Module Server for ADTTE Specification

This defines the server part for the ADTTE specification. The resulting data set binned_adtte_subset contains the subset of ADTTE selected by the time-to-event endpoint, joined together with the gene information extracted from specified assay and experiment, as numeric and factor columns. The factor column is created by binning the numeric column according to the quantile cutoffs specified in probs.

Usage

adtteSpecServer(
  id,
  data,
  mae_name,
  adtte_name,
  adtte_vars,
  experiment_data,
  experiment_name,
  assay,
  genes,
  probs
)

Arguments

id

(string) the shiny module id.

data

(reactive)
reactive(<teal_data>) holding all the data sets provided during app initialization after going through the filters.

mae_name

(string)
name of the MAE data used in the teal module.

adtte_name

(string)
name of the ADTTE dataset.

adtte_vars

(named list of string)
names of the variables to use in the ADTTE dataset. It should comprise elements:

• aval: the numeric time-to-event variable.

• avalu: the variable holding the unit of aval.

• is_event: the logical event variable. It needs to be TRUE when there was an observed event, and FALSE if the time is censored without observed event.

• paramcd: the character or factor parameter code variable, defining the type of time-to-event for selection in the module.

• usubjid: the subject ID variable.

experiment_data

(reactive AnyHermesData)
input experiment.

experiment_name

(reactive string)
name of the input experiment.

assay

(reactive string)
name of the assay.

genes

(reactive GeneSpec)
gene specification.

probs

(reactive numeric)
probabilities to bin the gene or gene signature into.

Value

List with the following elements:

• binned_adtte_subset: reactive containing the joined ADTTE and gene data.

• gene_col: reactive containing the string with the column name of the original numeric gene variable.

• gene_factor: string with the variable name for the binned gene data.

• time_unit: reactive string with the time unit for the current subset.

See also

adtteSpecInput() for the module UI.

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following object is masked from ‘package:testthat’:
#> 
#>     matches
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

ui <- function(id) {
  ns <- NS(id)

  teal.widgets::standard_layout(
    encoding = uiOutput(ns("encoding_ui")),
    output = verbatimTextOutput(ns("summary"))
  )
}

server <- function(id, data, filter_panel_api) {
  checkmate::assert_class(data, "reactive")
  checkmate::assert_class(shiny::isolate(data()), "teal_data")
  moduleServer(id, function(input, output, session) {
    output$encoding_ui <- renderUI({
      tags$div(
        experimentSpecInput(session$ns("experiment"), data, mae_name = "MAE"),
        assaySpecInput(session$ns("assay")),
        geneSpecInput(session$ns("genes"), funs = list(Mean = colMeans)),
        adtteSpecInput(session$ns("adtte"))
      )
    })
    experiment <- experimentSpecServer(
      "experiment",
      data = data,
      filter_panel_api = filter_panel_api,
      mae_name = "MAE"
    )
    assay <- assaySpecServer(
      "assay",
      assays = experiment$assays
    )
    genes <- geneSpecServer(
      "genes",
      funs = list(Mean = colMeans),
      gene_choices = experiment$genes
    )
    adtte <- adtteSpecServer(
      "adtte",
      data = data,
      adtte_name = "ADTTE",
      mae_name = "MAE",
      adtte_vars = list(
        aval = "AVAL",
        avalu = "AVALU",
        is_event = "is_event",
        paramcd = "PARAMCD",
        usubjid = "USUBJID"
      ),
      experiment_data = experiment$data,
      experiment_name = experiment$name,
      assay = assay,
      genes = genes,
      probs = reactive({
        0.5
      })
    )
    output$summary <- renderPrint({
      binned_adtte_subset <- adtte$binned_adtte_subset()
      summary(binned_adtte_subset)
    })
  })
}

my_app <- function() {
  data <- teal_data()
  data <- within(data, {
    ADSL <- teal.data::rADSL
    ADTTE <- teal.data::rADTTE %>%
      dplyr::mutate(is_event = .data$CNSR == 0)
    MAE <- hermes::multi_assay_experiment
  })
  join_keys(data) <- default_cdisc_join_keys[c("ADSL", "ADTTE", "MAE")]

  app <- init(
    data = data,
    modules = modules(
      module(
        label = "adtteSpec example",
        server = server,
        ui = ui,
        datanames = "all"
      )
    )
  )
  shinyApp(app$ui, app$server)
}

if (interactive()) {
  my_app()
}