Package 'teal.goshawk' reference manual

Title:	Longitudinal Visualization `teal` Modules
Description:	Modules that produce web interfaces through which longitudinal visualizations can be dynamically modified and displayed. These included box plot, correlation plot, density distribution plot, line plot, scatter plot and spaghetti plot with accompanying summary. Data are expected in ADaM structure. Requires analysis subject level (ADSL) and analysis laboratory (ADLB) data sets. Beyond core variables, Limit of Quantification flag variable (LOQFL) is expected with levels 'Y', 'N' or NA.
Authors:	Dony Unardi [aut, cre], Nick Paszty [aut], Dawid Kaledkowski [aut], Mahmoud Hallal [aut], Pawel Rucki [aut], Wenyi Liu [aut], Jeffrey Tomlinson [aut], Bali Toth [aut], Junlue Zhao [aut], Maciej Nasinski [aut], Maximilian Mordig [ctb], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer:	Dony Unardi <[email protected]>
License:	Apache License 2.0 \| file LICENSE
Version:	0.6.1.9000
Built:	2026-10-14 22:50:45 UTC
Source:	https://github.com/insightsengineering/teal.goshawk

helper for writing arm mapping and ordering code.

Description

Provides lines of code for left hand side of arm mapping. user must provide right hand side

Usage

maptrt(df_armvar, code = c("M", "O"))
maptrt(df_armvar, code = c("M", "O"))

Arguments

df_armvar

the dataframe and column name containing treatment code. e.g. ADSL$ARMCD

code

controls whether mapping or ordering code is written to console. Valid values: "M" and "O".

Details

SPA configure study specific pre-processing for deploying goshawk. writing the code for ARM mapping and ordering is tedious. this function helps to get that started by providing the left hand side of the mapping and ordering syntax. call the function and then copy and paste the resulting code from the console into the app.R file.

Value

Data frame with the unique treatment codes. The function prints the left hand side of the mapping or ordering code to the console.

Examples

ADSL <- teal.data::rADSL

# get treatment mapping code
maptrt(df_armvar = ADSL$ARMCD, code = "M")

# get treatment ordering code
maptrt(df_armvar = ADSL$ARMCD, code = "O")
ADSL <- teal.data::rADSL

# get treatment mapping code
maptrt(df_armvar = ADSL$ARMCD, code = "M")

# get treatment ordering code
maptrt(df_armvar = ADSL$ARMCD, code = "O")

Box Plot

Description

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 = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  yaxis_var = teal.picks::variables(c("AVAL", "CHG"), "AVAL"),
  xaxis_var = teal.picks::variables("AVISITCD", "AVISITCD"),
  facet_var = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  trt_group = teal.picks::variables(selected = "ARM"),
  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(),
  decorators = list()
)
tm_g_gh_boxplot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  yaxis_var = teal.picks::variables(c("AVAL", "CHG"), "AVAL"),
  xaxis_var = teal.picks::variables("AVISITCD", "AVISITCD"),
  facet_var = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  trt_group = teal.picks::variables(selected = "ARM"),
  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(),
  decorators = list()
)

Arguments

label

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

dataname

(character(1)) analysis data passed to the data argument of teal::init(). E.g. ADaM structured laboratory data frame ADLB.

param_var

(character(1)) name of variable containing biomarker codes e.g. PARAMCD.

param

(teal.picks::picks() or teal.transform::choices_selected()) biomarker selected.

yaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on y-axis e.g. AVAL.

xaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on x-axis e.g. BASE.

(variables or choices_selected) object with available choices and pre-selected option for variable names representing facet variable e.g. AVISITCD.

trt_group

(teal.picks::variables() or legacy teal.transform::choices_selected()) object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.

color_manual

(named character, optional) vector of colors applied to treatment values.

shape_manual

(named numeric, optional) vector of symbols applied to LOQ values.

