Package 'teal.osprey' reference manual

Title:	'teal' Modules for TLG Functions in Osprey
Description:	Community efforts to collect 'teal' modules for TLGs defined in 'osprey' package. Enables 'teal' app developers to create 'shiny' applications with a use of 'osprey' analysis functions.
Authors:	Nina Qi [aut, cre], Dawid Kaledkowski [aut], Chendi Liao [aut], Liming Li [aut], Konrad Pagacz [aut], Molly He [ctb], Carolyn Zhang [ctb], Tina Cho [ctb], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer:	Nina Qi <[email protected]>
License:	Apache License 2.0
Version:	0.4.0
Built:	2026-05-25 07:07:06 UTC
Source:	https://github.com/insightsengineering/teal.osprey

Automatically switch variable labels for standard `AE` variables in `AE` osprey functions `label_aevar` is deprecated and will be unexported in the next release.

Description

Automatically switch variable labels for standard AE variables in AE osprey functions label_aevar is deprecated and will be unexported in the next release.

Usage

label_aevar(x)
label_aevar(x)

Arguments

x

variable key

Helper function to plot decorated output UI

Description

Adds teal.widgets::plot_with_settings_ui()

Usage

plot_decorate_output(id)
plot_decorate_output(id)

Arguments

id

(character) id of this element

Value

An html element.

Utility function for quick filter

Description

Utility function for quick filter

Usage

quick_filter(filter_opt, ANL)
quick_filter(filter_opt, ANL)

Arguments

filter_opt

vector of string names of flag variable to filter (keep Y rows only)

ANL

input dataset

Value

a filtered dataframe

Author(s)

Carolyn Zhang (zhanc107) [email protected]

Helper server function to decorate plot output

Description

This is used in tm_g_ae_oview() and tm_g_events_term_id().

Usage

srv_g_decorate(
  id,
  plot_id = "out",
  plt = reactive(NULL),
  plot_height,
  plot_width
)
srv_g_decorate(
  id,
  plot_id = "out",
  plt = reactive(NULL),
  plot_height,
  plot_width
)

Arguments

id

(character) id of the module

plot_id

(character) id for plot output

plt

(reactive) a reactive object of graph object

plot_height

(numeric) optional vector of length three with c(value, min, max). Specifies the height of the main plot.

plot_width

(numeric) optional vector of length three with c(value, min, max). Specifies the width of the main plot and renders a slider on the plot to interactively adjust the plot width.

Teal module for the `AE` overview

Description

Display the AE overview plot as a shiny module

Usage

tm_g_ae_oview(
  label,
  dataname,
  arm_var,
  flag_var_anl,
  fontsize = c(5, 3, 7),
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  transformators = list()
)
tm_g_ae_oview(
  label,
  dataname,
  arm_var,
  flag_var_anl,
  fontsize = c(5, 3, 7),
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  transformators = 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 used in the teal module, needs to be available in the list passed to the data argument of teal::init().

arm_var

(choices_selected)
object with all available choices and the pre-selected option for variable names that can be used as arm_var. See teal.transform::choices_selected() for details. Column arm_var in the dataname has to be a factor.

flag_var_anl

(teal.transform::choices_selected) choices_selected object with variables used to count adverse event sub-groups (e.g. Serious events, Related events, etc.)

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.

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

the teal::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:

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

Examples

data <- teal_data() %>%
  within({
    library(dplyr)
    ADSL <- rADSL
    ADAE <- rADAE
    .add_event_flags <- function(dat) {
      dat <- dat %>%
        mutate(
          TMPFL_SER = AESER == "Y",
          TMPFL_REL = AEREL == "Y",
          TMPFL_GR5 = AETOXGR == "5",
          AEREL1 = (AEREL == "Y" & ACTARM == "A: Drug X"),
          AEREL2 = (AEREL == "Y" & ACTARM == "B: Placebo")
        )
      labels <- c(
        "Serious AE", "Related AE", "Grade 5 AE",
        "AE related to A: Drug X", "AE related to B: Placebo"
      )
      cols <- c("TMPFL_SER", "TMPFL_REL", "TMPFL_GR5", "AEREL1", "AEREL2")
      for (i in seq_along(labels)) {
        attr(dat[[cols[i]]], "label") <- labels[i]
      }
      dat
    }
    ADAE <- .add_event_flags(ADAE)
  })

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

ADAE <- data[["ADAE"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_ae_oview(
      label = "AE Overview",
      dataname = "ADAE",
      arm_var = choices_selected(
        selected = "ACTARM",
        choices = c("ACTARM", "ACTARMCD")
      ),
      flag_var_anl = choices_selected(
        selected = "AEREL1",
        choices = variable_choices(
          ADAE,
          c("TMPFL_SER", "TMPFL_REL", "TMPFL_GR5", "AEREL1", "AEREL2")
        ),
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

data <- teal_data() %>%
  within({
    library(dplyr)
    ADSL <- rADSL
    ADAE <- rADAE
    .add_event_flags <- function(dat) {
      dat <- dat %>%
        mutate(
          TMPFL_SER = AESER == "Y",
          TMPFL_REL = AEREL == "Y",
          TMPFL_GR5 = AETOXGR == "5",
          AEREL1 = (AEREL == "Y" & ACTARM == "A: Drug X"),
          AEREL2 = (AEREL == "Y" & ACTARM == "B: Placebo")
        )
      labels <- c(
        "Serious AE", "Related AE", "Grade 5 AE",
        "AE related to A: Drug X", "AE related to B: Placebo"
      )
      cols <- c("TMPFL_SER", "TMPFL_REL", "TMPFL_GR5", "AEREL1", "AEREL2")
      for (i in seq_along(labels)) {
        attr(dat[[cols[i]]], "label") <- labels[i]
      }
      dat
    }
    ADAE <- .add_event_flags(ADAE)
  })

