.9000
+Version: 0.0.0.9001
 Authors@R: c(
     person("Ercan", "Suekuer", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0009-0001-1626-1526")),

NAMESPACE

@@ -7,8 +7,11 @@ export(apply_filters)
 export(apply_labels)
 export(as_factor_preserve_label)
 export(calculate_summary_stats)
+export(check_slope_rule_overlap)
 export(create_start_impute)
+export(export_cdisc)
 export(filter_breaks)
+export(filter_slopes)
 export(flexible_violinboxplot)
 export(format_pkncaconc_data)
 export(format_pkncadata_intervals)
@@ -26,105 +29,53 @@ export(parse_annotation)
 export(parse_tlg_definitions)
 export(pivot_wider_pknca_results)
 export(pkcg01)
-export(pptestcd_dict)
 export(run_app)
 export(set_empty_label)
-import(bslib)
 import(dplyr)
 import(forcats)
 import(ggplot2)
 import(haven)
 import(nestcolor)
 import(plotly)
-import(shiny)
 import(tidyr)
-importFrom(DT,DTOutput)
-importFrom(DT,datatable)
-importFrom(DT,formatStyle)
-importFrom(DT,renderDataTable)
-importFrom(DT,styleEqual)
-importFrom(PKNCA,PKNCA.options)
-importFrom(PKNCA,PKNCAconc)
-importFrom(PKNCA,PKNCAdata)
-importFrom(PKNCA,PKNCAdose)
 importFrom(PKNCA,pk.calc.c0)
-importFrom(PKNCA,pk.nca)
-importFrom(PKNCA,pknca_units_table)
 importFrom(checkmate,assert_numeric)
 importFrom(dplyr,across)
 importFrom(dplyr,arrange)
-importFrom(dplyr,case_when)
 importFrom(dplyr,distinct)
 importFrom(dplyr,filter)
 importFrom(dplyr,group_by)
 importFrom(dplyr,left_join)
 importFrom(dplyr,mutate)
 importFrom(dplyr,n)
-importFrom(dplyr,pull)
 importFrom(dplyr,rename)
-importFrom(dplyr,rename_with)
 importFrom(dplyr,rowwise)
 importFrom(dplyr,select)
 importFrom(dplyr,slice)
-importFrom(dplyr,summarise)
 importFrom(dplyr,ungroup)
 importFrom(dplyr,where)
 importFrom(ggh4x,scale_y_facet)
 importFrom(ggplot2,aes)
-importFrom(ggplot2,facet_wrap)
-importFrom(ggplot2,geom_errorbar)
-importFrom(ggplot2,geom_line)
-importFrom(ggplot2,geom_point)
-importFrom(ggplot2,ggplot)
 importFrom(ggplot2,ggplot_build)
 importFrom(ggplot2,ggplot_gtable)
 importFrom(ggplot2,labs)
 importFrom(ggplot2,scale_x_continuous)
 importFrom(glue,glue)
 importFrom(grid,convertUnit)
-importFrom(htmlwidgets,JS)
 importFrom(logger,log_debug)
 importFrom(logger,log_error)
 importFrom(logger,log_fatal)
 importFrom(logger,log_info)
 importFrom(logger,log_trace)
 importFrom(logger,log_warn)
 importFrom(magrittr,`%>%`)
-importFrom(plotly,event_data)
-importFrom(plotly,plotlyOutput)
-importFrom(plotly,plotly_build)
-importFrom(plotly,renderPlotly)
 importFrom(purrr,imap)
-importFrom(reactable,colDef)
-importFrom(reactable,getReactableState)
-importFrom(reactable,reactable)
-importFrom(reactable,reactableOutput)
-importFrom(reactable,reactableTheme)
-importFrom(reactable,renderReactable)
-importFrom(reactable.extras,dropdown_extra)
-importFrom(reactable.extras,text_extra)
-importFrom(rio,export_list)
 importFrom(rlang,sym)
-importFrom(rmarkdown,render)
 importFrom(scales,breaks_log)
 importFrom(scales,label_log)
-importFrom(shinyBS,bsModal)
-importFrom(shinyFiles,shinyDirChoose)
-importFrom(shinyWidgets,dropdown)
-importFrom(shinyWidgets,pickerInput)
-importFrom(shinyWidgets,switchInput)
-importFrom(shinyWidgets,updatePickerInput)
-importFrom(shinycssloaders,withSpinner)
-importFrom(shinyjqui,orderInput)
-importFrom(shinyjqui,updateOrderInput)
 importFrom(stats,sd)
-importFrom(stringi,stri_rand_strings)
 importFrom(tern,g_ipp)
 importFrom(tidyr,pivot_longer)
 importFrom(tidyr,pivot_wider)
-importFrom(tools,file_ext)
 importFrom(units,set_units)
-importFrom(utils,read.csv)
-importFrom(utils,write.csv)
 importFrom(yaml,read_yaml)
-importFrom(zip,zipr)