(integer(1)) numeric value indicating number of facets per row.

loq_legend

(logical(1)) loq legend toggle.

rotate_xlab

(logical(1)) 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

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

hline_arb_label

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

hline_vars

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

hline_vars_colors

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

hline_vars_labels

(character) a character vector naming the labels for the additional horizontal lines that will appear in the plot.

plot_height

(numeric(3)) controls plot height.

plot_width

(numeric(3), optional) controls plot width.

font_size

(numeric(3)) font size control for title, x-axis label, y-axis label and legend.

dot_size

(numeric(3)) plot dot size.

alpha

(numeric(3)) 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").

decorators

(named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

See section "Decorating Module" below for more details.

Value

A teal::module() object that can be used in a teal::init() call.

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

plot (ggplot)

A Decorator is applied to the specific output using a named list of teal_transform_module objects. The name of this list corresponds to the name of the output to which the decorator is applied. See code snippet below:

tm_g_gh_boxplot(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...) # applied only to `plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.goshawk").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

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:

vignette("reportable-shiny-application", package = "teal.reporter")
vignette("adding-support-for-reporting-to-custom-modules", package = "teal")

Author(s)

Jeff Tomlinson

Balazs Toth

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"
  )
  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()

  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 = 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")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# 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"
  )
  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()

  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 = 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")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Scatter Plot Teal Module For Biomarker Analysis

Description

Scatter Plot Teal Module For Biomarker Analysis

Usage

tm_g_gh_correlationplot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  xaxis_param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  xaxis_var = teal.picks::variables(c("AVAL", "BASE", "CHG", "PCHG"), "BASE"),
  yaxis_param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "CRP", multiple = FALSE), check_dataset = FALSE),
  yaxis_var = teal.picks::variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
  trt_group = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  color_manual = NULL,
  shape_manual = NULL,
  facet_ncol = 2,
  visit_facet = TRUE,
  trt_facet = FALSE,
  reg_line = FALSE,
  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,
  vline_arb = numeric(0),
  vline_arb_color = "red",
  vline_arb_label = "Vertical line",
  vline_vars = character(0),
  vline_vars_colors = "green",
  vline_vars_labels = vline_vars,
  plot_height = c(500, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  dot_size = c(1, 1, 12),
  reg_text_size = c(3, 3, 10),
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)
tm_g_gh_correlationplot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  xaxis_param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  xaxis_var = teal.picks::variables(c("AVAL", "BASE", "CHG", "PCHG"), "BASE"),
  yaxis_param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "CRP", multiple = FALSE), check_dataset = FALSE),
  yaxis_var = teal.picks::variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
  trt_group = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  color_manual = NULL,
  shape_manual = NULL,
  facet_ncol = 2,
  visit_facet = TRUE,
  trt_facet = FALSE,
  reg_line = FALSE,
  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,
  vline_arb = numeric(0),
  vline_arb_color = "red",
  vline_arb_label = "Vertical line",
  vline_vars = character(0),
  vline_vars_colors = "green",
  vline_vars_labels = vline_vars,
  plot_height = c(500, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  dot_size = c(1, 1, 12),
  reg_text_size = c(3, 3, 10),
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)

Arguments

label

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

dataname

(character(1)) analysis data passed to the data argument of teal::init(). E.g. ADaM structured laboratory data frame ADLB.

param_var

(character(1)) name of variable containing biomarker codes e.g. PARAMCD.

xaxis_param

(teal.picks::picks() or legacy teal.transform::choices_selected()) biomarker selected for x-axis.

xaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on x-axis e.g. BASE.

yaxis_param

(teal.picks::picks() or legacy teal.transform::choices_selected()) biomarker selected for y-axis.

yaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on y-axis e.g. AVAL.

trt_group

(teal.picks::variables() or legacy teal.transform::choices_selected()) object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.

color_manual

(named character, optional) vector of colors applied to treatment values.

shape_manual

(named numeric, optional) vector of symbols applied to LOQ values.