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

ADAE <- data[["ADAE"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_ae_oview(
      label = "AE Overview",
      dataname = "ADAE",
      arm_var = choices_selected(
        selected = "ACTARM",
        choices = c("ACTARM", "ACTARMCD")
      ),
      flag_var_anl = choices_selected(
        selected = "AEREL1",
        choices = variable_choices(
          ADAE,
          c("TMPFL_SER", "TMPFL_REL", "TMPFL_GR5", "AEREL1", "AEREL2")
        ),
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

teal module for the `AE` by subgroups

Description

Display the AE by subgroups plot as a teal module

Usage

tm_g_ae_sub(
  label,
  dataname,
  arm_var,
  group_var,
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  fontsize = c(5, 3, 7),
  transformators = list()
)
tm_g_ae_sub(
  label,
  dataname,
  arm_var,
  group_var,
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  fontsize = c(5, 3, 7),
  transformators = 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 used in the teal module, needs to be available in the list passed to the data argument of teal::init().

arm_var

group_var

(choices_selected) subgroups variables. See teal.transform::choices_selected() for details.

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.

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.

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

the teal::module() object.

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)

Liming Li (Lil128) [email protected]

Molly He (hey59) [email protected]

Examples

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  within({
    ADSL <- rADSL
    ADAE <- rADAE
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_ae_sub(
      label = "AE by Subgroup",
      dataname = "ADAE",
      arm_var = choices_selected(
        selected = "ACTARMCD",
        choices = c("ACTARM", "ACTARMCD")
      ),
      group_var = choices_selected(
        selected = c("SEX", "REGION1", "RACE"),
        choices = c("SEX", "REGION1", "RACE")
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  within({
    ADSL <- rADSL
    ADAE <- rADAE
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_ae_sub(
      label = "AE by Subgroup",
      dataname = "ADAE",
      arm_var = choices_selected(
        selected = "ACTARMCD",
        choices = c("ACTARM", "ACTARMCD")
      ),
      group_var = choices_selected(
        selected = c("SEX", "REGION1", "RACE"),
        choices = c("SEX", "REGION1", "RACE")
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Butterfly plot Teal Module

Description

Display butterfly plot as a shiny module

Usage

tm_g_butterfly(
  label,
  dataname,
  filter_var = NULL,
  right_var,
  left_var,
  category_var,
  color_by_var,
  count_by_var,
  facet_var = NULL,
  sort_by_var = teal.transform::choices_selected(selected = "count", choices = c("count",
    "alphabetical")),
  legend_on = TRUE,
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = list()
)
tm_g_butterfly(
  label,
  dataname,
  filter_var = NULL,
  right_var,
  left_var,
  category_var,
  color_by_var,
  count_by_var,
  facet_var = NULL,
  sort_by_var = teal.transform::choices_selected(selected = "count", choices = c("count",
    "alphabetical")),
  legend_on = TRUE,
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = 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 used in the teal module, needs to be available in the list passed to the data argument of teal::init().

filter_var

(choices_selected) variable name of data filter, please see details regarding expected values, default isNULL.choices vector with filter_var choices, default is NULL

right_var

(choices_selected) dichotomization variable for right side

left_var

(choices_selected) dichotomization variable for left side

category_var

(choices_selected) category (y axis) variable

color_by_var

(choices_selected) variable defines color blocks within each bar

count_by_var

(choices_selected) variable defines how x axis is calculated

(choices_selected) variable for row facets

sort_by_var

(choices_selected) argument for order of class and term elements in table, default here is "count"

legend_on

(boolean) value for whether legend is displayed

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.

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").

Details

filter_var option is designed to work in conjunction with filtering function provided by teal (encoding panel on the right hand side of the shiny app). It can be used as quick access to predefined subsets of the domain datasets (not subject-level dataset) to be used for analysis, denoted by an value of "Y". Each variable within the filter_var_choices is expected to contain values of either "Y" or "N". If multiple variables are selected as filter_var, only observations with "Y" value in each and every selected variables will be used for subsequent analysis. Flag variables (from ADaM datasets) can be used directly as filter.

Value

the teal::module() object.