R/export_cdisc.R

@@ -18,34 +18,6 @@
 #'
 #' @import dplyr
 #' @export
-
-
-# Define the unique combinations
-pptestcd_dict <- setNames(
-  c(
-    "Total CL Obs by F", "Time of Last Nonzero Conc", "Max Conc", "Vz Obs by F", "AUC Infinity Obs",
-    "Last Nonzero Conc", "Time of CMAX", "R Squared", "R Squared Adjusted", "Max Conc Norm by Dose",
-    "AUC to Last Nonzero Conc Norm by Dose", "Lambda z", "AUC to Last Nonzero Conc",
-    "Half-Life Lambda z", "Number of points used for Lambda z", "Last Nonzero Conc Predicted",
-    "Span Ratio", "Lambda z lower limit (time)",
-
-    # Manually filled
-    "Trough Concentration", "Average Concentration", "AUC Infinity Predicted",
-    "AUMC Infinity Observed", "AUC Percent Extrapolated Observed",
-    "AUC Percent Extrapolated Predicted", "Clearance Observed",
-    "Clearance Predicted", "Mean Residence Time Intravenous Observed",
-    "Volume of Distribution Observed",
-    "Steady-State Volume of Distribution Intravenous Observed",
-    "AUC Infinity Observed Dose-Normalized", "Maximum Concentration Dose-Normalized"
-  ),
-  c("CLFO", "TLST", "CMAX", "VZFO", "AUCIFO", "CLST", "TMAX", "R2", "R2ADJ", "CMAXD", "AUCLSTD",
-    "LAMZ", "AUCLST", "LAMZHL", "LAMZNPT", "CLSTP", "LAMZSPNR", "LAMZLL",
-    "CTROUGH", "CAV", "AUCIFP", "AUMCINF.OBS", "AUCPEO", "AUCPEP", "CL.OBS", "CL.PRED",
-    "MRT.IV.OBS", "VZ.OBS", "VSS.IV.OBS", "AUCINF.OBS.DN", "CMAX.DN"
-  )
-)
-
-
 export_cdisc <- function(res_nca) {
   if (FALSE) {
     # uncomment in case of more added variables
@@ -192,7 +164,7 @@ export_cdisc <- function(res_nca) {
       PPENINT = ifelse(end != Inf, end, NA)
     )  %>%
     # Map PPTEST CDISC descriptions using PPTESTCD CDISC names
-    mutate(PPTEST = pptestcd_dict[PPTESTCD])  %>%
+    mutate(PPTEST = .pptestcd_dict[PPTESTCD])  %>%
     group_by(USUBJID)  %>%
     mutate(PPSEQ = if ("PCSEQ" %in% names(.)) PCSEQ else row_number())  %>%
     ungroup()
@@ -214,3 +186,27 @@ export_cdisc <- function(res_nca) {
 
   return(list(pp = pp, adpp = adpp))
 }
+
+.pptestcd_dict <- setNames(
+  c(
+    "Total CL Obs by F", "Time of Last Nonzero Conc", "Max Conc", "Vz Obs by F", "AUC Infinity Obs",
+    "Last Nonzero Conc", "Time of CMAX", "R Squared", "R Squared Adjusted", "Max Conc Norm by Dose",
+    "AUC to Last Nonzero Conc Norm by Dose", "Lambda z", "AUC to Last Nonzero Conc",
+    "Half-Life Lambda z", "Number of points used for Lambda z", "Last Nonzero Conc Predicted",
+    "Span Ratio", "Lambda z lower limit (time)",
+
+    # Manually filled
+    "Trough Concentration", "Average Concentration", "AUC Infinity Predicted",
+    "AUMC Infinity Observed", "AUC Percent Extrapolated Observed",
+    "AUC Percent Extrapolated Predicted", "Clearance Observed",
+    "Clearance Predicted", "Mean Residence Time Intravenous Observed",
+    "Volume of Distribution Observed",
+    "Steady-State Volume of Distribution Intravenous Observed",
+    "AUC Infinity Observed Dose-Normalized", "Maximum Concentration Dose-Normalized"
+  ),
+  c("CLFO", "TLST", "CMAX", "VZFO", "AUCIFO", "CLST", "TMAX", "R2", "R2ADJ", "CMAXD", "AUCLSTD",
+    "LAMZ", "AUCLST", "LAMZHL", "LAMZNPT", "CLSTP", "LAMZSPNR", "LAMZLL",
+    "CTROUGH", "CAV", "AUCIFP", "AUMCINF.OBS", "AUCPEO", "AUCPEP", "CL.OBS", "CL.PRED",
+    "MRT.IV.OBS", "VZ.OBS", "VSS.IV.OBS", "AUCINF.OBS.DN", "CMAX.DN"
+  )
+)

