Run Bioconductor on Compute Engine

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Bioconductor maintains Docker containers with R, Bioconductor packages, and RStudio Server all ready to go! Its a great way to set up your R environment quickly and start working. The instructions to deploy it to Google Compute Engine are below but if you want to learn more about these containers, see

  1. Click on click-to-deploy Bioconductor to navigate to the launcher page on the Cloud Platform Console.
  1. Optional: change the Machine type if you would like to deploy a machine with more CPU cores or RAM.
  2. Optional: change the Data disk size (GB) if you would like to use a larger persistent disk for your own files.
  3. Optional: change Docker image if you would like to run a container with additional Bioconductor packages preinstalled.
  1. Click on the Deploy Bioconductor button.
  2. Follow the post-deployment instructions to log into RStudioServer via your browser!

If you want to deploy a different docker container, such as the one from BioC 2015: Where Software and Biology Connect or from

  1. In field Docker Image choose item custom.
  2. Click on More to display the additional form fields.
  3. In field Custom docker image paste in the docker image path, such as or

Change your virtual machine type (number of cores, amount of memory)

  1. First, make sure results from your current R session are saved to the data disk (underneath /home/rstudio/data) or another location outside of the container.
  2. Follow these instructions to stop, resize, and start your VM:

“Stop” or “Delete” your virtual machine

If you would like to pause your VM when not using it:

  1. Go to the Google Cloud Platform Console and select your project:
  2. Click on the checkbox next to your VM.
  3. Click on Stop to pause your VM.
  4. When you are ready to use it again, Start your VM. For more detail, see:

If you want to delete your deployment:

  1. First copy any data off of the data disk that you wish to keep. The data disk will be deleted when the deployment is deleted.
  2. Click on Deployments to navigate to your deployment and delete it.

Have feedback or corrections? All improvements to these docs are welcome! You can click on the “Edit on GitHub” link at the top right corner of this page or file an issue.

Need more help? Please see