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)

Carolyn Zhang (zhanc107) [email protected]

Chendi Liao (liaoc10) [email protected]

Examples

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  eval_code("set.seed(23) # @linksto ADSL") %>%
  within({
    library(nestcolor)
    library(dplyr)
    ADSL <- rADSL
    ADAE <- rADAE
    ADSL <- mutate(ADSL, DOSE = paste(sample(1:3, n(), replace = TRUE), "UG"))
    ADAE <- mutate(
      ADAE,
      flag1 = ifelse(AETOXGR == 1, 1, 0),
      flag2 = ifelse(AETOXGR == 2, 1, 0),
      flag3 = ifelse(AETOXGR == 3, 1, 0),
      flag1_filt = rep("Y", n())
    )
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_butterfly(
      label = "Butterfly Plot",
      dataname = "ADAE",
      right_var = choices_selected(
        selected = "SEX",
        choices = c("SEX", "ARM", "RACE")
      ),
      left_var = choices_selected(
        selected = "RACE",
        choices = c("SEX", "ARM", "RACE")
      ),
      category_var = choices_selected(
        selected = "AEBODSYS",
        choices = c("AEDECOD", "AEBODSYS")
      ),
      color_by_var = choices_selected(
        selected = "AETOXGR",
        choices = c("AETOXGR", "None")
      ),
      count_by_var = choices_selected(
        selected = "# of patients",
        choices = c("# of patients", "# of AEs")
      ),
      facet_var = choices_selected(
        selected = NULL,
        choices = c("RACE", "SEX", "ARM")
      ),
      sort_by_var = choices_selected(
        selected = "count",
        choices = c("count", "alphabetical")
      ),
      legend_on = TRUE,
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  eval_code("set.seed(23) # @linksto ADSL") %>%
  within({
    library(nestcolor)
    library(dplyr)
    ADSL <- rADSL
    ADAE <- rADAE
    ADSL <- mutate(ADSL, DOSE = paste(sample(1:3, n(), replace = TRUE), "UG"))
    ADAE <- mutate(
      ADAE,
      flag1 = ifelse(AETOXGR == 1, 1, 0),
      flag2 = ifelse(AETOXGR == 2, 1, 0),
      flag3 = ifelse(AETOXGR == 3, 1, 0),
      flag1_filt = rep("Y", n())
    )
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_butterfly(
      label = "Butterfly Plot",
      dataname = "ADAE",
      right_var = choices_selected(
        selected = "SEX",
        choices = c("SEX", "ARM", "RACE")
      ),
      left_var = choices_selected(
        selected = "RACE",
        choices = c("SEX", "ARM", "RACE")
      ),
      category_var = choices_selected(
        selected = "AEBODSYS",
        choices = c("AEDECOD", "AEBODSYS")
      ),
      color_by_var = choices_selected(
        selected = "AETOXGR",
        choices = c("AETOXGR", "None")
      ),
      count_by_var = choices_selected(
        selected = "# of patients",
        choices = c("# of patients", "# of AEs")
      ),
      facet_var = choices_selected(
        selected = NULL,
        choices = c("RACE", "SEX", "ARM")
      ),
      sort_by_var = choices_selected(
        selected = "count",
        choices = c("count", "alphabetical")
      ),
      legend_on = TRUE,
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Events by Term Plot Teal Module

Description

Display Events by Term plot as a shiny module

Usage

tm_g_events_term_id(
  label,
  dataname,
  term_var,
  arm_var,
  fontsize = c(5, 3, 7),
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  transformators = list()
)
tm_g_events_term_id(
  label,
  dataname,
  term_var,
  arm_var,
  fontsize = c(5, 3, 7),
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  transformators = 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 used in the teal module, needs to be available in the list passed to the data argument of teal::init().

term_var

teal.transform::choices_selected object with all available choices and pre-selected option names that can be used to specify the term for events

arm_var

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.

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

the teal::module() object.

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)

Liming Li (lil128) [email protected]

Molly He (hey59) [email protected]

Examples

data <- teal_data() %>%
  within({
    ADSL <- rADSL
    ADAE <- rADAE
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_events_term_id(
      label = "Common AE",
      dataname = "ADAE",
      term_var = choices_selected(
        selected = "AEDECOD",
        choices = c(
          "AEDECOD", "AETERM",
          "AEHLT", "AELLT", "AEBODSYS"
        )
      ),
      arm_var = choices_selected(
        selected = "ACTARMCD",
        choices = c("ACTARM", "ACTARMCD")
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

data <- teal_data() %>%
  within({
    ADSL <- rADSL
    ADAE <- rADAE
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_events_term_id(
      label = "Common AE",
      dataname = "ADAE",
      term_var = choices_selected(
        selected = "AEDECOD",
        choices = c(
          "AEDECOD", "AETERM",
          "AEHLT", "AELLT", "AEBODSYS"
        )
      ),
      arm_var = choices_selected(
        selected = "ACTARMCD",
        choices = c("ACTARM", "ACTARMCD")
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Teal module for the heatmap by grade

Description

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,
  transformators = list()
)
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,
  transformators = list()
)

Arguments

label

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

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.

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

the teal::module() object.

