/OmicLearn

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

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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

Online Access

🟢 OmicLearn.com

This is an online version hosted by streamlit using free cloud resources, which might have limited performance. Use the local installation to run OmicLearn on your own hardware.

Local Installation

One-click Installation

You can use the one-click installer to install OmicLearn as an application locally. Click on one of the links below to download the latest release for:

Windows, macOS, Linux

Python Installation

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

    1. Redirect to the folder of choice and clone the repository: git clone https://github.com/OmicEra/OmicLearn
    2. Create a new environment for OmicLearn: conda create --name omic_learn python=3.9
    3. Activate the environment with conda activate omic_learn
    4. Install OmicLearn with pip install .

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

    python -m omiclearn

  • 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 contain 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).

We appreciate community contributions to the repository. By signing our OmicEra Individual Contributor License Agreement, we ensure that the community is free to use your contributions. 🤝