Decorate Module Output

Introduction

The outputs produced by teal modules, like graphs or tables, are created by the module developer and look a certain way. It is hard to design an output that will satisfy every possible user, so the form of the output should be considered a default value that can be customized. Here we describe the concept of decoration, enabling the app developer to tailor outputs to their specific requirements without rewriting the original module code.

The decoration process is build upon transformation procedures, introduced in teal. While transformators are meant to edit module’s input, decorators are meant to adjust the module’s output. To distinguish the difference, modules in teal.goshawk have 2 separate parameters: transformators and decorators.

To get a complete understanding refer the following vignettes:

Transforming the input data in this vignette.
Transforming module output in this vignette.

Outputs that can be decorated

It is important to note which output objects from a given module can be decorated. The module function documentation’s Decorating Module section has this information.

You can also refer the table shown below to know which module outputs can be decorated.

Module	Output (Class)
`tm_g_gh_boxplot`	plot (`ggplot`)
`tm_g_gh_correlationplot`	plot (`ggplot`)
`tm_g_gh_density_distribution_plot`	plot (`ggplot`)
`tm_g_gh_lineplot`	plot (`ggplot`)
`tm_g_gh_spaghettiplot`	plot (`ggplot`)

Decorating `ggplot`

Here’s an example to showcase how you can edit an output of class ggplot. You can extend them using ggplot2 functions.

data <- within(teal_data(), {
  library(dplyr)
  library(nestcolor)
  library(stringr)
  # use non-exported function from goshawk
  .h_identify_loq_values <- getFromNamespace("h_identify_loq_values", "goshawk")
  # original ARM value = dose value
  .arm_mapping <- list(
    "A: Drug X" = "150mg QD",
    "B: Placebo" = "Placebo",
    "C: Combination" = "Combination"
  )
  ADSL <- teal.data::rADSL
  ADLB <- teal.data::rADLB
  .var_labels <- lapply(ADLB, function(x) attributes(x)$label)
  ADLB <- ADLB %>%
    mutate(
      AVISITCD = case_when(
        AVISIT == "SCREENING" ~ "SCR",
        AVISIT == "BASELINE" ~ "BL",
        grepl("WEEK", AVISIT) ~ paste("W", str_extract(AVISIT, "(?<=(WEEK ))[0-9]+")),
        TRUE ~ as.character(NA)
      ),
      AVISITCDN = case_when(
        AVISITCD == "SCR" ~ -2,
        AVISITCD == "BL" ~ 0,
        grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
        TRUE ~ as.numeric(NA)
      ),
      AVISITCD = factor(AVISITCD) %>% reorder(AVISITCDN),
      TRTORD = case_when(
        ARMCD == "ARM C" ~ 1,
        ARMCD == "ARM B" ~ 2,
        ARMCD == "ARM A" ~ 3
      ),
      ARM = as.character(.arm_mapping[match(ARM, names(.arm_mapping))]),
      ARM = factor(ARM) %>% reorder(TRTORD),
      ACTARM = as.character(.arm_mapping[match(ACTARM, names(.arm_mapping))]),
      ACTARM = factor(ACTARM) %>% reorder(TRTORD),
      ANRLO = 50,
      ANRHI = 75
    ) %>%
    rowwise() %>%
    group_by(PARAMCD) %>%
    mutate(LBSTRESC = ifelse(
      USUBJID %in% sample(USUBJID, 1, replace = TRUE),
      paste("<", round(runif(1, min = 25, max = 30))), LBSTRESC
    )) %>%
    mutate(LBSTRESC = ifelse(
      USUBJID %in% sample(USUBJID, 1, replace = TRUE),
      paste(">", round(runif(1, min = 70, max = 75))), LBSTRESC
    )) %>%
    ungroup()
  # add LLOQ and ULOQ variables
  ALB_LOQS <- .h_identify_loq_values(ADLB, "LOQFL")
  ADLB <- left_join(ADLB, ALB_LOQS, by = "PARAM")
})

join_keys(data) <- default_cdisc_join_keys[names(data)]

app <- init(
  data = data,
  modules = modules(
    tm_g_gh_boxplot(
      label = "Box Plot",
      dataname = "ADLB",
      param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      yaxis_var = variables(c("AVAL", "BASE", "CHG"), "AVAL"),
      xaxis_var = variables(c("ACTARM", "ARM", "AVISITCD", "STUDYID"), "ARM"),
      facet_var = variables(c("ACTARM", "ARM", "AVISITCD", "SEX"), "AVISITCD"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      loq_legend = TRUE,
      rotate_xlab = FALSE,
      hline_arb = c(60, 55),
      hline_arb_color = c("grey", "red"),
      hline_arb_label = c("default_hori_A", "default_hori_B"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("pink", "brown", "purple", "black"),
      decorators = list(plot = ggplot_caption_decorator("I am a ggplot"))
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Introduction

Outputs that can be decorated

Decorating ggplot

Decorating `ggplot`