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")

Examples

data <- teal_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"))
  })

join_keys(data) <- default_cdisc_join_keys[names(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)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

data <- teal_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"))
  })

join_keys(data) <- default_cdisc_join_keys[names(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)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Patient Profile plot teal module

Description

Display patient profile plot as a shiny module

Usage

tm_g_patient_profile(
  label = "Patient Profile Plot",
  patient_id,
  sl_dataname,
  ex_dataname = NA,
  ae_dataname = NA,
  rs_dataname = NA,
  cm_dataname = NA,
  lb_dataname = NA,
  sl_start_date,
  ex_var = NULL,
  ae_var = NULL,
  ae_line_col_var = NULL,
  ae_line_col_opt = NULL,
  rs_var = NULL,
  cm_var = NULL,
  lb_var = NULL,
  x_limit = "-28, 365",
  plot_height = c(1200L, 400L, 5000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = list()
)
tm_g_patient_profile(
  label = "Patient Profile Plot",
  patient_id,
  sl_dataname,
  ex_dataname = NA,
  ae_dataname = NA,
  rs_dataname = NA,
  cm_dataname = NA,
  lb_dataname = NA,
  sl_start_date,
  ex_var = NULL,
  ae_var = NULL,
  ae_line_col_var = NULL,
  ae_line_col_opt = NULL,
  rs_var = NULL,
  cm_var = NULL,
  lb_var = NULL,
  x_limit = "-28, 365",
  plot_height = c(1200L, 400L, 5000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = list()
)

Arguments

label

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

patient_id

(choices_seleced) unique subject ID variable

sl_dataname

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

ex_dataname, ae_dataname, rs_dataname, cm_dataname, lb_dataname

(character(1)) names of exposure, adverse events, response, concomitant medications, and labs datasets, respectively; must be available in the list passed to the data argument of teal::init()
set to NA (default) to omit from analysis

sl_start_date

choices_selected study start date variable, usually set to treatment start date or randomization date

ex_var

choices_selected exposure variable to plot as each line
leave unspecified or set to NULL if exposure data is not available

ae_var

choices_selected adverse event variable to plot as each line
leave unspecified or set to NULL if adverse events data is not available

ae_line_col_var

choices_selected variable for coloring AE lines
leave unspecified or set to NULL if adverse events data is not available

ae_line_col_opt

aesthetic values to map color values (named vector to map color values to each name). If not NULL, please make sure this contains all possible values for ae_line_col_var values.
leave unspecified or set to NULL if adverse events data is not available

rs_var

choices_selected response variable to plot as each line
leave unspecified or set to NULL if response data is not available

cm_var

choices_selected concomitant medication variable to plot as each line
leave unspecified or set to NULL if concomitant medications data is not available

lb_var

choices_selected lab variable to plot as each line
leave unspecified or set to NULL if labs data is not available

x_limit

a single character string with two numbers separated by a comma indicating the x-axis limit, default is "-28, 365"

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.

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").

Details

As the patient profile module plots different domains in one plot, the study day (x-axis) is derived for consistency based the start date of user's choice in the app (for example, ADSL.RANDDT or ADSL.TRTSDT):

In ADAE, ADEX, and ADCM, it would be study day based on ASTDT and/or AENDT in reference to the start date
In ADRS and ADLB, it would be study day based on ADT in reference to the start date

Value

the teal::module() object.

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)

Xuefeng Hou (houx14) [email protected]

Tina Cho (chot) [email protected]

Molly He (hey59) [email protected]

Ting Qi (qit3) [email protected]

Examples

data <- teal_data() %>%
  within({
    library(nestcolor)
    library(dplyr)
    ADSL <- rADSL
    ADAE <- rADAE %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    ADCM <- rADCM %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    # The step below is to pre-process ADCM to legacy standard
    ADCM <- ADCM %>%
      select(-starts_with("ATC")) %>%
      unique()
    ADRS <- rADRS %>% mutate(ADT = as.Date(ADTM))
    ADEX <- rADEX %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    ADLB <- rADLB %>% mutate(ADT = as.Date(ADTM), LBSTRESN = as.numeric(LBSTRESC))
  })

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

ADSL <- data[["ADSL"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_patient_profile(
      label = "Patient Profile Plot",
      patient_id = choices_selected(
        choices = unique(ADSL$USUBJID),
        selected = unique(ADSL$USUBJID)[1]
      ),
      sl_dataname = "ADSL",
      ex_dataname = "ADEX",
      ae_dataname = "ADAE",
      rs_dataname = "ADRS",
      cm_dataname = "ADCM",
      lb_dataname = "ADLB",
      sl_start_date = choices_selected(
        selected = "TRTSDTM",
        choices = c("TRTSDTM", "RANDDT")
      ),
      ex_var = choices_selected(
        selected = "PARCAT2",
        choices = "PARCAT2"
      ),
      ae_var = choices_selected(
        selected = "AEDECOD",
        choices = c("AEDECOD", "AESOC")
      ),
      ae_line_col_var = choices_selected(
        selected = "AESER",
        choices = c("AESER", "AEREL")
      ),
      ae_line_col_opt = c("Y" = "red", "N" = "blue"),
      rs_var = choices_selected(
        selected = "PARAMCD",
        choices = "PARAMCD"
      ),
      cm_var = choices_selected(
        selected = "CMDECOD",
        choices = c("CMDECOD", "CMCAT")
      ),
      lb_var = choices_selected(
        selected = "LBTESTCD",
        choices = c("LBTESTCD", "LBCAT")
      ),
      x_limit = "-28, 750",
      plot_height = c(1200, 400, 5000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

data <- teal_data() %>%
  within({
    library(nestcolor)
    library(dplyr)
    ADSL <- rADSL
    ADAE <- rADAE %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    ADCM <- rADCM %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    # The step below is to pre-process ADCM to legacy standard
    ADCM <- ADCM %>%
      select(-starts_with("ATC")) %>%
      unique()
    ADRS <- rADRS %>% mutate(ADT = as.Date(ADTM))
    ADEX <- rADEX %>% mutate(ASTDT = as.Date(ASTDTM), AENDT = as.Date(AENDTM))
    ADLB <- rADLB %>% mutate(ADT = as.Date(ADTM), LBSTRESN = as.numeric(LBSTRESC))
  })

