R¶

General R resources¶

If you are looking for some help getting started with R or taking your R to the next level, check out these useful resources:

• Swirl - interactive R learning
• Tidyverse workshop and resources
• Parisod Lab R Knowledge base & Cheatsheet
• R-bloggers - tips and tricks
• Using Rprojects to organize scripts
• Using workflowR for reproducible work
• Using Rmarkdown to generate reports
• Also check out the lab_code slack channel for help!

Using R on IBU¶

Making sure everyone has the same version of several different R packages (specifically Tidyverse) can be a nightmare for software development. Fortunately, there are several ways to get around this issue:

Docker/singularity container:¶

Instead of using conda environments (or maybe in addition to), a docker/singularity image can be generated with R packages installed. The benefit is that singularity images can be used on IBU or locally and minimal set up is required. The downside is that on some occasions there can be errors generating the docker image with incompatible package versions.

Using renv for R Package Management:¶

Renv is a package that allows you to create a project-specific library for R packages. This is useful for ensuring that all users have the same version of R packages. To use renv, you need to install the package and then run renv::init() in your R project. This will create a renv.lock file that lists all the packages you have installed in your project. When you share your project with someone else, they can run renv::restore() to install the same versions of the packages you have. This is a good way to ensure that everyone is using the same versions of R packages.

Setting Up renv:

1. Install renv: First, you'll need to install renv if it isn't already installed.

install.packages("renv")

2. Initialize renv: Navigate to your project directory and initialize renv. This will create a project-specific library and an renv.lock file that captures the versions of the packages you are using.

renv::init()

This will snapshot the current state of your R environment, saving the versions of all packages currently installed and used in the project.

3. Install Packages: You can install any required packages as usual, and renv will manage them within the project’s library.

renv::install("tidyverse")

4. Snapshot Dependencies: Whenever you make changes to your package dependencies, update the lock file to reflect these changes.

renv::snapshot()

The renv.lock file can be committed to your version control system to ensure that anyone else using the project can recreate the exact same environment.

5. Restoring the Environment: When someone else clones your project repository, they can restore the project environment using the renv.lock file.

renv::restore()

This will install the exact versions of the packages as specified in the renv.lock file, ensuring consistent environments across different users and systems.

Using renv in Scripts and Pipelines:

• You can add the following lines to your scripts to ensure the renv environment is automatically activated when running the script:

if (!requireNamespace("renv", quietly = TRUE)) install.packages("renv") renv::activate()

• For Nextflow pipelines, you can include renv::activate() at the beginning of your R scripts to make sure the correct environment is loaded:

echo "renv::activate()" | cat - ${workflow.projectDir}/bin/Script.R > Script.R Rscript --vanilla Script.R

Running Rstudio on IBU¶

The IBU allow users with active IBU allocations to use RStudio from a web browser. See IBU Rstudio Server for an overview of the system.

Go to the https://rstudio.bioinformatics.unibe.ch/users/$USER_NAME/ (Do not forget the “/” at the end). Log in with your netid and password just like you would on IBU. make sure you are connected with VPN if you are off campus

You can set the working directory with setwd("path_to_directory") and then open and save files and data in Rstudio just like you were using it locally on your computer -- but with data and files on IBU!!

To link RStudio server to the filesystem:
1. create an RSTUDIO directory in the project root (e.g. /data/projects/$PROJECT_ID/) or at the user level (/data/users/$USERNAME/)
2. the folder will appear in your RStudio home directory (check the files pane). Note: this may take up to 10' (worst case scenario)