Customise your static shiny

Introduction

In this vignette we will see how to edit the panelDetails object to have one more level of customisation.

Load packages

library(OmopViewer)
library(dplyr, warn.conflicts = FALSE)
library(omopgenerics, warn.conflicts = FALSE)

Mock data

We will use the incidence results obtained by the package, we can subset our reuslts using the following command:

result <- omopViewerResults |> 
  filterSettings(result_type == "incidence")

As we can see it contains data from different settings:

result |>
  settings() |>
  glimpse()
#> Rows: 18
#> Columns: 20
#> $ result_id                            <int> 19, 20, 21, 22, 23, 24, 25, 26, 2…
#> $ result_type                          <chr> "incidence", "incidence", "incide…
#> $ package_name                         <chr> "IncidencePrevalence", "Incidence…
#> $ package_version                      <chr> "1.2.0", "1.2.0", "1.2.0", "1.2.0…
#> $ group                                <chr> "denominator_cohort_name &&& outc…
#> $ strata                               <chr> "", "", "", "", "", "", "", "", "…
#> $ additional                           <chr> "incidence_start_date &&& inciden…
#> $ min_cell_count                       <chr> "5", "5", "5", "5", "5", "5", "5"…
#> $ analysis_censor_cohort_name          <chr> "None", "None", "None", "None", "…
#> $ analysis_complete_database_intervals <chr> "TRUE", "TRUE", "TRUE", "TRUE", "…
#> $ analysis_outcome_washout             <chr> "365", "365", "365", "365", "365"…
#> $ analysis_repeated_events             <chr> "FALSE", "FALSE", "FALSE", "FALSE…
#> $ denominator_age_group                <chr> "0 to 150", "0 to 150", "0 to 150…
#> $ denominator_days_prior_observation   <chr> "365", "365", "365", "365", "365"…
#> $ denominator_end_date                 <chr> "2009-12-31", "2009-12-31", "2009…
#> $ denominator_requirements_at_entry    <chr> "FALSE", "FALSE", "FALSE", "FALSE…
#> $ denominator_sex                      <chr> "Both", "Female", "Male", "Both",…
#> $ denominator_start_date               <chr> "2000-01-01", "2000-01-01", "2000…
#> $ denominator_target_cohort_name       <chr> "None", "None", "None", "None", "…
#> $ denominator_time_at_risk             <chr> "0 to Inf", "0 to Inf", "0 to Inf…

In this case we will create two incidence tabs one for the Male data and another one for the Female data, the starting point will be the default incidence tab, we can ibtain it using:

getPanel("incidence")
#> [34mIncidence[0m (OmopViewer panel)
#> • [1m icon:[0m chart-line
#> • [1m data:[0m result_type: <incidence>
#> • [1m filters:[0m 1 filters + 6 automatic filters
#> • [1m content:[0m [1;34mTidy[0m ([3mDT[0m); [1;34mTable Incidence[0m ([3mgt[0m); [1;34mPlot Incidence[0m ([3mui[0m); [1;34mPlot population[0m ([3mui[0m)

Or just producing it from the results:

panelDetailsFromResult(result = result)
#> $incidence
#> [34mIncidence[0m (OmopViewer panel)
#> • [1m icon:[0m chart-line
#> • [1m data:[0m result_type: <incidence>
#> • [1m filters:[0m 1 filters + 6 automatic filters
#> • [1m content:[0m [1;34mTidy[0m ([3mDT[0m); [1;34mTable Incidence[0m ([3mgt[0m); [1;34mPlot Incidence[0m ([3mui[0m); [1;34mPlot population[0m ([3mui[0m)

We can then define our panelDetails object using:

panelDetails <- list(
  incidence_female = getPanel("incidence"),
  incidence_male = getPanel("incidence")
)

For the moment this the only thing that will create is two panels of incidence, but with the same information, the first thing that we will do is to restrict to the corresponding data in each one of the panels:

panelDetails$incidence_female$data <- list(denominator_sex = "Female")
panelDetails$incidence_male$data <- list(denominator_sex = "Male")

We can now for example edit the title:

panelDetails$incidence_female$title <- "Incidence in Female"
panelDetails$incidence_male$title <- "Incidence in Male"

And the icons:

panelDetails$incidence_female$icon <- "venus"
panelDetails$incidence_male$icon <- "mars"

Let’s create the shiny and see how it looks like:

exportStaticApp(result = result, panelDetails = panelDetails, directory = tempdir())

We can for example remove the tidy panel for the female tab and the plot panel for the male tab like this:

panelDetails$incidence_female$content$tidy <- NULL
panelDetails$incidence_male$content$plot <- NULL

Finally we will remove the filter for denominator_sex for both panels:

panelDetails$incidence_female$exclude_filters <- c(panelDetails$incidence_female$exclude_filters, "denominator_sex")
panelDetails$incidence_male$exclude_filters <- c(panelDetails$incidence_male$exclude_filters, "denominator_sex")

We can now regenerate the shiny and see how our changes were effective:

exportStaticApp(result = result, panelDetails = panelDetails, directory = tempdir())