---
title: "Getting Started with teal"
author: "NEST CoreDev"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Getting Started with teal}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

## Introduction

`teal` is a `shiny`-based interactive exploration framework for analyzing data, with particular emphasis on CDISC clinical trial data.
`teal` applications allow their users to:

* "Pull" in data from external data sources
* Dynamically filter of data to be used in the analyses
* Generate reproducible code to regenerate the on-screen analyses
* Create and download reports containing results of analyses (for analysis modules which support reporting)

In addition, the `teal` framework provides application developers with:

* A large suite of custom-made standard analysis modules to be included in applications
* A logging framework to facilitate debugging of applications

More advanced users of the framework can also create new analysis modules which can be added into any `teal` applications.

## Your first `teal` application:

This simple `teal` application takes the `iris` and `mtcars` datasets and displays their contents:

```{r setup, include=FALSE}
library(teal)
```

```{r app}
library(teal)

app <- init(
  data = teal_data(IRIS = iris, MTCARS = mtcars),
  modules = modules(
    example_module("Module 1"),
    example_module("Module 2")
  ),
  filter = teal_slices(
    teal_slice(dataname = "IRIS", varname = "Species", selected = "setosa")
  )
) |>
  modify_title("My first teal application") |>
  modify_header(h3("My first teal application")) |>
  modify_footer(tags$div(a("Powered by teal", href = "https://insightsengineering.github.io/teal/latest-tag/")))

if (interactive()) {
  shinyApp(app$ui, app$server)
}
```

<style>
  .teal-example {
    display: none;
  }
  span:hover .teal-components {
    display: none;
  }
  span:hover .teal-example {
    display: inline-block;
  }
</style>

_Hovering_ the image shows the `teal` application generated by this code.

<!-- These images can be edited with Inkscape or online tools that handle SVG (vectorial) format  -->
<span>
  <img class="teal-components" src="images/teal-app-components.svg" alt="Example application" style="width: 100%;" />
  <img class="teal-example" src="images/teal-app-components-hover.svg" alt="Example application (hover)" style="width: 100%;" />
</span>

Every `teal` application is composed of the following elements, all of which can be controlled by the app developer by passing arguments to the `init` function:

* <span style="color: #BF37F3;">Application Title</span> _(browser's tab title)_: is the title of the application.
* <span style="color: #FB6251;">Application Header and Footer</span> _(the top and the bottom of the app)_: any content to be placed at the top and bottom of the application.
* <span style="color: #f2b73f;">Teal Modules</span> _(tabs under the header)_: tab for each module included in the application.
  * In the example code: there are two modules named "Module 1" and "Module 2".
* <span style="color: #83cc41;">Module Content</span> _(panel on the middle)_: the outputs of the currently active module.
* <span style="color: #3A88FE;">Filter Panel</span> _(panel on the right hand side)_: for filtering the data to be passed into all `teal` modules.
  * In the example code: the filter panel is being initialized with a filter for the `Species` variable in the `iris` dataset.

## Try the above app in `shinylive`

```{r shinylive_iframe, echo = FALSE, out.width = '150%', out.extra = 'style = "position: relative; z-index:1"', eval = requireNamespace("roxy.shinylive", quietly = TRUE) && knitr::is_html_output() && identical(Sys.getenv("IN_PKGDOWN"), "true")}
code <- paste0(c(
  "interactive <- function() TRUE",
  knitr::knit_code$get("app")
), collapse = "\n")
url <- roxy.shinylive::create_shinylive_url(code)
knitr::include_url(url, height = "800px")
```

## Creating your own applications

The key function to use to create your `teal` application is `init`, which requires two mandatory arguments: `data` and `modules`. There are other optional arguments for `init`, which can be used to customize the application. Please refer to the documentation for `init` for further details.

### Application data

The `data` argument in the `init` function specifies the data used in your application. All datasets which are about to be used in `teal` application must be passed through `teal_data` object.
It is also possible to specify relationships between the datasets using the `join_keys` argument but in this case the datasets are not related. See [this vignette](including-data-in-teal-applications.html) for details.
If data is not available and has to be pulled from a remote source, `init` must receive a `teal_data_module` that specifies how to obtain the desired datasets and put them into a `teal_data` object.
See [this vignette](data-as-shiny-module.html) for details.

In order to use CDISC clinical trial data in a `teal` application the `cdisc_data` function is used instead.
Custom `SDTM` standards can be handled with `teal_data` and `join_keys`.

For further details, we recommend exploring the [`teal.data`](https://insightsengineering.github.io/teal.data/) package documentation.

### Modules

The `modules` argument to `init` consists of a list of `teal` modules (which can be wrapped together using the function `modules`).
Core `teal` developers have created several universal `teal` modules that can be useful in any `teal` application.
To learn how to create your own modules, please explore [Creating Custom Modules vignette](creating-custom-modules.html).
To use our predefined modules, see the references below for links to these modules.

### Defining filters

The optional `filter` argument in `init` allows you to initialize the application with predefined filters.
For further details see [Filter Panel vignette](filter-panel.html).

### Reporting

If any of the `modules` in your `teal` application support reporting (see [`teal.reporter`](https://insightsengineering.github.io/teal.reporter/) for more details), users of your application can add the outputs of the modules to a report.
This report can then be downloaded and a special _Report Previewer_ module will be added to your application as an additional tab, where users can view and configure their reports before downloading them. See more details in [this vignette](adding-support-for-reporting.html).


### Reproducible code

`teal` hands over data with reproducible code to every module included in the application.
Note that `teal` does not display the code, that is the modules' responsibility.
For example, the `example_module` function used above shows the code in the main panel together with other outputs.
For more details see [this vignette](including-data-in-teal-applications.html).

### Embedding teal in shiny application

Advanced `shiny` users can include teal application in their `shiny` application. For further details see [teal as a module](teal-as-a-shiny-module.html).

## Where to go next

To learn more about the `teal` framework we recommend first exploring some of the available analysis modules.

For example see:

* [general analysis modules](https://insightsengineering.github.io/teal.modules.general/)
* [clinical trial reporting modules](https://insightsengineering.github.io/teal.modules.clinical/)
* [modules for analyzing `MultiAssayExperiment` objects](https://insightsengineering.github.io/teal.modules.hermes/)

For a demo of `teal` apps see:

* [The gallery of sample apps based on teal](https://insightsengineering.github.io/teal.gallery/)
* [A catalog of Tables, Listings and Graphs](https://insightsengineering.github.io/tlg-catalog/)
* [A catalog of Biomarker Analysis Templates of Tables And Graphs](https://insightsengineering.github.io/biomarker-catalog/)

The `teal` framework relies on a set of supporting packages whose documentation provides more in-depth information.
The packages which are of most interest when defining `teal`applications are:

* [`teal.data`](https://insightsengineering.github.io/teal.data/): defining data for `teal` application.
* [`teal.slice`](https://insightsengineering.github.io/teal.slice/): defining data filtering before passing into `teal` modules.
