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