# FreesearchR FreesearchR website [![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14527429.svg)](https://doi.org/10.5281/zenodo.14527429) [![rhub](https://github.com/agdamsbo/FreesearchR/actions/workflows/rhub.yaml/badge.svg)](https://github.com/agdamsbo/FreesearchR/actions/workflows/rhub.yaml) [![FreesearchR](https://img.shields.io/badge/Shiny-shinyapps.io-blue?style=flat&labelColor=white&logo=RStudio&logoColor=blue)](https://agdamsbo.shinyapps.io/FreesearchR/) The [***FreesearchR***](https://app.freesearchr.org) is a simple, clinical health data exploration and analysis tool to democratise clinical research by assisting any researcher to easily evaluate and analyse data and export publication ready results. [***FreesearchR***](https://app.freesearchr.org) is free and open-source, and is [accessible in your web browser through this link](https://app.freesearchr.org). The app can also run locally, please [see below](#run-locally-on-your-own-machine-sec-run-locally). All feedback is welcome and can be shared as a GitHub issue. Any suggestions on collaboration is much welcomed. Please reach out! ![FreesearchR demo](./man/figures/demo.gif) ## Motivation This app has the following simple goals: 1. help the health clinician getting an overview of data in quality improvement projects and clinical research 1. help learners get a good start analysing data and coding in *R* 1. ease quick data overview and basic visualisations for any clinical researcher ## Run locally on your own machine The ***FreesearchR*** app can also run on your own machine with no data transmitted anywhere. Blow are the available options. ### Run from R (or RStduio) Working with data in R, FreesearchR is a quick and easy tool to get overview and perform the first explorative analyses to get you going. Any data available in the your R session will be available to the FreesearchR app. Just follow the below steps to get going: 1. **Requirement:** You need to have [*R* installed](https://www.r-project.org/) and possibly an editor like [RStudio](https://posit.co/download/rstudio-desktop/). 1. Then open the *R* console and copy/paste the following code, that will install the `{devtools}` package and then the `{FreesearchR}` *R*-package with its dependencies: ``` require("devtools") devtools::install_github("agdamsbo/FreesearchR") library(FreesearchR) # By loading mtcars to the environment, it will be available # in the interface like any other data.frame data(mtcars) launch_FreesearchR() ``` ### Running with docker compose For advanced users, wanting to deploy the FreesearchR app to run anywhere, a docker image is available. Below is the minimal `docker_compose.yml` file: ``` services: freesearchr: image: ghcr.io/agdamsbo/freesearchr:latest ports: - '3838:3838' restart: on-failure ``` ## Code of Conduct Please note that the ***FreesearchR*** project is published with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms. ## Acknowledgements Like any other project, this project was never possible without the great work of others. These are some of the sources and packages I have used: - The ***FreesearchR*** app is build with [Shiny](https://shiny.posit.co/) and based on [*R*](https://www.r-project.org/). - [gtsummary](https://www.danieldsjoberg.com/gtsummary/): superb and flexible way to create publication-ready analytical and summary tables. - [dreamRs](https://github.com/dreamRs): maintainers of a broad selection of great extensions and tools for [Shiny](https://shiny.posit.co/). - [easystats](https://easystats.github.io/easystats/): the [`performance::check_model()`](https://easystats.github.io/performance/articles/check_model.html) function was central in sparking the idea to create a data analysis tool. - [IDEAfilter](https://biogen-inc.github.io/IDEAFilter/): a visually appealing data filter function based on the [{shinyDataFilter}](https://github.com/dgkf/shinyDataFilter). This project was all written by a human and not by any AI-based tools. The online ***FreesearchR*** app contains a tracking script, transmitting minimal data on usage. No uploaded data is transmitted anywhere. Have a look at the [tracking data here](https://analytics.gdamsbo.dk/share/2i4BNpMcDMB9lJvF/agdamsbo.shinyapps.io). No tracking data is sent running the app locally (see above).