docker_igv_js

A Docker container to wrap IGV.js

Motivation

Visualizations in Refinery are provided by Docker containers. The link between Refinery and the Docker containers is django_docker_engine. A container may provide back-end services to a visualization, or after start up it may just serve static html and js, as is the case here. In either case the input files are provided in a directory which is mounted on a predetermined path.

Add new genomes

The IGV instance will look for genome reference files in a particular S3 bucket. To add reference files for a new assembly, check out get-reference-genomes and run genome-to-s3.sh.

Development

Clone the repository, make sure Docker is installed, and then:

pip install -r requirements.txt
python test.py

After the tests run successfully the containers used for testing are killed.

Running and accessing the container

• The docker_igv_js container can be run by pointing to valid input.json file by url:

  • docker run -p 8080:80 -e INPUT_JSON_URL=https://raw.githubusercontent.com/refinery-platform/docker_igv_js/master/input_fixtures/good/input.json gehlenborglab/docker_igv_js

• Or an input.json file can be constructed and passed to the container directly through the envvar: INPUT_JSON.

  • docker run -p 8080:80 -e INPUT_JSON='
      {
        "node_info": {
          "id-1": {
            "file_url": "https://raw.githubusercontent.com/igvteam/igv/master/test/data/bed/intervalTest.bed",
            "node_solr_info": {"name": "track-name"}
          }
        },
        "parameters": [
          {"name": "Genome Build", "value": "hg19"}
        ]
      }' gehlenborglab/docker_igv_js
    

• Visit http://localhost:8080

Note: The current intentions of this project are to satisfy the needs of the refinery-platform, which currently has a strict way of passing input data to the underlying application (as seen above). Decoupling this tool, and providing a more general purpose solution has been talked of here.

Release

Successful Github tags and PRs will prompt Travis to push the built image to Dockerhub. For a new version number:

git tag v0.0.x && git push origin --tags