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

ADSL <- data[["ADSL"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_patient_profile(
      label = "Patient Profile Plot",
      patient_id = choices_selected(
        choices = unique(ADSL$USUBJID),
        selected = unique(ADSL$USUBJID)[1]
      ),
      sl_dataname = "ADSL",
      ex_dataname = "ADEX",
      ae_dataname = "ADAE",
      rs_dataname = "ADRS",
      cm_dataname = "ADCM",
      lb_dataname = "ADLB",
      sl_start_date = choices_selected(
        selected = "TRTSDTM",
        choices = c("TRTSDTM", "RANDDT")
      ),
      ex_var = choices_selected(
        selected = "PARCAT2",
        choices = "PARCAT2"
      ),
      ae_var = choices_selected(
        selected = "AEDECOD",
        choices = c("AEDECOD", "AESOC")
      ),
      ae_line_col_var = choices_selected(
        selected = "AESER",
        choices = c("AESER", "AEREL")
      ),
      ae_line_col_opt = c("Y" = "red", "N" = "blue"),
      rs_var = choices_selected(
        selected = "PARAMCD",
        choices = "PARAMCD"
      ),
      cm_var = choices_selected(
        selected = "CMDECOD",
        choices = c("CMDECOD", "CMCAT")
      ),
      lb_var = choices_selected(
        selected = "LBTESTCD",
        choices = c("LBTESTCD", "LBCAT")
      ),
      x_limit = "-28, 750",
      plot_height = c(1200, 400, 5000)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Spider plot Teal Module

Description

Display spider plot as a shiny module

Usage

tm_g_spiderplot(
  label,
  dataname,
  paramcd,
  x_var,
  y_var,
  marker_var,
  line_colorby_var,
  xfacet_var = NULL,
  yfacet_var = NULL,
  vref_line = NULL,
  href_line = NULL,
  anno_txt_var = TRUE,
  legend_on = FALSE,
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = list()
)
tm_g_spiderplot(
  label,
  dataname,
  paramcd,
  x_var,
  y_var,
  marker_var,
  line_colorby_var,
  xfacet_var = NULL,
  yfacet_var = NULL,
  vref_line = NULL,
  href_line = NULL,
  anno_txt_var = TRUE,
  legend_on = FALSE,
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = 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 used in the teal module, needs to be available in the list passed to the data argument of teal::init().

paramcd

(character(1) or choices_selected)
variable value designating the studied parameter. See teal.transform::choices_selected() for details.

x_var

x-axis variables

y_var

y-axis variables

marker_var

variable dictates marker symbol

line_colorby_var

variable dictates line color

xfacet_var

variable for x facets

yfacet_var

variable for y facets

vref_line

vertical reference lines

href_line

horizontal reference lines

anno_txt_var

annotation text

legend_on

boolean value for whether legend is displayed

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.

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

the teal::module() object.

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)

Carolyn Zhang (zhanc107) [email protected]

Chendi Liao (liaoc10) [email protected]

Examples

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  within({
    library(nestcolor)
    ADSL <- rADSL
    ADTR <- rADTR
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_spiderplot(
      label = "Spider plot",
      dataname = "ADTR",
      paramcd = choices_selected(
        choices = "SLDINV",
        selected = "SLDINV"
      ),
      x_var = choices_selected(
        choices = "ADY",
        selected = "ADY"
      ),
      y_var = choices_selected(
        choices = c("PCHG", "CHG", "AVAL"),
        selected = "PCHG"
      ),
      marker_var = choices_selected(
        choices = c("SEX", "RACE", "USUBJID"),
        selected = "SEX"
      ),
      line_colorby_var = choices_selected(
        choices = c("SEX", "USUBJID", "RACE"),
        selected = "SEX"
      ),
      xfacet_var = choices_selected(
        choices = c("SEX", "ARM"),
        selected = "SEX"
      ),
      yfacet_var = choices_selected(
        choices = c("SEX", "ARM"),
        selected = "ARM"
      ),
      vref_line = "10, 37",
      href_line = "-20, 0"
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  within({
    library(nestcolor)
    ADSL <- rADSL
    ADTR <- rADTR
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_spiderplot(
      label = "Spider plot",
      dataname = "ADTR",
      paramcd = choices_selected(
        choices = "SLDINV",
        selected = "SLDINV"
      ),
      x_var = choices_selected(
        choices = "ADY",
        selected = "ADY"
      ),
      y_var = choices_selected(
        choices = c("PCHG", "CHG", "AVAL"),
        selected = "PCHG"
      ),
      marker_var = choices_selected(
        choices = c("SEX", "RACE", "USUBJID"),
        selected = "SEX"
      ),
      line_colorby_var = choices_selected(
        choices = c("SEX", "USUBJID", "RACE"),
        selected = "SEX"
      ),
      xfacet_var = choices_selected(
        choices = c("SEX", "ARM"),
        selected = "SEX"
      ),
      yfacet_var = choices_selected(
        choices = c("SEX", "ARM"),
        selected = "ARM"
      ),
      vref_line = "10, 37",
      href_line = "-20, 0"
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Teal Module for `Swimlane` Plot

