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📰 Manual and Documentation is available at: OmicLearn Wiki Page

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OmicLearn

Transparent exploration of machine learning for biomarker discovery from proteomics and omics data

Manuscript

📰 Open-access article: Transparent exploration of machine learning for biomarker discovery from proteomics and omics data

Citation:
Transparent exploration of machine learning for biomarker discovery from proteomics and omics data
Furkan M Torun, Sebastian Virreira Winter, Sophia Doll, Felix M Riese, Artem Vorobyev, Johannes B Müller-Reif, Philipp E Geyer, Maximilian T Strauss
bioRxiv 2021.03.05.434053; doi: https://doi.org/10.1101/2021.03.05.434053

Access

🟢 OmicLearn.com

🟢 Streamlit Share (collects usage statistics - XGBoost not installed)

Installation & Running

More information about Installation & Running is available on our Wiki pages.

  • It is strongly recommended to install OmicLearn in its own environment using Anaconda or Miniconda.

    1. Open the console and create a new conda environment: conda create --name omic_learn python=3.7
    2. Activate the environment: conda activate omic_learn for Linux / Mac Os X / Windows

    Note: Type the following command for conda versions prior to 4.6:

    source activate omic_learn for macOS and Linux

    activate omic_learn for Windows

    1. Redirect to the folder of choice and clone the repository: git clone https://github.com/OmicEra/OmicLearn
    2. Install the required packages with pip install -r requirements.txt
    3. To be able to use Xgboost, install via conda: conda install py-xgboost

  • After a successful installation, type the following command to run OmicLearn:

    streamlit run omic_learn.py --browser.gatherUsageStats False

    Running with Docker option is also available. Please, check the installation instructions on the Wiki pages.

  • After starting the streamlit server, the OmicLearn page should be automatically opened in your browser (Default link: http://localhost:8501

Getting Started with OmicLearn

The following image displays the main steps of OmicLearn:

OmicLearn Workflow

Detailed instructions on how to get started with OmicLearn can be found here.

On this page, you can click on the titles listed in the Table of Contents, which contains instructions for each section.

Contributing

All contributions are welcome. 👍

📰 To get started, please check out our CONTRIBUTING guidelines.

When contributing to OmicLearn, please open a new issue to report the bug or discuss the changes you plan before sending a PR (pull request).

Also, be aware that you agree to the OmicEra Individual Contributor License Agreement by submitting your code. 🤝