Server function that loads the data through reactive loading and then delegates to srv_teal().

Usage

srv_teal_with_splash(id, data, modules, filter = list())

Arguments

id

(character)
module id to embed it, if provided, the server function must be called with shiny::moduleServer(); See the vignette for an example. However, ui_teal_with_splash() is then preferred to this function.

data

(TealData or TealDataset or TealDatasetConnector or list or data.frame or MultiAssayExperiment)
R6 object as returned by teal.data::cdisc_data(), teal.data::teal_data(), teal.data::cdisc_dataset(), teal.data::dataset(), teal.data::dataset_connector() or teal.data::cdisc_dataset_connector() or a single data.frame or a MultiAssayExperiment or a list of the previous objects or function returning a named list. NOTE: teal does not guarantee reproducibility of the code when names of the list elements do not match the original object names. To ensure reproducibility please use teal.data::teal_data() or teal.data::cdisc_data() with check = TRUE enabled.

modules

teal_modules object containing the output modules which will be displayed in the teal application. See modules() and module() for more details.

filter

(list)
You can define filters that show when the app starts. List names should be named according to datanames passed to the data argument. In case of data.frame` the list should be composed as follows:

list(<dataname1> = list(<varname1> = ..., <varname2> = ...),
     <dataname2> = list(...),
     ...)

For example, filters for variable Sepal.Length in iris can be specified as follows:

list(iris = list(Sepal.Length = list(selected = c(5.0, 7.0))))
# or
list(iris = list(Sepal.Length = c(5.0, 7.0)))

In case developer would like to include NA and Inf values in the filtered dataset.

list(Species = list(selected = c(5.0, 7.0), keep_na = TRUE, keep_inf = TRUE))
list(Species = c(c(5.0, 7.0), NA, Inf))

To initialize with specific variable filter with all values on start, one can use

list(Species = list())

filter should be set with respect to the class of the column:

• numeric: selected should be a two elements vector defining the range of the filter.

• Date: selected should be a two elements vector defining the date-range of the filter

• POSIXct: selected should be a two elements vector defining the datetime range of the filter

• character and factor: selected should be a vector of any length defining initial values selected to filter.
  filter for MultiAssayExperiment objects should be specified in slightly different way. Since it contains patient data with list of experiments, filter list should be created as follows:
  

list(
  <MAE dataname> = list(
    subjects = list(<column in colData> = ..., <column in colData> = ...),
    <experiment name> = list(
      subset = list(<column in rowData of experiment> = ...,
                    <column in rowData of experiment> = ...),
      select = list(<column in colData of experiment> = ...,
                    <column in colData of experiment> = ...)
    )
  )
)

By adding the filterable attribute it is possible to control which variables can be filtered for each dataset. See the example below where ADSL can only be filtered by AGE, SEX or RACE.

Value

reactive, return value of srv_teal()