The gga_load_data tools allow automated deployment of GMOD visualisation tools (Chado, Tripal, JBrowse, Galaxy) for a bunch of genomes and datasets.
They are based on the Galaxy Genome Annotation (GGA) project (https://galaxy-genome-annotation.github.io).
A stack of Docker services is deployed for each organism, from an input yaml file describing the data.
See `examples/example.yml` for an example of what information can be described and the correct formatting of this input file.
Each GGA environment is deployed at [https://hostname/sp/genus_species/](https://hostname/sp/genus_species/).
## Requirements
To run the gga_load_data tools, Python 3.6 and the packages listed in [requirements.txt](./requirements.txt) are required.
To deploy the GGA Docker services, one or multiple hosts machines are required with [Docker](https://docs.docker.com/engine/install/) installed,
and a [swarm](https://docs.docker.com/engine/swarm/swarm-tutorial)(for cluster management and orchestration).
## Reverse proxy and authentication
Traefik is a reverse proxy which allows to direct HTTP traffic to various Docker Swarm services.
The Traefik dashboard is deployed at [https://hostname/traefik/](https://hostname/traefik/)
Authelia is an authentication agent, which can be plugged to an LDAP server, and that Traefik can you to check permissions to access services.
The authentication layer is optional. If used, the config file needs the variables `https_port`, `auth_hostname`, `authelia_config_path`.
Authelia is accessed automatically by Traefik to check permissions everytime someones wants to access a page.
If the user is not logged in, he is redirected to the authelia portal.
Note that Authelia needs a secured connexion (no self-signed certificate) between the upstream proxy and Traefik (and https between internet and the proxy).
## Steps
The "gga_load_data" tools are composed of 4 scripts:
- gga_init: Create directory tree for organisms and deploy stacks for the input organisms as well as Traefik and optionally Authelia stacks
- gga_get_data: Create `src_data` directory tree for organisms and copy datasets for the input organisms into the organisms directory tree
- gga_load_data: Load the datasets of the input organisms into their Galaxy library
- run_workflow_phaeoexplorer: Remotely run a custom workflow in Galaxy, proposed as an "example script" to take inspiration from as workflow parameters are specific to Phaeoexplorer data
## Usage:
For all scripts one input file is required, that describes the species and their associated data.
(see `examples/example.yml`). Every dataset path in this file must be an absolute path.
Another yaml file is required, the config file, with configuration variables (Galaxy and Tripal passwords, etc..) that
the scripts need to create the different services and to access the Galaxy container. By default, the config file
inside the repository root will be used if none is precised in the command line. An example of this config file is available
in the `examples` folder.
**The input file and config file have to be the same for all scripts!**
Loraine Gueguen authored