R/run_app.R

@@ -1,32 +1,47 @@
 #' Run the Shiny app
-#'
-#' List of functions imported for the shiny application.
-#' When adding new imports, please keep the alphabetical order, at lest for packages.
-#'
-#' @import shiny
-#' @import bslib
-#' @importFrom dplyr mutate filter select group_by summarise pull arrange ungroup
-#' @importFrom dplyr rename_with across case_when left_join rename
-#' @importFrom DT DTOutput renderDataTable datatable formatStyle styleEqual
-#' @importFrom ggplot2 ggplot geom_errorbar geom_point geom_line labs aes facet_wrap
-#' @importFrom htmlwidgets JS
-#' @importFrom PKNCA PKNCAconc PKNCAdose PKNCAdata pk.nca PKNCA.options pknca_units_table
-#' @importFrom plotly plotlyOutput renderPlotly plotly_build event_data
-#' @importFrom reactable reactable reactableOutput renderReactable colDef reactableTheme
-#' @importFrom reactable getReactableState
-#' @importFrom reactable.extras text_extra dropdown_extra
-#' @importFrom rio export_list
-#' @importFrom rmarkdown render
-#' @importFrom shinyBS bsModal
-#' @importFrom shinycssloaders withSpinner
-#' @importFrom shinyFiles shinyDirChoose
-#' @importFrom shinyjqui orderInput updateOrderInput
-#' @importFrom shinyWidgets dropdown pickerInput switchInput updatePickerInput
-#' @importFrom stringi stri_rand_strings
-#' @importFrom tools file_ext
-#' @importFrom utils read.csv write.csv
-#' @importFrom zip zipr
+#' @param ... Arguments passed to `shiny::runApp()`
 #' @export
-run_app <- function() {
-  shiny::runApp(system.file("shiny", package = "aNCA"))
+run_app <- function(...) {
+  require(aNCA)
+
+  require(bslib)
+  require(checkmate)
+  require(dplyr)
+  require(DT)
+  require(forcats)
+  require(ggh4x)
+  require(ggplot2)
+  require(glue)
+  require(haven)
+  require(htmlwidgets)
+  require(logger)
+  require(magrittr)
+  require(nestcolor)
+  require(PKNCA)
+  require(plotly)
+  require(purrr)
+  require(reactable)
+  require(reactable.extras)
+  require(rio)
+  require(rmarkdown)
+  require(scales)
+  require(shiny)
+  require(shinyBS)
+  require(shinycssloaders)
+  require(shinyFiles)
+  require(shinyjqui)
+  require(shinyjs)
+  require(shinyWidgets)
+  require(stats)
+  require(stringi)
+  require(stringr)
+  require(tern)
+  require(tidyr)
+  require(tools)
+  require(utils)
+  require(units)
+  require(rlang)
+  require(yaml)
+  require(zip)
+  shiny::runApp(system.file("shiny", package = "aNCA"), ...)
 }

R/utils-slope_selector.R

@@ -11,8 +11,8 @@
 #' @returns Original dataset, with `is.included.hl`, `is.excluded.hl` and `exclude_half.life`
 #'          columns modified in accordance to the provided slope filters.
 #' @importFrom dplyr filter group_by mutate
-#'
-.filter_slopes <- function(data, slopes, profiles) {
+#' @export
+filter_slopes <- function(data, slopes, profiles) {
   if (is.null(data) || is.null(data$conc) || is.null(data$conc$data))
     stop("Please provide valid data.")
 