(integer(1)) numeric value indicating number of facets per row.

visit_facet

(logical(1)) visit facet toggle.

trt_facet

(logical(1)) facet by treatment group trt_group.

reg_line

(logical(1)) include regression line and annotations for slope and coefficient in visualization. Use with facet TRUE.

loq_legend

(logical(1)) loq legend toggle.

rotate_xlab

(logical(1)) 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

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

hline_arb_label

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

hline_vars

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

hline_vars_colors

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

hline_vars_labels

(character) a character vector naming the labels for the additional horizontal lines that will appear in the plot.

vline_arb

(numeric) vector of at most 2 values identifying intercepts for arbitrary vertical lines.

vline_arb_color

(character) a character vector of at most length of vline_arb. naming the color for the arbitrary vertical lines.

vline_arb_label

(character) a character vector of at most length of vline_arb. naming the label for the arbitrary vertical lines.

vline_vars

(character) a character vector to name the columns that will define additional vertical lines.

vline_vars_colors

(character) a character vector naming the colors for the additional vertical lines.

vline_vars_labels

(character) a character vector naming the labels for the additional vertical lines that will appear in the plot.

plot_height

(numeric(3)) controls plot height.

plot_width

(numeric(3), optional) controls plot width.

font_size

(numeric(3)) font size control for title, x-axis label, y-axis label and legend.

dot_size

(numeric(3)) plot dot size.

reg_text_size

(numeric(3)) font size control for regression line annotations.

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").

decorators

(named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

See section "Decorating Module" below for more details.

Value

A teal::module() object that can be used in a teal::init() call.

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

plot (ggplot)

tm_g_gh_correlationplot(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...) # applied only to `plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.goshawk").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Reporting

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

vignette("reportable-shiny-application", package = "teal.reporter")
vignette("adding-support-for-reporting-to-custom-modules", package = "teal")

Author(s)

Nick Paszty

Balazs Toth

Examples

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(data, {
  library(dplyr)
  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"
  )
  .color_manual <- c("150mg QD" = "#000000", "Placebo" = "#3498DB", "Combination" = "#E74C3C")
  # assign LOQ flag symbols: circles for "N" and triangles for "Y", squares for "NA"
  .shape_manual <- c("N" = 1, "Y" = 2, "NA" = 0)

  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",
          trimws(
            substr(
              AVISIT,
              start = 6,
              stop = str_locate(AVISIT, "DAY") - 1
            )
          )
        ),
      TRUE ~ NA_character_
    )) %>%
    mutate(AVISITCDN = case_when(
      AVISITCD == "SCR" ~ -2,
      AVISITCD == "BL" ~ 0,
      grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
      TRUE ~ NA_real_
    )) %>%
    # use ARMCD values to order treatment in visualization legend
    mutate(TRTORD = ifelse(grepl("C", ARMCD), 1,
      ifelse(grepl("B", ARMCD), 2,
        ifelse(grepl("A", ARMCD), 3, NA)
      )
    )) %>%
    mutate(ARM = as.character(.arm_mapping[match(ARM, names(.arm_mapping))])) %>%
    mutate(ARM = factor(ARM) %>%
      reorder(TRTORD)) %>%
    mutate(
      ANRHI = case_when(
        PARAMCD == "ALT" ~ 60,
        PARAMCD == "CRP" ~ 70,
        PARAMCD == "IGA" ~ 80,
        TRUE ~ NA_real_
      ),
      ANRLO = case_when(
        PARAMCD == "ALT" ~ 20,
        PARAMCD == "CRP" ~ 30,
        PARAMCD == "IGA" ~ 40,
        TRUE ~ NA_real_
      )
    ) %>%
    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[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"
  attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"

  # add LLOQ and ULOQ variables
  ADLB_LOQS <- .h_identify_loq_values(ADLB, "LOQFL")
  ADLB <- left_join(ADLB, ADLB_LOQS, by = "PARAM")
})

