yurasong/project-template

Template for project directory structure.

Project Title

One paragraph describing the project.

Set up new project with RStudio

This template is loosely based on A Quick Guide to Organizing Computational Biology Projects.

To set up a new project, follow these steps:

1. Create new repo in your personal GitHub account based on this template
2. Open RStudio
3. Got to File > New Project... > Version control > Git, fill in the repository URL, copied from GitHub (click on the green button "Clone or download" to get the URL)
4. Save the project somewhere reasonable, for example in your home directory ("~/") or in a "Projects" directory under your home directory ("~/Projects")

See https://happygitwithr.com/ for further information on using Git and GitHub with RStudio.

Contents

Notebooks

All your R notebooks needed to reproduce your analyses should go here. If necessary you can also create a subdirectory "output" to store or back up any intermediate outputs of your notebooks. If your project only contains a single notebook, you might also consider putting it in the root directory of your project.

Scripts

Any scripts that you might write for your project. For example, when you write some functions that you use in multiple notebooks/analyses, you might consider putting it in a separate script that you can then load into your R notebooks. This is a great way of keeping your projects clean and avoiding mistakes that might occur when copy-and-pasting code.

Documentation

Any longer descriptions of the analyses carried out that do not fit in your notebooks should go here.

Some examples of things to put here:

• Global summary of the analyses carried out (this could potentially also go into the README.md at the project root)
• Any notes, descriptions or background information that provide more details about the analyses carried out.
• Manuscript(s) related to the project

Keep in mind that, ideally, a total stranger should be able to reproduce your analyses using only your project's repository. The doc folder is a great place to refer to in order to achieve that goal.

You might also consider adding a Lab notebook, either in this directory or the results.

Data

Any input data needed for your analyses. However, keep in mind that it's not possible to push large data objects (> 100 MB) to GitHub. If this is the case, add those objects to your .gitignore and consider providing a script or instructions to download the data (if it's in a public somewhere) instead.

Results

Any output data generated by your analyses should go here. This will generally be everything relevant to your analyses' results that is not a figure (those go in to the figures directory). You can also save any intermediate results that are used by subsequent analyses here.

Figures

All (relevant) figures generated by your analyses. This also makes it easy to add figures to any Markdown documents you might have in doc/ or in your README.md by linking to this directory.