risserlin/em_base_image repository overview

If you want to run this docker with example code. First clone the Cytoscape_workflows repository.

• git clone https://github.com/BaderLab/Cytoscape_workflows.git⁠

To run this image run the following:

docker run -v "$(pwd)":/home/rstudio/projects -e PASSWORD=password -p 8787:8787 --add-host "localhost:###.###.###.###" risserlin/em_base_image

• Update the localhost to map to your current IP address.

• map your current working directory to the docker. (If you are using the cytoscpae workflow examples use "$(pwd)"/Cytoscape_workflows as the base directory.

• Once the container is running, in your web browser, go to localhost:8787 and login with the username=rstudio , password=password

What should be in the directory:

1. Your rank file
2. Protocol2_createEM.Rmd - RNotebook with EM pipeline. You will need to substitute host_machine_dir parameter at the top of the notebook with the full path to the current directory that you mapped to the docker.
   • for example at the top of the notebook I set - host_machine_dir: /Users/ruthisserlin/fake_em_dir

If you are using the Cytoscape_workflows:

1. navigate to projects/EnrichtmentMapPipeline
2. Open Protocol2_createEM.Rmd
3. Run notebook.

• When running GSEA make sure the directory to GSEA shell script is set in the notebook param section to:
  • gsea_jar: /home/rstudio/GSEA_4.1.0/gsea-cli.sh

⁠Important Note (Feb. 2021)

• With the latest. release of docker (version 3.0+) the default memory setting for your container is often not enough to run GSEA.
• Make sure that docker is set up to use at least 4 GB.
  • Go to your docker dashboard.
  • Click on settings in the top right hand corner
  • Click on Resources
  • Ensure that memory is set to at least 4GB
  • Click on "Apply & Restart"