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

app <- init(
  data = data,
  modules = modules(
    tm_g_gh_correlationplot(
      label = "Correlation Plot",
      dataname = "ADLB",
      xaxis_param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      yaxis_param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "CRP", multiple = FALSE),
        check_dataset = FALSE
      ),
      xaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "BASE"),
      yaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      color_manual = c(
        "Drug X 100mg" = "#000000",
        "Placebo" = "#3498DB",
        "Combination 100mg" = "#E74C3C"
      ),
      shape_manual = c("N" = 1, "Y" = 2, "NA" = 0),
      plot_height = c(500, 200, 2000),
      facet_ncol = 2,
      visit_facet = TRUE,
      reg_line = FALSE,
      loq_legend = TRUE,
      font_size = c(12, 8, 20),
      dot_size = c(1, 1, 12),
      reg_text_size = c(3, 3, 10),
      hline_arb = c(40, 50),
      hline_arb_label = "arb hori label",
      hline_arb_color = c("red", "blue"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("green", "blue", "purple", "cyan"),
      hline_vars_labels = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      vline_vars_colors = c("yellow", "orange", "brown", "gold"),
      vline_vars_labels = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_arb = c(50, 70),
      vline_arb_label = "arb vert A",
      vline_arb_color = c("green", "orange")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(data, {
  library(dplyr)
  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"
  )
  .color_manual <- c("150mg QD" = "#000000", "Placebo" = "#3498DB", "Combination" = "#E74C3C")
  # assign LOQ flag symbols: circles for "N" and triangles for "Y", squares for "NA"
  .shape_manual <- c("N" = 1, "Y" = 2, "NA" = 0)

  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",
          trimws(
            substr(
              AVISIT,
              start = 6,
              stop = str_locate(AVISIT, "DAY") - 1
            )
          )
        ),
      TRUE ~ NA_character_
    )) %>%
    mutate(AVISITCDN = case_when(
      AVISITCD == "SCR" ~ -2,
      AVISITCD == "BL" ~ 0,
      grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
      TRUE ~ NA_real_
    )) %>%
    # use ARMCD values to order treatment in visualization legend
    mutate(TRTORD = ifelse(grepl("C", ARMCD), 1,
      ifelse(grepl("B", ARMCD), 2,
        ifelse(grepl("A", ARMCD), 3, NA)
      )
    )) %>%
    mutate(ARM = as.character(.arm_mapping[match(ARM, names(.arm_mapping))])) %>%
    mutate(ARM = factor(ARM) %>%
      reorder(TRTORD)) %>%
    mutate(
      ANRHI = case_when(
        PARAMCD == "ALT" ~ 60,
        PARAMCD == "CRP" ~ 70,
        PARAMCD == "IGA" ~ 80,
        TRUE ~ NA_real_
      ),
      ANRLO = case_when(
        PARAMCD == "ALT" ~ 20,
        PARAMCD == "CRP" ~ 30,
        PARAMCD == "IGA" ~ 40,
        TRUE ~ NA_real_
      )
    ) %>%
    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[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"
  attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"

  # add LLOQ and ULOQ variables
  ADLB_LOQS <- .h_identify_loq_values(ADLB, "LOQFL")
  ADLB <- left_join(ADLB, ADLB_LOQS, by = "PARAM")
})

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

app <- init(
  data = data,
  modules = modules(
    tm_g_gh_correlationplot(
      label = "Correlation Plot",
      dataname = "ADLB",
      xaxis_param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      yaxis_param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "CRP", multiple = FALSE),
        check_dataset = FALSE
      ),
      xaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "BASE"),
      yaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      color_manual = c(
        "Drug X 100mg" = "#000000",
        "Placebo" = "#3498DB",
        "Combination 100mg" = "#E74C3C"
      ),
      shape_manual = c("N" = 1, "Y" = 2, "NA" = 0),
      plot_height = c(500, 200, 2000),
      facet_ncol = 2,
      visit_facet = TRUE,
      reg_line = FALSE,
      loq_legend = TRUE,
      font_size = c(12, 8, 20),
      dot_size = c(1, 1, 12),
      reg_text_size = c(3, 3, 10),
      hline_arb = c(40, 50),
      hline_arb_label = "arb hori label",
      hline_arb_color = c("red", "blue"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("green", "blue", "purple", "cyan"),
      hline_vars_labels = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      vline_vars_colors = c("yellow", "orange", "brown", "gold"),
      vline_vars_labels = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_arb = c(50, 70),
      vline_arb_label = "arb vert A",
      vline_arb_color = c("green", "orange")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Density Distribution Plot

