teal
application to use response plot with various
datasets types
This vignette will guide you through the four parts to create a
teal
application using various types of datasets using the
response plot module tm_g_response()
:
- Load libraries
- Create data sets
- Create an
app
variable - Run the app
1 - Load libraries
library(teal.modules.general) # used to create the app
library(dplyr) # used to modify data sets
2 - Create data sets
Inside this app 4 datasets will be used
-
ADSL
A wide data set with subject data -
ADRS
A long data set with response data for subjects at different time points of the study -
ADTTE
A long data set with time to event data -
ADLB
A long data set with lab measurements for each subject
data <- teal_data()
data <- within(data, {
ADSL <- teal.data::rADSL %>%
mutate(TRTDUR = round(as.numeric(TRTEDTM - TRTSDTM), 1))
ADRS <- teal.data::rADRS
ADTTE <- teal.data::rADTTE
ADLB <- teal.data::rADLB %>%
mutate(CHGC = as.factor(case_when(
CHG < 1 ~ "N",
CHG > 1 ~ "P",
TRUE ~ "-"
)))
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
3 - Create an app
variable
This 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_response()
using different combinations of data sets.
# configuration for the single wide dataset
mod1 <- tm_g_response(
label = "Single wide dataset",
response = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]], c("BMRKR2", "ITTFL", "BEP01FL")),
selected = "BMRKR2",
multiple = FALSE,
fixed = FALSE
)
),
x = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]], c("SEX", "RACE", "COUNTRY", "ARMCD", "STRATA1")),
selected = "ARMCD",
multiple = FALSE,
fixed = FALSE
)
)
)
# configuration for the two wide datasets
mod2 <- tm_g_response(
label = "Two wide datasets",
response = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]], c("BMRKR2", "ITTFL", "BEP01FL")),
selected = "BMRKR2",
multiple = FALSE
)
),
x = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = c("SEX", "COUNTRY", "RACE", "STRATA1", "ARMCD"),
selected = "ARMCD",
multiple = FALSE
)
)
)
# configuration for the multiple long datasets
mod3 <- tm_g_response(
label = "Multiple long datasets",
response = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
label = "Select parameter:",
vars = "PARAMCD",
choices = levels(data[["ADLB"]]$PARAMCD),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE
),
filter_spec(
label = "Select visit:",
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[1],
multiple = FALSE
)
),
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADLB"]], c("BMRKR2", "ITTFL", "BEP01FL")),
selected = "BMRKR2",
multiple = FALSE
)
),
x = data_extract_spec(
dataname = "ADRS",
filter = list(
filter_spec(
label = "Select parameter:",
vars = "PARAMCD",
choices = levels(data[["ADRS"]]$PARAMCD),
selected = levels(data[["ADRS"]]$PARAMCD)[3],
multiple = FALSE
),
filter_spec(
label = "Select visit:",
vars = "AVISIT",
choices = levels(data[["ADRS"]]$AVISIT),
selected = levels(data[["ADRS"]]$AVISIT)[3],
multiple = FALSE
)
),
select = select_spec(
choices = c("AVALC", "ITTFL", "BEP01FL"),
selected = "AVALC",
multiple = FALSE,
fixed = TRUE
)
),
row_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = "SEX",
selected = NULL,
multiple = FALSE
)
),
col_facet = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["ADSL"]], c("SEX", "COUNTRY")),
selected = NULL,
multiple = FALSE
)
)
)
# configuration for the wide and long dataset
mod4 <- tm_g_response(
label = "Wide and long dataset",
response = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = levels(data[["ADLB"]]$PARAMCD),
selected = levels(data[["ADLB"]]$PARAMCD)[2],
multiple = TRUE,
label = "Select measurement:"
),
filter_spec(
vars = "AVISIT",
choices = levels(data[["ADLB"]]$AVISIT),
selected = levels(data[["ADLB"]]$AVISIT)[2],
multiple = TRUE,
label = "Select visit:"
)
),
select = select_spec(
choices = variable_choices(data[["ADLB"]], c("BMRKR2", "ITTFL", "BEP01FL")),
selected = "BMRKR2",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),
x = data_extract_spec(
dataname = "ADSL",
select = select_spec(
choices = variable_choices(data[["ADSL"]], c("ARMCD", "BMRKR1", "BMRKR2", "BEP01FL")),
selected = "BMRKR2",
multiple = FALSE,
fixed = FALSE
)
)
)
# configuration for the same long datasets (same subsets)
mod5 <- tm_g_response(
label = "Same long datasets (same subsets)",
response = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("BMRKR2", "AVALC", "BEP01FL")),
selected = "AVALC",
multiple = FALSE,
fixed = TRUE,
label = "Select variable:"
)
),
x = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = variable_choices(data[["ADRS"]], c("AVALC", "AGE", "SEX", "ARMCD", "STRATA1")),
selected = "ARMCD",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),
row_facet = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = "PARAMCD",
selected = "PARAMCD",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
),
col_facet = data_extract_spec(
dataname = "ADRS",
select = select_spec(
choices = "AVISIT",
selected = "AVISIT",
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
)
)
# configuration for the same long datasets (different subsets)
mod6 <- tm_g_response(
label = "Same long datasets (different subsets)",
response = data_extract_spec(
dataname = "ADLB",
filter = filter_spec(
vars = "PARAMCD",
choices = levels(data[["ADLB"]]$PARAMCD),
selected = levels(data[["ADLB"]]$PARAMCD)[2],
multiple = FALSE,
label = "Select lab:"
),
select = select_spec(
choices = "BMRKR2",
selected = "BMRKR2",
multiple = FALSE,
fixed = TRUE
)
),
x = data_extract_spec(
dataname = "ADLB",
filter = filter_spec(
vars = "PARAMCD",
choices = levels(data[["ADLB"]]$PARAMCD),
selected = levels(data[["ADLB"]]$PARAMCD)[1],
multiple = FALSE,
label = "Select lab:"
),
select = select_spec(
choices = variable_choices(data[["ADLB"]], c("AVISIT", "PARAMCD", "BEP01FL")),
selected = "AVISIT",
multiple = FALSE,
fixed = TRUE
)
),
row_facet = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = levels(data[["ADLB"]]$PARAMCD),
selected = levels(data[["ADLB"]]$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 = variable_choices(data[["ADLB"]], c("SEX", "RACE", "ARMCD")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select Variable"
)
),
col_facet = data_extract_spec(
dataname = "ADLB",
filter = list(
filter_spec(
vars = "PARAMCD",
choices = levels(data[["ADLB"]]$PARAMCD),
selected = levels(data[["ADLB"]]$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 = variable_choices(data[["ADLB"]], c("SEX", "RACE", "ARMCD")),
selected = NULL,
multiple = FALSE,
fixed = FALSE,
label = "Select variable:"
)
)
)
# initialize the app
app <- init(
data = data,
modules = modules(
modules(
label = "Response plot",
mod1,
mod2,
mod3,
mod4,
mod5,
mod6
)
)
)
4 - Run the app
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))