Description

This is teal module that generates a swimlane plot (bar plot with markers) for ADaM data

Usage

tm_g_swimlane(
  label,
  dataname,
  bar_var,
  bar_color_var = NULL,
  sort_var = NULL,
  marker_pos_var = NULL,
  marker_shape_var = NULL,
  marker_shape_opt = NULL,
  marker_color_var = NULL,
  marker_color_opt = NULL,
  anno_txt_var = NULL,
  vref_line = NULL,
  plot_height = c(1200L, 400L, 5000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  x_label = "Time from First Treatment (Day)",
  transformators = list()
)
tm_g_swimlane(
  label,
  dataname,
  bar_var,
  bar_color_var = NULL,
  sort_var = NULL,
  marker_pos_var = NULL,
  marker_shape_var = NULL,
  marker_shape_opt = NULL,
  marker_color_var = NULL,
  marker_color_opt = NULL,
  anno_txt_var = NULL,
  vref_line = NULL,
  plot_height = c(1200L, 400L, 5000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  x_label = "Time from First Treatment (Day)",
  transformators = 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

analysis data used for plotting, needs to be available in the list passed to the data argument of teal::init(). If no markers are to be plotted in the module, "ADSL" should be the input. If markers are to be plotted, data name for the marker data should be the input

bar_var

teal.transform::choices_selected subject-level numeric variable from dataset to plot as the bar length

bar_color_var

teal.transform::choices_selected color by variable (subject-level)

sort_var

choices_selected sort by variable (subject-level)

marker_pos_var

teal.transform::choices_selected variable for marker position from marker data (Note: make sure that marker position has the same relative start day as bar length variable bar_var

marker_shape_var

teal.transform::choices_selected marker shape variable from marker data

marker_shape_opt

aesthetic values to map shape values (named vector to map shape values to each name). If not NULL, please make sure this contains all possible values for marker_shape_var values, otherwise shape will be assigned by ggplot default

marker_color_var

marker color variable from marker data

marker_color_opt

aesthetic values to map color values (named vector to map color values to each name). If not NULL, please make sure this contains all possible values for marker_color_var values, otherwise color will be assigned by ggplot default

anno_txt_var

character vector with subject-level variable names that are selected as annotation

vref_line

vertical reference lines

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.

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.

x_label

the label of the x axis

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

the teal::module() object.

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)

Ting Qi (qit3) [email protected]

Examples

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  within({
    library(nestcolor)
    library(dplyr)
    ADSL <- rADSL %>%
      mutate(TRTDURD = as.integer(TRTEDTM - TRTSDTM) + 1) %>%
      filter(STRATA1 == "A" & ARMCD == "ARM A")
    ADRS <- rADRS %>%
      filter(PARAMCD == "LSTASDI" & DCSREAS == "Death") %>%
      mutate(AVALC = DCSREAS, ADY = EOSDY) %>%
      rbind(rADRS %>% filter(PARAMCD == "OVRINV" & AVALC != "NE")) %>%
      arrange(USUBJID)
  })

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

ADSL <- data[["ADSL"]]
ADRS <- data[["ADRS"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_swimlane(
      label = "Swimlane Plot",
      dataname = "ADRS",
      bar_var = choices_selected(
        selected = "TRTDURD",
        choices = c("TRTDURD", "EOSDY")
      ),
      bar_color_var = choices_selected(
        selected = "EOSSTT",
        choices = c("EOSSTT", "ARM", "ARMCD", "ACTARM", "ACTARMCD", "SEX")
      ),
      sort_var = choices_selected(
        selected = "ACTARMCD",
        choices = c("USUBJID", "SITEID", "ACTARMCD", "TRTDURD")
      ),
      marker_pos_var = choices_selected(
        selected = "ADY",
        choices = c("ADY")
      ),
      marker_shape_var = choices_selected(
        selected = "AVALC",
        c("AVALC", "AVISIT")
      ),
      marker_shape_opt = c("CR" = 16, "PR" = 17, "SD" = 18, "PD" = 15, "Death" = 8),
      marker_color_var = choices_selected(
        selected = "AVALC",
        choices = c("AVALC", "AVISIT")
      ),
      marker_color_opt = c(
        "CR" = "green", "PR" = "blue", "SD" = "goldenrod",
        "PD" = "red", "Death" = "black"
      ),
      vref_line = c(30, 60),
      anno_txt_var = choices_selected(
        selected = c("ACTARM", "SEX"),
        choices = c(
          "ARM", "ARMCD", "ACTARM", "ACTARMCD", "AGEGR1",
          "SEX", "RACE", "COUNTRY", "DCSREAS", "DCSREASP"
        )
      )
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# Example using stream (ADaM) dataset
data <- teal_data() %>%
  within({
    library(nestcolor)
    library(dplyr)
    ADSL <- rADSL %>%
      mutate(TRTDURD = as.integer(TRTEDTM - TRTSDTM) + 1) %>%
      filter(STRATA1 == "A" & ARMCD == "ARM A")
    ADRS <- rADRS %>%
      filter(PARAMCD == "LSTASDI" & DCSREAS == "Death") %>%
      mutate(AVALC = DCSREAS, ADY = EOSDY) %>%
      rbind(rADRS %>% filter(PARAMCD == "OVRINV" & AVALC != "NE")) %>%
      arrange(USUBJID)
  })