Description

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

Usage

tm_g_gh_density_distribution_plot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  xaxis_var = teal.picks::variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
  trt_group = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  color_manual = NULL,
  color_comb = NULL,
  plot_height = c(500, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  line_size = c(1, 0.25, 3),
  hline_arb = numeric(0),
  hline_arb_color = "red",
  hline_arb_label = "Horizontal line",
  facet_ncol = 2L,
  comb_line = TRUE,
  rotate_xlab = FALSE,
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)
tm_g_gh_density_distribution_plot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  xaxis_var = teal.picks::variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
  trt_group = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  color_manual = NULL,
  color_comb = NULL,
  plot_height = c(500, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  line_size = c(1, 0.25, 3),
  hline_arb = numeric(0),
  hline_arb_color = "red",
  hline_arb_label = "Horizontal line",
  facet_ncol = 2L,
  comb_line = TRUE,
  rotate_xlab = FALSE,
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)

Arguments

label

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

dataname

(character(1)) analysis data passed to the data argument of teal::init(). E.g. ADaM structured laboratory data frame ADLB.

param_var

(character(1)) name of variable containing biomarker codes e.g. PARAMCD.

param

(teal.picks::picks() or teal.transform::choices_selected()) biomarker selected.

xaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on x-axis e.g. BASE.

trt_group

(teal.picks::variables() or legacy teal.transform::choices_selected()) object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.

color_manual

(named character, optional) vector of colors applied to treatment values.

color_comb

name or hex value for combined treatment color.

plot_height

(numeric(3)) controls plot height.

plot_width

(numeric(3), optional) controls plot width.

font_size

(numeric(3)) font size control for title, x-axis label, y-axis label and legend.

line_size

plot line thickness.

hline_arb

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

hline_arb_color

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

hline_arb_label

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

(integer(1)) numeric value indicating number of facets per row.

comb_line

display combined treatment line toggle.

rotate_xlab

(logical(1)) 45 degree rotation of x-axis values.

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").

decorators

(named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

See section "Decorating Module" below for more details.

Value

A teal::module() object that can be used in a teal::init() call.

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

plot (ggplot)

tm_g_gh_density_distribution_plot(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...) # applied only to `plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.goshawk").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Reporting

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

vignette("reportable-shiny-application", package = "teal.reporter")
vignette("adding-support-for-reporting-to-custom-modules", package = "teal")

Author(s)

Nick Paszty

Balazs Toth

Examples

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(data, {
  library(dplyr)
  library(stringr)

  # 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)
    )

  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_density_distribution_plot(
      label = "Density Distribution Plot",
      dataname = "ADLB",
      param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      xaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      color_manual = c(
        "150mg QD" = "#000000",
        "Placebo" = "#3498DB",
        "Combination" = "#E74C3C"
      ),
      color_comb = "#39ff14",
      comb_line = TRUE,
      plot_height = c(500, 200, 2000),
      font_size = c(12, 8, 20),
      line_size = c(1, .25, 3),
      hline_arb = c(.02, .05),
      hline_arb_color = c("red", "black"),
      hline_arb_label = c("Horizontal Line A", "Horizontal Line B")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(data, {
  library(dplyr)
  library(stringr)