@@ -39,7 +39,7 @@
     # Go over all rules and check if there is no overlap - if there is, edit accordingly
     slopes <- purrr::reduce(
       split(slopes, seq_len(nrow(slopes))),
-      .f = ~ .check_slope_rule_overlap(.x, .y, .keep = TRUE)
+      .f = ~ check_slope_rule_overlap(.x, .y, .keep = TRUE)
     )
   }
 
@@ -84,7 +84,8 @@
 #'                 that the user wants to remove rule if new range already exists in the dataset.
 #'                 If TRUE, in that case full range will be kept.
 #' @returns Data frame with full ruleset, adjusted for new rules.
-.check_slope_rule_overlap <- function(existing, new, .keep = FALSE) {
+#' @export
+check_slope_rule_overlap <- function(existing, new, .keep = FALSE) {
   # check if any rule already exists for specific patient and profile #
   existing_index <- which(
     existing$TYPE == new$TYPE &

README.md

@@ -28,19 +28,33 @@ This application enables users to upload their datasets and perform Non-Compartm
 * **Save your analysis settings** and reupload them later to keep on analysing!
 
 ## Installation
-To install the application, clone the repository and load it locally using the following commands in your terminal:
-``` sh
-git clone https://github.com/pharmaverse/aNCA.git # Clone the repository
+### Via pak (recommended)
+We recommend using [pak](https://github.com/r-lib/pak) for package installation, along with all system dependencies. If you do not have `pak` available, you will need to set it up first:
+```R
+install.packages("pak")
 ```
-You can then run the application from the R console anytime. Just make sure first your working directory is set to the aNCA folder:
-``` r
-# install devtools if not present
-if (!requireNamespace('devtools', quietly = TRUE)) install.packages('devtools')
-devtools::load_all() # load all dependencies
-aNCA::run_app() # run the application
+then you can install  [aNCA](.) by running:
+```R
+pak::install("pharmaverse/aNCA")
+```
+in your R console.
+
+### Via cloning the repository (for contributors)
+Alternatively, you can set up the package by cloning the repository:
+```bash
+git clone https://github.com/pharmaverse/aNCA.git
+```
+and then loading it directly using [devtools](https://github.com/r-lib/devtools):
+```R
+devtools::load_all()
 ```
 
 ## Quick start
+To run the application, simply invoke:
+```R
+aNCA::run_app()
+```
+
 The testing data will be automatically loaded upon application startup. You can provide your own dataset in the **data** tab. Here you can also specify pre-processing filters.
 
 In the **NCA** tab, start off by loading the pre-processed data using *Submit* button. You will also need to choose dose number in the *Settings*. Then, you will be able to run the NCA analysis. From there, you can also specify different analysis options, like applying flag rule sets and selecting slopes.

inst/WORDLIST

@@ -26,11 +26,13 @@ cmax
 codebase
 csv
 customizable
+devtools
 df
 ggplot
 ggplots
 lastdose
 nca
+pak
 pharmacokinetic
 pkcg
 pknca

inst/shiny/modules/slope_selector.R

@@ -356,12 +356,12 @@ slope_selector_server <- function(
 
     # Observe input$nca
     observeEvent(profiles_per_patient(), {
-      mydata(.filter_slopes(mydata(), manual_slopes(), profiles_per_patient()))
+      mydata(filter_slopes(mydata(), manual_slopes(), profiles_per_patient()))
     })
 
     #' saves and implements provided ruleset
     observeEvent(input$save_ruleset, {
-      mydata(.filter_slopes(mydata(), manual_slopes(), profiles_per_patient()))
+      mydata(filter_slopes(mydata(), manual_slopes(), profiles_per_patient()))
       pk_nca_trigger(pk_nca_trigger() + 1)
     })
 
@@ -370,7 +370,7 @@ slope_selector_server <- function(
     #' and exclusions before applying them to the actual dataset.
     plot_data <- reactive({
       req(mydata(), manual_slopes(), profiles_per_patient())
-      .filter_slopes(mydata(), manual_slopes(), profiles_per_patient())
+      filter_slopes(mydata(), manual_slopes(), profiles_per_patient())
     }) %>%
       shiny::debounce(750)
 
@@ -410,7 +410,7 @@ slope_selector_server <- function(
       )
 
       # Check if there is any overlap with existing rules, adda new or edit accordingly
-      new_manual_slopes <- .check_slope_rule_overlap(manual_slopes(), new_slope_rule)
+      new_manual_slopes <- check_slope_rule_overlap(manual_slopes(), new_slope_rule)
 
       manual_slopes(new_manual_slopes)