Line plot — tm_g_gh_lineplot • teal.goshawk

This teal module renders the UI and calls the function that creates a line plot.

Usage

tm_g_gh_lineplot(
  label,
  dataname,
  param_var,
  param,
  param_var_label = "PARAM",
  xaxis_var,
  yaxis_var,
  xvar_level = NULL,
  filter_var = yaxis_var,
  filter_var_choices = filter_var,
  trt_group,
  trt_group_level = NULL,
  shape_choices = NULL,
  stat = "mean",
  hline_arb = numeric(0),
  hline_arb_color = "red",
  hline_arb_label = "Horizontal line",
  color_manual = c(getOption("ggplot2.discrete.colour"), c("#ff0000", "#008000",
    "#4ca3dd", "#8a2be2"))[1:4],
  xtick = ggplot2::waiver(),
  xlabel = xtick,
  rotate_xlab = FALSE,
  plot_height = c(600, 200, 4000),
  plot_width = NULL,
  plot_font_size = c(12, 8, 20),
  dodge = c(0.4, 0, 1),
  pre_output = NULL,
  post_output = NULL,
  count_threshold = 0,
  table_font_size = c(12, 4, 20),
  dot_size = c(2, 1, 12),
  plot_relative_height_value = 1000
)

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 ADLB.
param_var: name of variable containing biomarker codes e.g. PARAMCD.
param: biomarker selected.
param_var_label: single name of variable in analysis data that includes parameter labels.
xaxis_var: single name of variable in analysis data that is used as x-axis in the plot for the respective goshawk function.
yaxis_var: single name of variable in analysis data that is used as summary variable in the respective goshawk function.
xvar_level: vector that can be used to define the factor level of xvar. Only use it when xvar is character or factor.
filter_var: data constraint variable.
filter_var_choices: data constraint variable choices.
trt_group: choices_selected object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.
trt_group_level: vector that can be used to define factor level of trt_group.
shape_choices: Vector or choices_selected object with names of ADSL variables which can be used to change shape
stat: string of statistics
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.
color_manual: string vector representing customized colors
xtick: numeric vector to define the tick values of x-axis when x variable is numeric. Default value is waive().
xlabel: vector with same length of xtick to define the label of x-axis tick values. Default value is waive().
rotate_xlab: logical(1) value indicating whether to rotate x-axis labels.
plot_height: controls plot height.
plot_width: optional, controls plot width.
plot_font_size: control font size for title, x-axis, y-axis and legend font.
dodge: controls the position dodge of error bar
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.
count_threshold: minimum count of observations (as listed in the output table) to plot nodes on the graph
table_font_size: controls the font size of values in the table
dot_size: plot dot size.
plot_relative_height_value: numeric value between 500 and 5000 for controlling the starting value of the relative plot height slider

Value

shiny object

Author

Wenyi Liu (luiw2) wenyi.liu@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(stringr)
  library(nestcolor)

  # original ARM value = dose value
  .arm_mapping <- list(
    "A: Drug X" = "150mg QD",
    "B: Placebo" = "Placebo",
    "C: Combination" = "Combination"
  )

  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)
    )
  attr(ADLB[["ARM"]], "label") <- .var_labels[["ARM"]]
  attr(ADLB[["ACTARM"]], "label") <- .var_labels[["ACTARM"]]
})

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

app <- init(
  data = data,
  modules = modules(
    tm_g_gh_lineplot(
      label = "Line Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      shape_choices = c("SEX", "RACE"),
      xaxis_var = choices_selected("AVISITCD", "AVISITCD"),
      yaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      hline_arb = c(20.5, 19.5),
      hline_arb_color = c("red", "green"),
      hline_arb_label = c("A", "B")
    )
  )
)
#> Initializing tm_g_gh_lineplot
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}