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Run Bioconductor on Compute Engine

The properly rendered version of this document can be found at Read The Docs.

If you are reading this on github, you should instead click here.

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 :doc:`/workshops/bioc-2015` 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