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

ADSL <- data[["ADSL"]]
ADRS <- data[["ADRS"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_swimlane(
      label = "Swimlane Plot",
      dataname = "ADRS",
      bar_var = choices_selected(
        selected = "TRTDURD",
        choices = c("TRTDURD", "EOSDY")
      ),
      bar_color_var = choices_selected(
        selected = "EOSSTT",
        choices = c("EOSSTT", "ARM", "ARMCD", "ACTARM", "ACTARMCD", "SEX")
      ),
      sort_var = choices_selected(
        selected = "ACTARMCD",
        choices = c("USUBJID", "SITEID", "ACTARMCD", "TRTDURD")
      ),
      marker_pos_var = choices_selected(
        selected = "ADY",
        choices = c("ADY")
      ),
      marker_shape_var = choices_selected(
        selected = "AVALC",
        c("AVALC", "AVISIT")
      ),
      marker_shape_opt = c("CR" = 16, "PR" = 17, "SD" = 18, "PD" = 15, "Death" = 8),
      marker_color_var = choices_selected(
        selected = "AVALC",
        choices = c("AVALC", "AVISIT")
      ),
      marker_color_opt = c(
        "CR" = "green", "PR" = "blue", "SD" = "goldenrod",
        "PD" = "red", "Death" = "black"
      ),
      vref_line = c(30, 60),
      anno_txt_var = choices_selected(
        selected = c("ACTARM", "SEX"),
        choices = c(
          "ARM", "ARMCD", "ACTARM", "ACTARMCD", "AGEGR1",
          "SEX", "RACE", "COUNTRY", "DCSREAS", "DCSREASP"
        )
      )
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Teal Module for Waterfall Plot

Description

This is teal module that generates a waterfall plot for ADaM data

Usage

tm_g_waterfall(
  label,
  dataname_tr = "ADTR",
  dataname_rs = "ADRS",
  bar_paramcd,
  bar_var,
  bar_color_var,
  bar_color_opt = NULL,
  sort_var,
  add_label_var_sl,
  add_label_paramcd_rs,
  anno_txt_var_sl,
  anno_txt_paramcd_rs,
  facet_var,
  ytick_at = 20,
  href_line = NULL,
  gap_point_val = NULL,
  show_value = TRUE,
  plot_height = c(1200L, 400L, 5000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = list()
)
tm_g_waterfall(
  label,
  dataname_tr = "ADTR",
  dataname_rs = "ADRS",
  bar_paramcd,
  bar_var,
  bar_color_var,
  bar_color_opt = NULL,
  sort_var,
  add_label_var_sl,
  add_label_paramcd_rs,
  anno_txt_var_sl,
  anno_txt_paramcd_rs,
  facet_var,
  ytick_at = 20,
  href_line = NULL,
  gap_point_val = NULL,
  show_value = TRUE,
  plot_height = c(1200L, 400L, 5000L),
  plot_width = NULL,
  pre_output = NULL,
  post_output = NULL,
  transformators = 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_tr

tumor burden analysis data used in teal module to plot as bar height, needs to be available in the list passed to the data argument of teal::init()

dataname_rs

response analysis data used in teal module to label response parameters, needs to be available in the list passed to the data argument of teal::init()

bar_paramcd

choices_selected parameter in tumor burden data that will be plotted as bar height

bar_var

choices_selected numeric variable from dataset to plot the bar height, e.g., PCHG

bar_color_var

choices_selected color by variable (subject level), None corresponds to NULL

bar_color_opt

aesthetic values to map color values (named vector to map color values to each name). If not NULL, please make sure this contains all possible values for bar_color_var values, otherwise color will be assigned by ggplot default, please note that NULL needs to be specified in this case

sort_var

choices_selected sort by variable (subject level), None corresponds to NULL

add_label_var_sl

choices_selected add label to bars (subject level), None corresponds to NULL

add_label_paramcd_rs

choices_selected add label to bars (response dataset), None corresponds to NULL. At least one of add_label_var_sl and add_label_paramcd_rs needs to be NULL

anno_txt_var_sl

choices_selected subject level variables to be displayed in the annotation table, default is NULL

anno_txt_paramcd_rs

choices_selected analysis dataset variables to be displayed in the annotation table, default is NULL

choices_selected facet by variable (subject level), None corresponds to NULL

ytick_at

bar height axis interval, default is 20

href_line

numeric vector to plot horizontal reference lines, default is NULL

gap_point_val

singular numeric value for adding bar break when some bars are significantly higher than others, default is NULL

show_value

boolean of whether value of bar height is shown, default is TRUE

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.

