Teal module for the heatmap by grade

Display the heatmap by grade as a shiny module

Usage

tm_g_heat_bygrade(
  label,
  sl_dataname,
  ex_dataname,
  ae_dataname,
  cm_dataname = NA,
  id_var,
  visit_var,
  ongo_var,
  anno_var,
  heat_var,
  conmed_var = NULL,
  fontsize = c(5, 3, 7),
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL
)

Arguments

label

(character(1))
menu item label of the module in the teal app.

sl_dataname

(character) subject level dataset name, needs to be available in the list passed to the data argument of teal::init()

ex_dataname

(character) exposures dataset name, needs to be available in the list passed to the data argument of teal::init()

ae_dataname

(character) adverse events dataset name, needs to be available in the list passed to the data argument of teal::init()

cm_dataname

(character) concomitant medications dataset name, needs to be available in the list passed to the data argument of teal::init()
specify to NA if no concomitant medications data is available

id_var

(choices_seleced) unique subject ID variable

visit_var

(choices_seleced) analysis visit variable

ongo_var

(choices_seleced) study ongoing status variable. This variable is a derived logical variable. Usually it can be derived from EOSSTT.

anno_var

(choices_seleced) annotation variable

heat_var

(choices_seleced) heatmap variable

conmed_var

(choices_seleced) concomitant medications variable, specify to NA if no concomitant medications data is available

fontsize

(numeric(1) or numeric(3))
Defines initial possible range of font-size. fontsize is set for teal.widgets::optionalSliderInputValMinMax() which controls font-size in the output plot.

plot_height

(numeric(3))
vector to indicate default value, minimum and maximum values.

plot_width

(numeric(3))
vector to indicate default value, minimum and maximum values.

Value

the teal::module() object.

Examples

data <- cdisc_data() |>
  within({
    library(dplyr)
    library(nestcolor)
    ADSL <- rADSL %>% slice(1:30)
    ADEX <- rADEX %>% filter(USUBJID %in% ADSL$USUBJID)
    ADAE <- rADAE %>% filter(USUBJID %in% ADSL$USUBJID)
    ADCM <- rADCM %>% filter(USUBJID %in% ADSL$USUBJID)
    # This preprocess is only to force legacy standard on ADCM
    ADCM <- ADCM %>%
      select(-starts_with("ATC")) %>%
      unique()
    # function to derive AVISIT from ADEX
    add_visit <- function(data_need_visit) {
      visit_dates <- ADEX %>%
        filter(PARAMCD == "DOSE") %>%
        distinct(USUBJID, AVISIT, ASTDTM) %>%
        group_by(USUBJID) %>%
        arrange(ASTDTM) %>%
        mutate(next_vis = lead(ASTDTM), is_last = ifelse(is.na(next_vis), TRUE, FALSE)) %>%
        rename(this_vis = ASTDTM)
      data_visit <- data_need_visit %>%
        select(USUBJID, ASTDTM) %>%
        left_join(visit_dates, by = "USUBJID") %>%
        filter(ASTDTM > this_vis & (ASTDTM < next_vis | is_last == TRUE)) %>%
        left_join(data_need_visit) %>%
        distinct()
      return(data_visit)
    }
    # derive AVISIT for ADAE and ADCM
    ADAE <- add_visit(ADAE)
    ADCM <- add_visit(ADCM)
    # derive ongoing status variable for ADEX
    ADEX <- ADEX %>%
      filter(PARCAT1 == "INDIVIDUAL") %>%
      mutate(ongo_status = (EOSSTT == "ONGOING"))
  })

datanames(data) <- c("ADSL", "ADEX", "ADAE", "ADCM")
join_keys(data) <- default_cdisc_join_keys[datanames(data)]

ADCM <- data[["ADCM"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_heat_bygrade(
      label = "Heatmap by grade",
      sl_dataname = "ADSL",
      ex_dataname = "ADEX",
      ae_dataname = "ADAE",
      cm_dataname = "ADCM",
      id_var = choices_selected(
        selected = "USUBJID",
        choices = c("USUBJID", "SUBJID")
      ),
      visit_var = choices_selected(
        selected = "AVISIT",
        choices = c("AVISIT")
      ),
      ongo_var = choices_selected(
        selected = "ongo_status",
        choices = c("ongo_status")
      ),
      anno_var = choices_selected(
        selected = c("SEX", "COUNTRY"),
        choices = c("SEX", "COUNTRY", "USUBJID")
      ),
      heat_var = choices_selected(
        selected = "AETOXGR",
        choices = c("AETOXGR")
      ),
      conmed_var = choices_selected(
        selected = "CMDECOD",
        choices = c("CMDECOD")
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
#> Initializing tm_g_heat_bygrade
#> Warning: 'package:nestcolor' may not be available when loading
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}