  # 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)
    )

  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_density_distribution_plot(
      label = "Density Distribution Plot",
      dataname = "ADLB",
      param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      xaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      color_manual = c(
        "150mg QD" = "#000000",
        "Placebo" = "#3498DB",
        "Combination" = "#E74C3C"
      ),
      color_comb = "#39ff14",
      comb_line = TRUE,
      plot_height = c(500, 200, 2000),
      font_size = c(12, 8, 20),
      line_size = c(1, .25, 3),
      hline_arb = c(.02, .05),
      hline_arb_color = c("red", "black"),
      hline_arb_label = c("Horizontal Line A", "Horizontal Line B")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Line plot

Description

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

Usage

tm_g_gh_lineplot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  param_var_label = "PARAM",
  xaxis_var = teal.picks::variables(dplyr::starts_with("AVISIT"), "AVISITCD"),
  yaxis_var = teal.picks::variables(c("AVAL", "CHG", "PCHG"), "AVAL"),
  xvar_level = NULL,
  filter_var = lifecycle::deprecated(),
  filter_var_choices = lifecycle::deprecated(),
  trt_group = teal.picks::variables(selected = "ARM"),
  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,
  transformators = list(),
  decorators = list()
)
tm_g_gh_lineplot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  param_var_label = "PARAM",
  xaxis_var = teal.picks::variables(dplyr::starts_with("AVISIT"), "AVISITCD"),
  yaxis_var = teal.picks::variables(c("AVAL", "CHG", "PCHG"), "AVAL"),
  xvar_level = NULL,
  filter_var = lifecycle::deprecated(),
  filter_var_choices = lifecycle::deprecated(),
  trt_group = teal.picks::variables(selected = "ARM"),
  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,
  transformators = list(),
  decorators = list()
)

Arguments

label

(character(1)) Label shown in the navigation item for the module or module group. For modules() defaults to "root". See Details.

dataname

(character(1)) analysis data passed to the data argument of teal::init(). E.g. ADaM structured laboratory data frame ADLB.

param_var

(character(1)) name of variable containing biomarker codes e.g. PARAMCD.

param

(teal.picks::picks() or teal.transform::choices_selected()) biomarker selected.

param_var_label

(character(1)) single name of variable in analysis data that includes parameter labels.

xaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on x-axis e.g. BASE.

yaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on y-axis e.g. AVAL.

xvar_level

(character()) vector that can be used to define the factor level of xvar. Only use it when xaxis_var is of type character or factor.

filter_var

data constraint variable.

filter_var_choices

data constraint variable choices.

trt_group

(teal.picks::variables() or legacy teal.transform::choices_selected()) object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.

trt_group_level

(⁠named character()⁠) vector that can be used to define factor level of trt_group.

shape_choices

(character(), teal.picks::variables() or legacy teal.transform::choices_selected()) vector or teal.picks::variables() object with names of ADSL variables which can be used to change shape

stat

(character(1)) string of statistics

hline_arb

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

hline_arb_color

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

hline_arb_label

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

color_manual

(named character, optional) vector of colors applied to treatment values.

xtick

(numeric()) numeric vector to define the tick values of x-axis when x variable is numeric. Default value is waive().

xlabel

(character()) vector with same length of xtick to define the label of x-axis tick values. Default value is waive().

rotate_xlab

(logical(1)) 45 degree rotation of x-axis values.

plot_height

(numeric(3)) controls plot height.

plot_width

(numeric(3), optional) controls plot width.

plot_font_size

(numeric(3)) control font size for title, x-axis, y-axis and legend font.

dodge

(numeric(3)) 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

(numeric(1)) minimum count of observations (as listed in the output table) to plot nodes on the graph

table_font_size

(numeric(3)) controls the font size of values in the table.

dot_size

(numeric(3)) plot dot size.

plot_relative_height_value

(numeric(1)) numeric value between 500 and 5000 for controlling the starting value of the relative plot height slider

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").

decorators

(named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

See section "Decorating Module" below for more details.

Value

A teal::module() object that can be used in a teal::init() call.