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

the teal::module() object.

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)

Ting Qi (qit3) [email protected]

houx14 [email protected]

Examples

data <- teal_data() %>%
  within({
    library(nestcolor)
    ADSL <- rADSL
    ADRS <- rADRS
    ADTR <- rADTR
    ADSL$SEX <- factor(ADSL$SEX, levels = unique(ADSL$SEX))
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_waterfall(
      label = "Waterfall",
      dataname_tr = "ADTR",
      dataname_rs = "ADRS",
      bar_paramcd = choices_selected(c("SLDINV"), "SLDINV"),
      bar_var = choices_selected(c("PCHG", "AVAL"), "PCHG"),
      bar_color_var = choices_selected(c("ARMCD", "SEX"), "ARMCD"),
      bar_color_opt = NULL,
      sort_var = choices_selected(c("ARMCD", "SEX"), NULL),
      add_label_var_sl = choices_selected(c("SEX", "EOSDY"), NULL),
      add_label_paramcd_rs = choices_selected(c("BESRSPI", "OBJRSPI"), NULL),
      anno_txt_var_sl = choices_selected(c("SEX", "ARMCD", "BMK1", "BMK2"), NULL),
      anno_txt_paramcd_rs = choices_selected(c("BESRSPI", "OBJRSPI"), NULL),
      facet_var = choices_selected(c("SEX", "ARMCD", "STRATA1", "STRATA2"), NULL),
      href_line = "-30, 20"
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

data <- teal_data() %>%
  within({
    library(nestcolor)
    ADSL <- rADSL
    ADRS <- rADRS
    ADTR <- rADTR
    ADSL$SEX <- factor(ADSL$SEX, levels = unique(ADSL$SEX))
  })

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

app <- init(
  data = data,
  modules = modules(
    tm_g_waterfall(
      label = "Waterfall",
      dataname_tr = "ADTR",
      dataname_rs = "ADRS",
      bar_paramcd = choices_selected(c("SLDINV"), "SLDINV"),
      bar_var = choices_selected(c("PCHG", "AVAL"), "PCHG"),
      bar_color_var = choices_selected(c("ARMCD", "SEX"), "ARMCD"),
      bar_color_opt = NULL,
      sort_var = choices_selected(c("ARMCD", "SEX"), NULL),
      add_label_var_sl = choices_selected(c("SEX", "EOSDY"), NULL),
      add_label_paramcd_rs = choices_selected(c("BESRSPI", "OBJRSPI"), NULL),
      anno_txt_var_sl = choices_selected(c("SEX", "ARMCD", "BMK1", "BMK2"), NULL),
      anno_txt_paramcd_rs = choices_selected(c("BESRSPI", "OBJRSPI"), NULL),
      facet_var = choices_selected(c("SEX", "ARMCD", "STRATA1", "STRATA2"), NULL),
      href_line = "-30, 20"
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

Helper UI function to decorate plot output UI

Description

This is used in tm_g_ae_oview() and tm_g_events_term_id().

Usage

ui_g_decorate(
  id,
  titles = "Titles",
  footnotes = "footnotes",
  fontsize = c(5, 4, 11)
)
ui_g_decorate(
  id,
  titles = "Titles",
  footnotes = "footnotes",
  fontsize = c(5, 4, 11)
)

Arguments

id

(character) id of this module. set to NULL if you want to make it identical to the module who called it.

titles

(character) default titles

footnotes

(character) default footnotes

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.

Package 'teal.osprey'

Help Index

Automatically switch variable labels for standard AE variables in AE osprey functions label_aevar is deprecated and will be unexported in the next release.

Description

Usage

Arguments

Helper function to plot decorated output UI

Description

Usage

Arguments

Value

Utility function for quick filter

Description

Usage

Arguments

Value

Author(s)

Helper server function to decorate plot output

Description

Usage

Arguments

Teal module for the AE overview

Description

Usage

Arguments

Value

Reporting

Examples

teal module for the AE by subgroups

Description

Usage

Arguments

Value

Reporting

Author(s)

Examples

Butterfly plot Teal Module

Description

Usage

Arguments

Details

Value

Reporting

Author(s)

Examples

Events by Term Plot Teal Module

Description

Usage

Arguments

Value

Reporting

Author(s)

Examples

Teal module for the heatmap by grade

Description

Usage

Arguments

Value

Reporting

Examples

Patient Profile plot teal module

Description

Usage

Arguments

Details

Value

Reporting

Author(s)

Examples

Spider plot Teal Module

Description

Usage

Arguments

Value

Reporting

Author(s)

Examples

Teal Module for Swimlane Plot

Description

Usage

Automatically switch variable labels for standard `AE` variables in `AE` osprey functions `label_aevar` is deprecated and will be unexported in the next release.

Teal module for the `AE` overview

teal module for the `AE` by subgroups

Teal Module for `Swimlane` Plot