Set up a Galaxy for Training
How do I prepare my Galaxy instance to support a training module?
How can I generate a Docker Galaxy instance for my topic?
Use ephemeris to install the training requirements to a Galaxy instance
Create a docker image for a training topicTime estimation: 2 hoursLast modification: May 15, 2023License: Tutorial Content is licensed under Creative Commons Attribution 4.0 International License. The GTN Framework is licensed under MITpurlPURL: https://gxy.io/GTN:T00285
In this tutorial, you will learn how to provision your Galaxy instance to support training modules from the GTN repository.
Tutorials in this repository are all supplemented with files describing the technical requirements to run them. This makes it easy to automate installation of tutorial requirements.
data-library.yaml: describes the input datasets
data-manager.yaml: describes the reference data required by tools
workflowsfolder: contains one or more workflows with all steps in the tutorial
toursfolder: contains one or more yaml files describing interactive tours
For more information about how to create these files, please see our module on specifying the technical requirements for your tutorial.
For just the list of Ephemeris commands needed for installation, skip to the Quickstart section at the end of this tutorial.
In this tutorial, we will deal with:
Prepare for installation
If you have a Galaxy server already running somewhere and would like to support one or more training modules, ephemeris can be used to easily install all the required tools, reference data, data libraries, tours and workflows.
For the purposes of this training, we will create a Galaxy instance running on
localhost:8080, but these instructions can be adapted for use with any Galaxy instance by replacing this value with the URL or IP address of your Galaxy server.
Start a local Galaxy
To setup a Galaxy server locally, we will first clone the Galaxy github repository, make a few small edits to the
galaxy.yaml configuration file, and then start the server.
Hands-on: Setup a local Galaxy instance
- Clone the github repository
git clone https://github.com/galaxyproject/galaxy.git cd galaxy
- Add yourself as admin user in
cp config/galaxy.yml.sample config/galaxy.yml
galaxy.ymlfile with your favorite editor and edit the following line with your email address:
- Start Galaxy
Galaxy will now install all its requirements, which may take a few minutes, when all is finished installing, you should see something like this in your screen:
Starting server in PID 9560. serving on http://localhost:8080
- Open Galaxy
- Open a web browser
- Navigate to
localhost:8080to access Galaxy
Find your Galaxy API key
In order to install the tutorial requirements, we will need the API key of an admin user.
Hands-on: Obtain Galaxy API key
- Register an account on Galaxy using the email address you added to the
- Once logged in, verify that you have a menu item named
Adminin your top menu bar.
- Go to your
User -> Preferencesin the top menu bar, then click on
Manage API key
- Click on
Create a new keyto generate an API key
- Copy your API key to somewhere convenient, you will need it throughout this tutorial
To install to training requirements to our Galaxy, we will use Ephemeris, let’s install it now:
Hands-on: Install Ephemeris
# optional: create a virtual environment virtualenv .venv; . .venv/bin/activate # install ephemeris pip install ephemeris
Installing tutorial requirements
We have created a small bash script to automatically install all of a tutorial’s requirements to an existing Galaxy. It’s located in this repository under:
In this example we will install the requirements for the Reference-based RNASeq tutorial to the Galaxy instance running on localhost.
Hands-on: Install a tutorial
- If you have not done so yet, clone the training material github repo:
git clone https://github.com/galaxyproject/training-material.git cd training-material
Run the script to install the RNASeq tutorial
bin/install_tutorial_requirements.sh topics/transcriptomics/tutorials/ref-based http://localhost:8080 <api key>
Installation may take some time. This script will automatically install the tools, create a data library and populate it with the input datasets from Zenodo, install and publish the workflows, and run any data managers that might be required.
The only thing the script cannot currently automate is the installation of the interactive tours. We will now do this manually by copying the contents of the
tours folder to our Galaxy instance, in the folder
Hands-on: Install the interactive Tours
- Copy the
tour.yamlfile from the training materials repo to Galaxy
cp -r topics/transcriptomics/tutorials/ref-based/tours/ $GALAXY_ROOT/config/plugins/tours
Installing an entire topic
If you would like to install all the requirements for every tutorial within an entire topic, you can use the script in
Installing a subset of components
If you would like to pick and choose what to install for each tutorial, below are descriptions of the commands used to install each of the components (tools, workflows, reference data, data libraries, tours) please see the Quickstart section for the individual commands used by the script
Below is the list of commands used in this tutorial.
Using the scripts in this repository:
# Make sure you are in the root of the training-material repo cd <training-materials repo root> # install single tutorial bin/install_tutorial_requirements.sh topics/<yourtopic>/tutorials/<yourtutorial> <Galaxy URL> <API key> # install entire topic bin/install_topic_requirements.sh topics/<yourtopic> <Galaxy URL> <API key>
Using ephemeris directly:
# install tools shed-tools install -g <Galaxy URL> -a <API key> -t <(curl https://training.galaxyproject.org/training-material/api/topics/<topic>/tutorials/<tutorial>/tutorial.json | jq .admin_install_yaml -r) # create data library with input datasets setup-data-libraries -g <Galaxy URL> -a <API key> -i topics/<topic>/tutorials/<tutorial>/data-library.yaml # install reference data run-data-managers -g <Galaxy URL> -a <API key> --config topics/<topic>/tutorials/<tutorial>/data-manager.yaml # install workflows workflow-install --publish-workflows -g <Galaxy URL> -a <API key> -w topics/<topic>/tutorials/<tutorial>/workflows # install tours copy the contents of the "tours" directory for the tutorial to Galaxy's "config/plugins/tours/"
When data libraries are created, depending on the server settings, they may be created privately. You will need to fix their permissions either through the UI or the API if you have many datasets. UseGalaxy.eu uses a script to correct the permissions.