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Version Control with Git
Using Git from RStudio

Learning Objectives

  • Understand how to use Git from RStudio
  • Integrating Git with existing R projects

Using Git with RStudio

Since version control is so useful when developing scripts, RStudio has built-in integration with Git. There are some more obscure Git features that you still need to use the command-line for, but RStudio has a nice interface for most common operations.

RStudio let's you create a project associated with a given directory. We have done this many times in the course so far. When we create a new project, RStudio has a feature in which we can keep track of related files using version control!

To get started using RStudio for version control, let's make a new project:

This will pop up a window asking us how we want to create the project. We have some options here. Let's say that we want to use RStudio with the planets repository that we already made. Since that repository lives in a directory on our computer, we'll choose existing directory:

Do you see a "version control" option?

Although we're not going to use it here, there should be a "version control" option on this menu. That is what you would click on if you wanted to create a project on your computer by cloning a repository from github. If that option is not present, it probably means that RStudio doesn't know where your git executable is. See this page for some debugging advice.

Next, RStudio will ask which existing directory we want to use. Click Browse to navigate to the correct directory on your computer, then click Create Project:

Ta-da! Now you have an R project containing your repository. Notice the vertical Git menu that is now on the menu bar. This means RStudio has recognized that this directory is a git repository, so it's giving you tools to use Git:

To edit the files in your repository, you can click on them from the panel in the lower right. Let's add some more information about pluto to pluto.txt:

And it's nice and out of the way.

We can also use RStudio to commit these changes. Go to the Git menu and click Commit:

This will bring up a screen where you can select which files to commit (check the boxes in the "staged" column) and enter a commit message (in the upper right). The icons in the "status" column indicate the current status of each file. You can also see the changes to each file by clicking on its name. Once everything is the way you want it, click Commit:

You can push these changes by selecting Push from the Git menu. There are also options there to pull from a remote version of the repository, and view the history:

Are the push/pull commands greyed out?

If this is the case, it generally means that RStudio doesn't know the location of any other version of your repository (i.e. the one on Github). To fix this, open a terminal to the repository and enter the command: git push -u origin master. Then restart RStudio.

If we click on "history", we can see a pretty graphical version of what git log would tell us:

RStudio creates some files that is uses to keep track of your project. You generally don't want to track these, so adding them to your .gitignore file is a good idea:

Integrating Git with an existing RStudio project

So far in this course we have created projects in RStudio, but we have not used Git integration. Now that you have seen how useful it can be, perhaps you want to go back to some your old projects and start tracking changes.

Rstudio allows for this pretty easily, and here we show you how.

  1. Open up the DEanalyis.Rproj.
  2. From the menu bar select 'Tools' -> 'Version Control' -> 'Project Setup...'

  1. This will open up the 'Project Options' box. From the pull-down menu select Git. You will then be asked to confirm creating a new repository and asked to restart RStudio.

Now in the top right panel (Environment/History) of RStudio you will see a tab for Git. You can now get started with version control on any of your existing script/markdown files!

NOTE: When using Git versioning for R projects for your NGS Data Analysis it is best practice not to commit your data files. Binary files in particular will be problematic, as Git is designed to track text changes not data. Thus, adding data file extensions (i.e .bam) or folders which only contain data files in your .gitignore can be very useful so those files are not accidently tracked.

Git Large File Storage (LFS)

There may be large files that you want to track (i.e PDF, rda, xlsx, html) and the standard Git workflow is not as efficient at doing this. Git LFS is a new command line extension and specification for managing large files with Git.

Some features of Git LFS are listed below:

  • Faster cloning and fetching. Git LFS is configured to download less data. This means faster cloning and fetching from repositories that deal with large files.
  • Same Git workflow. Aside from the install and tracking the specific large files (git lfs track), work like you always do on Git. No need for additional commands, secondary storage systems, or toolsets.
  • Same access controls and permissions. Keep the same access controls and permissions for large files as the rest of your Git repository.

NOTE: There is a charge for Git LFS as it uses AWS in the back-end. If you wanted to test it out first with smaller files, it is free until you hit a certain quota.