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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/",
out.width = "100%"
)
# for tidyCDISC
# remotes::install_github("tidyCDISC")
```
```{r, include=FALSE}
source("scripts/os-health.R")
source("scripts/riskmetric.R")
```
# tidyCDISC <a href='https://Biogen-Inc.github.io/tidyCDISC/'><img src="man/figures/hex-tidyCDISC-170h.png" align="right"/></a>
<!-- badges: start -->
[](https://pharmaverse.org/e2eclinical/tlg/)
[](https://github.com/Biogen-Inc/tidyCDISC/actions)
[](https://openpharma.github.io/GithubMetrics/)
[](https://pharmar.github.io/riskmetric/)
[](https://app.codecov.io/gh/Biogen-Inc/tidyCDISC/tree/devel)
<!-- badges: end -->
`tidyCDISC` is a shiny app to easily create custom tables and figures from ADaM-ish data sets.
<br>
<center>
<a href="https://rinpharma.shinyapps.io/tidyCDISC/">
<img src="man/figures/demo_tidyCDISC_button_lite2dark.png" alt="Demo full tidyCDISC app" width="25%">
</a>
</center>
## Purpose
One of `tidyCDISC`'s goals is to develop clinical tables that meet table standards leveraged for submission filings, called "standard analyses". However, this is secondary to the app's primary purpose: providing rich exploratory capabilities for clinical studies. High-level features of the app allow users to produce customized tables using a point-and-click interface, examine trends in patient populations with dynamic figures, and supply visualizations that narrow in on a single patient profile.
The beauty of the application: users don't have to write a lick of code to gather abundant insights from their study data. Thus, `tidyCDISC` aims to serve a large population of clinical personnel with varying levels of programming experience. For example:
- A **clinical head**, with presumably no programming experience (but the most domain expertise) can explore results without asking a statistician or programmer to build tables & figures.
- A **statistician** can use the application to make tables / figures instantly, cutting down on excess statistical programming requests for tables that aren't required, but are "nice to see".
::: {.floating}
```{r, echo=FALSE, out.width="25%", out.extra='style="float:right; padding:10px"'}
knitr::include_graphics("man/figures/pct_95_cropped.jpg")
```
- A **statistical programmer** can use `tidyCDISC` to perform preliminary QC programming prior to writing their own code in a validated process. Users who leverage `tidyCDISC` for routine trial analysis report **significant time savings, about 95%** on average, when performing their programming duties.
:::
For a high-level overview of the app with brief 10-minute demo, please review the following presentation on `tidyCDISC`at **Shiny Conf 2022**:
<br>
<center>
[](https://www.youtube.com/watch?v=0K8PCeKDbrI)
</center>
<br>
## Scope
As previously mentioned, `tidyCDISC` can only accept data sets that conform to CDISC ADaM standards with some minor flexibility (see [upload requirements](https://Biogen-Inc.github.io/tidyCDISC/articles/x00_Data_Upload.html) for more details). At this time, the app is designed to accept `sas7bdat` files only.
If you're looking to regularly generate R code for tables, the `tidyCDISC` app offers a handy feature to export an R script for full reproducibility of analyses performed in the app.
<br>
## Usage
You can start using the demo version of the app here: [tidyCDISC](https://rinpharma.shinyapps.io/tidyCDISC/). Note the demo version disables the **Data Upload** feature and, instead, uses CDISC pilot data. If you'd like to upload your own study data, we recommend installing `tidyCDISC` from CRAN (instructions below) to run the app locally or deploy it in your preferred environment. Please review the "[Get Started](https://Biogen-Inc.github.io/tidyCDISC/articles/tidyCDISC.html)" guide to follow an example use case with the app. However, to optimize one's use of `tidyCDISC`, we highly recommend reading the following articles that take a deeper look into the topics presented in the "Get Started" tutorial:
- [00 Data Upload](https://Biogen-Inc.github.io/tidyCDISC/articles/x00_Data_Upload.html)
- [01 Table Generator](https://Biogen-Inc.github.io/tidyCDISC/articles/x01_Table_Generator.html)
- [02 Population Explorer](https://Biogen-Inc.github.io/tidyCDISC/articles/x02_Pop_Exp.html)
- [03 Individual Explorer](https://Biogen-Inc.github.io/tidyCDISC/articles/x03_Indv_Expl.html)
- [04 Filtering](https://Biogen-Inc.github.io/tidyCDISC/articles/x04_Filtering.html)
We're confident the `tidyCDISC` application can save you time. If there is some use case that `tidyCDISC` can't solve, we want to know about it. Please send the [developers](https://github.com/Biogen-Inc/tidyCDISC/issues/new) a message with your question or request!
<br>
## Install the `tidyCDISC` R package
As a reminder, you can start using the demo version of the app right now: [launch tidyCDISC](https://rinpharma.shinyapps.io/tidyCDISC/) without any installation required. However, if you choose to upload your own study data OR export & run R code from the Table Generator, you will need the `tidyCDISC` package installed on your machine. Execute the following code to install the package:
```{r, eval=FALSE}
# Install from CRAN
install.packages("tidyCDISC")
# Or install the latest dev version
remotes::install_github("Biogen-Inc/tidyCDISC")
```
With a simple `library(tidyCDISC)` you can access all the exported functions from `tidyCDISC` that help users reproduce analysis performed in the app. Or, you can run the application locally (or deploy it in an `app.R` file) using:
```{r, eval=FALSE}
# Launch the application
tidyCDISC::run_app()
```
<br>
## Staying current
`tidyCDISC` is an actively developed project, so things are frequently changing. As such, there are a number of ways to stay current with the latest changes in any user workflows & methods for new (or past) releases! First, [our blog](https://biogen-inc.github.io/tidyCDISC/articles/Blog.html) covers all the new features and squashed bugs with detailed visuals and explanations to help you get up to speed. In addition, we have a [YouTube channel](https://www.youtube.com/@tidycdiscapp768) that posts explain-er videos for special how-to's, tips, and techniques. Last, the [NEWS file](https://biogen-inc.github.io/tidyCDISC/news/index.html) is a great resource for a recap on all the changes, with links to issues and actual code changes available for your review.
<br>
<br>
<center>
[{style="width:200px;float:left;margin-left: 60px;"}](https://biogen-inc.github.io/tidyCDISC/articles/Blog.html)
[{style="width:200px;"}](https://www.youtube.com/@tidycdiscapp768)
[{style="width:200px;float:right;margin-right: 60px;"}](https://biogen-inc.github.io/tidyCDISC/news/index.html)
</center>
<br>
<br>
<br>
<br>
<br>
Happy exploring!
<br>
<br>