NOTE: GIE folder is now deprecated as this has been merged into Galaxy. The Docker image is still being maintained here.

Phinch Galaxy IE

Galaxy Interactive Environment for the Phinch visualisation framework.

How to Run

Metagenomics Galaxy

This plugin is installed in the Metagenomics Galaxy Flavour.

Assuming docker is installed on your system, this container can be started as follows:

docker run --rm -p 8080:80 -it -p 8800:8800 -v `pwd`/foo/:/export/ --privileged=true quay.io/bgruening/galaxy-metagenomics

NOTE: See the README in the Metagenomics Galaxy repo for more information and advanced configurations.

Once the image is running, access it by navigating to <hostname>:8080 in your (Chrome) web browser. Make sure you are logged in and upload a biom file. You should now have Phinch as a visualisation option for that dataset.

How to run this on a local Galaxy

Below is a description of how to test this on a localhost Galaxy instance. For more advanced configurations, please see the excellent documentation by the Galaxy Team here.

Install Galaxy

$ git clone https://github.com/galaxyproject/galaxy/

edit the galaxi.ini file:

[..]

# The address on which to listen.  By default, only listen to localhost (Galaxy
# will not be accessible over the network).  Use '0.0.0.0' to listen on all
# available network interfaces.
host = 0.0.0.0

[..]

# Interactive environment plugins root directory: where to look for interactive
# environment plugins.  By default none will be loaded.  Set to
# config/plugins/interactive_environments to load Galaxy's stock plugins
# (currently just IPython).  These will require Docker to be configured and
# have security considerations, so proceed with caution. The path is relative to the 
# Galaxy root dir.  To use an absolute path begin the path with '/'.  This is a comma
# separated list.
interactive_environment_plugins_directory = config/plugins/interactive_environments

[..]

# Have Galaxy manage dynamic proxy component for routing requests to other
# services based on Galaxy's session cookie.  It will attempt to do this by
# default though you do need to install node+npm and do an npm install from
# `lib/galaxy/web/proxy/js`.  It is generally more robust to configure this
# externally managing it however Galaxy is managed.  If True Galaxy will only
# launch the proxy if it is actually going to be used (e.g. for IPython).
dynamic_proxy_manage=True

# Dynamic proxy can use an SQLite database or a JSON file for IPC, set that
# here.
dynamic_proxy_session_map=database/session_map.sqlite

# Set the port and IP for the the dynamic proxy to bind to, this must match
# the external configuration if dynamic_proxy_manage is False.
dynamic_proxy_bind_port=8800
dynamic_proxy_bind_ip=0.0.0.0

# Enable verbose debugging of Galaxy-managed dynamic proxy.
dynamic_proxy_debug=True

[..]

Set up the proxy

$ cd <GALAXY ROOT DIR>/lib/galaxy/web/proxy/js
$ npm install

(to install node on ubuntu:)

$ sudo apt-get install npm

# if you get an error /usr/bin/env: not found:
$ sudo ln -s /usr/bin/nodejs /usr/bin/node

Run

Start Galaxy:

$ cd <GALAXY ROOT DIR>
$ sh run.sh

• Open your Chrome web browser
• Navigate to :8080
• Make sure you are logged in
• Upload a .biom file (an example file is provided in this repo)
• Click on the visualisation button for the biom dataset and select Phinch
• The first time it will download the docker image from DockerHub, which may take a little while. (you can monitor progress in Galaxy log)
• After that it should be pretty quick to load.
• Your galaxy dataset should be automatically loaded into Phinch
• NOTE: share button has been disabled as the docker image will be short-lived
• NOTE: the docker image will be killed after 10 minutes of inactivity
• NOTE: export of filtered biom file or images should result in a new dataset in your history, but a refresh of the history may be required.