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

plot (ggplot)

tm_g_gh_lineplot(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...) # applied only to `plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.goshawk").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Reporting

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

vignette("reportable-shiny-application", package = "teal.reporter")
vignette("adding-support-for-reporting-to-custom-modules", package = "teal")

Author(s)

Wenyi Liu

Balazs Toth

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 <- 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)
    )
  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 = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      shape_choices = c("SEX", "RACE"),
      xaxis_var = variables("AVISITCD", "AVISITCD"),
      yaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      hline_arb = c(20.5, 19.5),
      hline_arb_color = c("red", "green"),
      hline_arb_label = c("A", "B")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# 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 <- 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)
    )
  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 = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      shape_choices = c("SEX", "RACE"),
      xaxis_var = variables("AVISITCD", "AVISITCD"),
      yaxis_var = variables(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      hline_arb = c(20.5, 19.5),
      hline_arb_color = c("red", "green"),
      hline_arb_label = c("A", "B")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Spaghetti Plot

Description

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

Usage

tm_g_gh_spaghettiplot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  param_var_label = "PARAM",
  idvar = "USUBJID",
  xaxis_var = teal.picks::variables(c("AVISITCD", "AVISIT"), "AVISITCD"),
  yaxis_var = teal.picks::variables(c("AVAL", "CHG", "PCHG"), "AVAL"),
  xaxis_var_level = NULL,
  filter_var = lifecycle::deprecated(),
  trt_group = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  trt_group_level = NULL,
  group_stats = "NONE",
  man_color = NULL,
  color_comb = NULL,
  xtick = ggplot2::waiver(),
  xlabel = xtick,
  rotate_xlab = FALSE,
  facet_ncol = 2,
  free_x = FALSE,
  plot_height = c(600, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  dot_size = c(2, 1, 12),
  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,
  alpha = c(0.8, 0, 1),
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)
tm_g_gh_spaghettiplot(
  label,
  dataname = "ADLB",
  param_var = lifecycle::deprecated(),
  param = teal.picks::picks(teal.picks::variables("PARAMCD", "PARAMCD"),
    teal.picks::values(selected = "ALT", multiple = FALSE), check_dataset = FALSE),
  param_var_label = "PARAM",
  idvar = "USUBJID",
  xaxis_var = teal.picks::variables(c("AVISITCD", "AVISIT"), "AVISITCD"),
  yaxis_var = teal.picks::variables(c("AVAL", "CHG", "PCHG"), "AVAL"),
  xaxis_var_level = NULL,
  filter_var = lifecycle::deprecated(),
  trt_group = teal.picks::variables(dplyr::starts_with("ARM"), selected = "ARM"),
  trt_group_level = NULL,
  group_stats = "NONE",
  man_color = NULL,
  color_comb = NULL,
  xtick = ggplot2::waiver(),
  xlabel = xtick,
  rotate_xlab = FALSE,
  facet_ncol = 2,
  free_x = FALSE,
  plot_height = c(600, 200, 2000),
  plot_width = NULL,
  font_size = c(12, 8, 20),
  dot_size = c(2, 1, 12),
  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,
  alpha = c(0.8, 0, 1),
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = 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 ADLB.

param_var

(character(1)) name of variable containing biomarker codes e.g. PARAMCD.

param

(teal.picks::picks() or teal.transform::choices_selected()) biomarker selected.

param_var_label

(character(1)) single name of variable in analysis data that includes parameter labels.

idvar

name of unique subject id variable.

xaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on x-axis e.g. BASE.

yaxis_var

(teal.picks::variables() or legacy teal.transform::choices_selected()) name of variable containing biomarker results displayed on y-axis e.g. AVAL.

xaxis_var_level

vector that can be used to define the factor level of xaxis_var. Only use it when xaxis_var is character or factor.

filter_var

data constraint variable.

trt_group

(teal.picks::variables() or legacy teal.transform::choices_selected()) object with available choices and pre-selected option for variable names representing treatment group e.g. ARM.

trt_group_level

(⁠named character()⁠) vector that can be used to define factor level of trt_group.

group_stats

control group mean or median overlay.

man_color

string vector representing customized colors

color_comb

name or hex value for combined treatment color.

xtick

(numeric()) numeric vector to define the tick values of x-axis when x variable is numeric. Default value is waive().

xlabel

(character()) vector with same length of xtick to define the label of x-axis tick values. Default value is waive().

rotate_xlab

(logical(1)) 45 degree rotation of x-axis values.

