teal
application to use bivariate plot with various
datasets typesThis vignette will guide you through the four parts to create a
teal
application using various types of datasets using the
bivariate plot module tm_g_bivariate()
:
app
variablelibrary(teal.modules.general) # used to create the app
library(dplyr) # used to modify data sets
Inside this app 4 datasets will be used
ADSL
A wide data set with subject dataADRS
A long data set with response data for subjects at
different time points of the studyADTTE
A long data set with time to event dataADLB
A long data set with lab measurements for each
subject<- teal_data()
data <- within(data, {
data <- teal.modules.general::rADSL %>%
ADSL mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
<- teal.modules.general::rADRS
ADRS <- teal.modules.general::rADTTE
ADTTE <- teal.modules.general::rADLB %>%
ADLB mutate(CHGC = as.factor(case_when(
< 1 ~ "N",
CHG > 1 ~ "P",
CHG TRUE ~ "-"
)))
})<- c("ADSL", "ADRS", "ADTTE", "ADLB")
datanames datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]
app
variableThis is the most important section. We will use the
teal::init()
function to create an app. The data will be
handed over using teal.data::teal_data()
. The app itself
will be constructed by multiple calls of tm_g_bivariate()
using different combinations of data sets.
# configuration for the single wide dataset
<- tm_g_bivariate(
mod1 label = "Single wide dataset",
x = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]]),
selected = "BMRKR1",
fixed = FALSE
)
),y = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]]),
selected = "SEX",
multiple = FALSE,
fixed = FALSE
)
),row_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]]),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
),col_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]]),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
)
)
# configuration for the two wide datasets
<- tm_g_bivariate(
mod2 label = "Two wide datasets",
x = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]], c("BMRKR1", "AGE", "SEX", "STRATA1", "RACE")),
selected = c("BMRKR1"),
multiple = FALSE
)
),y = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]], c("COUNTRY", "AGE", "RACE")),
selected = "RACE",
multiple = FALSE
)
),row_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]]),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
),col_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]]),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
)
)
# configuration for the multiple different long datasets
<- tm_g_bivariate(
mod3 label = "Multiple different long datasets",
x = data_extract_spec(
dataname = "ADRS",
filter = filter_spec(
label = "Select endpoints:",
vars = c("PARAMCD", "AVISIT"),
choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
selected = "OVRINV - END OF INDUCTION",
multiple = TRUE
),select = select_spec(
choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
selected = "AVALC",
multiple = FALSE
)
),y = data_extract_spec(
dataname = "ADTTE",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADTTE"]], c("AVAL", "CNSR")),
selected = "AVAL",
multiple = FALSE,
fixed = FALSE
),filter = filter_spec(
label = "Select endpoint:",
vars = c("PARAMCD"),
choices = value_choices(data[["ADTTE"]], "PARAMCD", "PARAM"),
selected = "OS",
multiple = FALSE
)
),row_facet = data_extract_spec(
dataname = "ADRS",
filter = filter_spec(
label = "Select endpoints:",
vars = c("PARAMCD", "AVISIT"),
choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
selected = "OVRINV - SCREENING",
multiple = TRUE
),select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "COUNTRY", "ARM", "PARAMCD", "AVISIT")),
selected = "SEX",
multiple = FALSE,
fixed = FALSE
)
),col_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")),
selected = NULL,
multiple = FALSE,
fixed = FALSE
)
),color_settings = TRUE,
color = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),fill = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),size = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),plot_height = c(600, 200, 2000),
ggtheme = "gray"
)
# configuration for the wide and long datasets
<- tm_g_bivariate(
mod4 label = "Wide and long datasets",
x = data_extract_spec(
dataname = "ADRS",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADRS"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select response:"
),filter_spec(
vars = "AVISIT",
choices = levels(data[["ADRS"]]$AVISIT),
selected = levels(data[["ADRS"]]$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
),select = select_spec(
choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
selected = "AVALC",
multiple = FALSE,
label = "Select variable:"
)
),y = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("BMRKR1", "SEX", "AGE", "RACE", "COUNTRY")),
selected = "BMRKR1",
multiple = FALSE,
label = "Select variable:",
fixed = FALSE
)
),row_facet = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "ARMCD", "PARAMCD")),
selected = "SEX",
multiple = FALSE,
label = "Select variable:"
)
),col_facet = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "ARMCD", "PARAMCD", "AVISIT")),
selected = "ARMCD",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
)
)
# configuration for the wide and multiple long datasets
<- tm_g_bivariate(
mod5 label = "Wide and multiple long datasets",
x = data_extract_spec(
dataname = "ADRS",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADRS"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADRS"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select response:"
),filter_spec(
vars = "AVISIT",
choices = levels(data[["ADRS"]]$AVISIT),
selected = levels(data[["ADRS"]]$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
),select = select_spec(
choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
selected = "AVALC",
multiple = FALSE,
label = "Select variable:"
)
),y = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("BMRKR1", "SEX", "AGE", "RACE", "COUNTRY")),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE
)
),row_facet = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select measurement:"
),filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
),select = select_spec(
choices = "ARMCD",
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),col_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("SEX", "AGE", "RACE", "COUNTRY")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),color_settings = TRUE,
color = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),fill = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),size = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),plot_height = c(600, 200, 2000),
ggtheme = "gray"
)
# Configuration for the same long datasets (same subset)
<- tm_g_bivariate(
mod6 label = "Same long datasets (same subset)",
x = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("AVALC", "AVAL")),
selected = "AVALC",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),y = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("SEX", "RACE", "COUNTRY", "ARMCD", "BMRKR1", "BMRKR2")),
selected = "BMRKR1",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),row_facet = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("AVISIT", "PARAMCD")),
selected = "PARAMCD",
multiple = FALSE,
label = "Select variables:"
)
),col_facet = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("AVISIT", "PARAMCD")),
selected = "AVISIT",
multiple = FALSE,
label = "Select variables:"
)
)
)
# Configuration for the same datasets (different subsets)
<- tm_g_bivariate(
mod7 label = "Same datasets (different subsets)",
x = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select lab:"
),filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
),select = select_spec(
choices = "AVAL",
selected = "AVAL",
multiple = FALSE,
fixed = TRUE
)
),y = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select lab:"
),filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = FALSE,
label = "Select visit:"
)
),select = select_spec(
choices = "AVAL",
selected = "AVAL",
multiple = FALSE,
fixed = TRUE
)
),use_density = FALSE,
row_facet = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select lab:"
),filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = FALSE,
label = "Select category:"
)
),select = select_spec(
choices = variable_choices(data[["ADLB"]], c("RACE", "SEX", "ARMCD", "ACTARMCD")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),col_facet = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select lab:"
),filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = FALSE,
label = "Select category:"
)
),select = select_spec(
choices = variable_choices(data[["ADLB"]], c("RACE", "SEX", "ARMCD", "ACTARMCD")),
selected = "ARMCD",
multiple = FALSE,
fixed = FALSE,
label = "Select variables:"
)
),color_settings = TRUE,
color = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),fill = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),size = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),plot_height = c(600, 200, 2000),
ggtheme = "gray"
)
# initialize the app
<- init(
app data = data,
modules = modules(
# tm_g_bivariate ------
modules(
label = "Bivariate plot",
mod1,
mod2,
mod3,
mod4,
mod5,
mod6,
mod7
)
) )
A simple shiny::shinyApp()
call will let you run the
app. Note that app is only displayed when running this code inside an
R
session.
shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024))