facuxpalacio/divan

Shiny app for exploratory functional DIVersity ANalysis

divan

Description

divan is intended to aid researchers and students in performing exploratory functional diversity (FD) analyses. The layout is based on the steps 3-7 proposed in Palacio et al. (2022), and works mainly as an exploration and interactive data tool. To perform a rigorous functional diversity data analysis, we suggest the user referring to several packages already available.

Installation

To use this app locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/facuxpalacio/divan.git
   
   

2. Install required packages

# Navigate to the app directory
setwd("divan")

# Install necessary R packages
install.packages(c("shiny", "other_required_packages"))

Usage To run the app, open the app.R file in RStudio and click on the 'Run App' button. Alternatively, you can run the following command in your R environment:

# Load the Shiny library
library(shiny)

# Run the app
shiny::runApp()

Testing

Automated tests have been implemented to ensure the functionality of this app. To run the tests:

Navigate to the tests/ directory. Execute the test suite using your preferred testing framework.

Folder Structure

R/app.R: Contains the main Shiny app code.

data/: Stores any necessary datasets or files.

Contributing

Contributions are welcome! If you want to improve the app or fix any issues, please take a moment to review these guidelines before getting started.

How to Contribute

1. Fork the repository.
2. Create a new branch for your contributions.
3. Make changes, enhancements, or bug fixes.
4. Test your changes thoroughly.
5. Submit a pull request.

Code Style and Standards

Please follow the established code style and standards used in the project. If there are no specific guidelines, try to match the existing coding style.

Reporting Issues

If you encounter any issues or have feature requests, please open an issue in the repository. Provide as much detail as possible to help us understand and address the problem.

Pull Requests

When submitting a pull request:

• Provide a clear description of the changes made.
• Reference any related issues.
• Ensure your code is well-tested and doesn't introduce new issues.
• Follow the project's coding conventions.

Communication

For any questions or discussions, use the issue tracker or the specified communication channels.

License

The web-based application is entirely based on Shiny, an open source R package (R 4.2.3, R Core Team 2023). The full list and version of each R package used can be found in the code available at https://github.com/facuxpalacio/divan/tree/main/R - see the LICENSE file for details.

Contact

If you have any questions or suggestions, feel free to contact Facundo X. Palacio at [email protected].

divan's Issues

Comments on the main branch code and files

The code as you will see is pretty rough. My main idea was to set a draft as follows:

• Use different tabs for each step (8 tabs)
• The first tab is just the description of the protocol and link to the (future) paper
• Each tab has checkboxes for the user to check what has done or not (along headings briefly explaining what the step refers to).
• I thought to develop steps 5 and 6 a bit more to include data summaries, plots, FD metrics, etc. I'm not sure if the remaining steps are worth to include anything useful, but ideas are welcome.
• The text throughout the app is intended to be just a draft, we can refine it when the app comes to an end.

I've also uploaded two datasets, one is the classical "Iris" data and the other belongs to one of my publications. I included Iris because it has several measurements per species, so it can be thought as a trait dataset accounting for intraspecific variation.

Awaiting for your comments!

alternatives to iris data

Federico sent me a blog post on dynamic ecology that uses the iris data for an unrelated reason today, but I just noticed that it received pushback in the replies because the iris data was made famous by Fisher in some of his eugenics work. I had no idea! They suggest an alternative wheat seed dataset instead. I can replace the iris components with this one if you're ok with swapping it out?

Layout

Hey!

I was wondering if it would be better to use a dashboard instead of tabsets. This would occupy a lateral section of the page, but the general layout is much more aesthetic.

See how dashboards look:

https://rstudio.github.io/shinydashboard/

Have a good week!

Facu