(integer(1)) numeric value indicating number of facets per row.

free_x

logical(1) should scales be "fixed" (FALSE) of "free" (TRUE) for x-axis in facet_wrap scales parameter.

plot_height

(numeric(3)) controls plot height.

plot_width

(numeric(3), optional) controls plot width.

font_size

(numeric(3)) font size control for title, x-axis label, y-axis label and legend.

dot_size

(numeric(3)) plot dot size.

hline_arb

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

hline_arb_color

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

hline_arb_label

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

hline_vars

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

hline_vars_colors

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

hline_vars_labels

(character) a character vector naming the labels for the additional horizontal lines that will appear in the plot.

alpha

(numeric(3)) 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").

decorators

(named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

See section "Decorating Module" below for more details.

Value

A teal::module() object that can be used in a teal::init() call.

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

plot (ggplot)

tm_g_gh_spaghettiplot(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...) # applied only to `plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.goshawk").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Reporting

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

vignette("reportable-shiny-application", package = "teal.reporter")
vignette("adding-support-for-reporting-to-custom-modules", package = "teal")

Author(s)

Wenyi Liu

Balazs Toth

Examples

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(data, {
  library(dplyr)
  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 = 30,
      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_spaghettiplot(
      label = "Spaghetti Plot",
      dataname = "ADLB",
      param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      idvar = "USUBJID",
      xaxis_var = variables(c("AVISITCD", "AVISIT"), "AVISITCD"),
      yaxis_var = variables(c("AVAL", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      color_comb = "#39ff14",
      man_color = c(
        "Combination" = "#000000",
        "Placebo" = "#fce300",
        "150mg QD" = "#5a2f5f"
      ),
      hline_arb = c(60, 50),
      hline_arb_color = c("grey", "red"),
      hline_arb_label = c("default A", "default B"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("pink", "brown", "purple", "black")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Example using ADaM structure analysis dataset.
data <- teal_data()
data <- within(data, {
  library(dplyr)
  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 = 30,
      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_spaghettiplot(
      label = "Spaghetti Plot",
      dataname = "ADLB",
      param = picks(
        variables("PARAMCD", "PARAMCD"),
        values(selected = "ALT", multiple = FALSE),
        check_dataset = FALSE
      ),
      idvar = "USUBJID",
      xaxis_var = variables(c("AVISITCD", "AVISIT"), "AVISITCD"),
      yaxis_var = variables(c("AVAL", "CHG", "PCHG"), "AVAL"),
      trt_group = variables(c("ARM", "ACTARM"), "ARM"),
      color_comb = "#39ff14",
      man_color = c(
        "Combination" = "#000000",
        "Placebo" = "#fce300",
        "150mg QD" = "#5a2f5f"
      ),
      hline_arb = c(60, 50),
      hline_arb_color = c("grey", "red"),
      hline_arb_label = c("default A", "default B"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("pink", "brown", "purple", "black")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Package 'teal.goshawk'

Help Index

helper for writing arm mapping and ordering code.

Description

Usage

Arguments

Details

Value

Examples

Box Plot

Description

Usage

Arguments

Value

Decorating Module

Reporting

Author(s)

Examples

Scatter Plot Teal Module For Biomarker Analysis

Description

Usage

Arguments

Value

Decorating Module

Reporting

Author(s)

Examples

Density Distribution Plot

Description

Usage

Arguments

Value

Decorating Module

Reporting

Author(s)

Examples

Line plot

Description

Usage

Arguments

Value

Decorating Module

Reporting

Author(s)

Examples

Spaghetti Plot

Description

Usage

Arguments

Value

Decorating Module

Reporting

Author(s)

Examples