PANDORA is a comprehensive suite of advanced analytical tools designed to support a wide range of biomedical research applications.

Overview

PANDORA uses advanced machine learning techniques, including clustering, t-SNE, PCA, UMAP, and interpretable machine learning models to enhance biomedical discovery. It supports multiclass outcomes, facilitating predictive modeling, biomarker discovery, and omics data analysis for systems biology.

Installation Quick-start

PANDORA can be installed using Docker, a pre-built version of the platform can be pulled from DockerHub. In order to run PANDORA, users will first need to install Docker.

Requirements

Software:

• Windows, Linux or MacOS
• Docker (version 17.05 or later is required)

Minimum suggested hardware recommendation:

• 64GB RAM
• 8 CPU Cores / 16 threads with 3 GHz base frequency

Installing PANDORA

• Please open your favorite Terminal and run the command below. On Windows - open Windows Power Shell => Click Start, type PowerShell, and then click Windows PowerShel

docker run --rm --detach --name genular --tty --interactive --env IS_DOCKER='true' --env TZ=Europe/London --oom-kill-disable --volume genular_frontend_latest:/var/www/genular/pandora --volume genular_backend_latest:/var/www/genular/pandora-backend --volume genular_data_latest:/mnt/usrdata --publish 3010:3010 --publish 3011:3011 --publish 3012:3012 --publish 3013:3013 genular/pandora:latest

PANDORA will be downloaded and started, and it can be accessed via a web browser at http://localhost:3010

• If you get asked, please allow connections through your Windows Firewall.

Reinstalling PANDORA

To ensure a clean re-installation of PANDORA, follow these steps to remove the existing Docker container, images, and volumes associated with PANDORA. This process will remove all data and settings related to the previous PANDORA installation.

Identify the names or IDs of your PANDORA container(s), volume(s), and image(s).
Use these commands to list entities:

• Containers: docker ps (for running) or docker ps -a (for all)
• Images: docker images
• Volumes: docker volume ls

(Or use Docker GUI)

## Stop and delete any old PANDORA Container
docker stop <ContainerName>
## Delete
docker rm <ContainerName>

## Check for any images and remove them if necessary
docker images

## Check for any volumes
docker volume ls

## Remove them as-well
docker volume rm genular_frontend_latest genular_backend_latest genular_data_latest

## Now you can proceed with clean installation

Contributing, writing code

Contributions are very much welcome!

If you need any help, please use community forums.

1. Check out our public issues board. If your issue isn’t on the board, open a new one.
2. Pick an issue that nobody has claimed and start working on it.
3. Fork the project (Need help forking a project?). You’ll do all of your work on your forked copy.
4. Create a branch specific to the issue or feature you are working on. Push your work on that branch (Need help with branching?).
5. Name the branch something like fixes-xxx-issue or add-xxx-feature where xxx is a short description of the changes or feature you are adding.
6. Once your code is ready, submit a pull request from your branch to PANDORA master branch. We’ll do a quick review and give you feedback.

Reaching Out

If you’d like to start a conversation feel free to e-mail us.
I would also like to hear from you if you find this project useful and helpful!

• Join us on #genular on freenode.net (or use the web client).
• Find us on Twitter under @genular
• Check out community forums

Security Vulnerabilities

If you discover a security vulnerability within PANDORA, please e-mail us. All security vulnerabilities will be promptly addressed. You are also welcome to open PR request.

Additional Links

Resource	Link
File an issue	https://github.com/genular/pandora/issues
Blog	https://genular.org/blog/
Twitter	https://twitter.com/genular

License

For more information please check LICENCE file.

Citation

PANDORA can be used for research purposes, you should cite
the aforementioned papers in any resulting publication.

    Adriana Tomic, Ivan Tomic, Yael Rosenberg-Hasson, Cornelia L. Dekker, Holden T. Maecker, Mark M. Davis.
    SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses
    http://www.jimmunol.org/content/early/2019/06/13/jimmunol.1900033.abstract
    doi: 10.4049/jimmunol.1900033

    Adriana Tomic, Ivan Tomic, Levi Waldron, Ludwig Geistlinger, Max Kuhn, Rachel L. Spreng, Lindsay C. Dahora, Kelly E. Seaton, Georgia Tomaras, Jennifer Hill, Niharika A. Duggal, Ross D. Pollock, Norman R. Lazarus, Stephen D.R. Harridge, Janet M. Lord, Purvesh Khatri, Andrew J. Pollard, Mark M. Davis.
    SIMON: Open-Source Knowledge Discovery Platform
    https://www.cell.com/patterns/fulltext/S2666-3899(20)30242-7
    doi:10.1016/j.patter.2020.100178