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Box Plot

Source: R/tm_g_gh_boxplot.R
tm_g_gh_boxplot.Rd

This teal module renders the UI and calls the functions that create a box plot and accompanying summary table.

Usage 

tm_g_gh_boxplot(
  label,
  dataname,
  param_var,
  param,
  yaxis_var = teal.transform::choices_selected(c("AVAL", "CHG"), "AVAL"),
  xaxis_var = teal.transform::choices_selected("AVISITCD", "AVISITCD"),
  facet_var = teal.transform::choices_selected(c("ARM", "ACTARM"), "ARM"),
  trt_group,
  color_manual = NULL,
  shape_manual = NULL,
  facet_ncol = NULL,
  loq_legend = TRUE,
  rotate_xlab = FALSE,
  hline_arb = numeric(0),
  hline_arb_color = "red",
  hline_arb_label = "Horizontal line",
  hline_vars = character(0),
  hline_vars_colors = "green",
  hline_vars_labels = hline_vars,
  plot_height = c(600, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  dot_size = c(2, 1, 12),
  alpha = c(0.8, 0, 1),
  pre_output = NULL,
  post_output = NULL,
  transformators = list()
)

Arguments

label

menu item label of the module in the teal app.

dataname

analysis data passed to the data argument of init. E.g. ADaM structured laboratory data frame ALB.

param_var

name of variable containing biomarker codes e.g. PARAMCD.

param

list of biomarkers of interest.

yaxis_var

name of variable containing biomarker results displayed on y-axis e.g. AVAL. When not provided, it defaults to choices_selected(c("AVAL", "CHG"), "AVAL").

xaxis_var

variable to categorize the x-axis. When not provided, it defaults to choices_selected("AVISITCD", "AVISITCD").

facet_var

variable to facet the plots by. When not provided, it defaults to choices_selected(c("ARM", "ACTARM"), "ARM").

trt_group

choices_selected object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.

color_manual

vector of colors applied to treatment values.

shape_manual

vector of symbols applied to LOQ values.

facet_ncol

numeric value indicating number of facets per row.

loq_legend

loq legend toggle.

rotate_xlab

45 degree rotation of x-axis values.

hline_arb

numeric vector of at most 2 values identifying intercepts for arbitrary horizontal lines.

hline_arb_color

a character vector of at most length of hline_arb. naming the color for the arbitrary horizontal lines.

hline_arb_label

a character vector of at most length of hline_arb. naming the label for the arbitrary horizontal lines.

hline_vars

a character vector to name the columns that will define additional horizontal lines.

hline_vars_colors

a character vector naming the colors for the additional horizontal lines.

hline_vars_labels

a character vector naming the labels for the additional horizontal lines that will appear in the legend.

plot_height

controls plot height.

plot_width

optional, controls plot width.

font_size

font size control for title, x-axis label, y-axis label and legend.

dot_size

plot dot size.

alpha

numeric vector to define transparency of plotted points.

pre_output

(shiny.tag) optional,
with text placed before the output to put the output into context. For example a title.

post_output

(shiny.tag) optional, with text placed after the output to put the output into context. For example the shiny::helpText() elements are useful.

transformators

(list of teal_transform_module) that will be applied to transform module's data input. To learn more check vignette("transform-input-data", package = "teal").

Value

an module object

Reporting

This module returns an object of class teal_module, that contains a server function. Since the server function returns a teal_report object, this makes this module reportable, which means that the reporting functionality will be turned on automatically by the teal framework.

For more information on reporting in teal, see the vignettes:

Author

Jeff Tomlinson (tomlinsj) jeffrey.tomlinson@roche.com

Balazs Toth (tothb2) toth.balazs@gene.com

Examples 

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(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"
  )
  set.seed(1) # @linksto ADSL ADLB
  ADSL <- rADSL
  ADLB <- 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()

  attr(ADLB[["ARM"]], "label") <- .var_labels[["ARM"]]
  attr(ADLB[["ACTARM"]], "label") <- .var_labels[["ACTARM"]]
  attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"
  attr(ADLB[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"

  # 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_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      yaxis_var = choices_selected(c("AVAL", "BASE", "CHG"), "AVAL"),
      xaxis_var = choices_selected(c("ACTARM", "ARM", "AVISITCD", "STUDYID"), "ARM"),
      facet_var = choices_selected(c("ACTARM", "ARM", "AVISITCD", "SEX"), "AVISITCD"),
      trt_group = choices_selected(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"),
    )
  )
)
#> Initializing tm_g_gh_boxplot
if (interactive()) {
  shinyApp(app$ui, app$server)
}