Statistics and machine learning

Statistical Analyses for omics data and machine learning using Galaxy tools

You can view the tutorial materials in different languages by clicking the dropdown icon next to the slides (slides) and tutorial (tutorial) buttons below.


Before diving into this topic, we recommend you to have a look at:


Lesson Slides Hands-on Recordings Input dataset Workflows Galaxy servers
A Docker-based interactive Jupyterlab powered by GPU for artificial intelligence in Galaxy tutorial
Age prediction using machine learning
Basics of machine learning
Classification in Machine Learning
  • Clustering in Machine Learning
    Deep Learning (Part 1) - Feedforward neural networks (FNN)
    plain text tutorial
  • Deep Learning (Part 2) - Recurrent neural networks (RNN)
    plain text tutorial
  • Deep Learning (Part 3) - Convolutional neural networks (CNN)
    plain text tutorial
  • Image classification in Galaxy with fruit 360 dataset
    plain text tutorial
  • Interval-Wise Testing for omics data
    Introduction to Machine Learning using R tutorial
  • Introduction to deep learning
    Machine learning: classification and regression
    PAPAA PI3K_OG: PanCancer Aberrant Pathway Activity Analysis tutorial
    Regression in Machine Learning
  • Text-mining with the SimText toolset tutorial

    Galaxy instances

    You can use a public Galaxy instance which has been tested for the availability of the used tools. They are listed along with the tutorials above.

    You can also use the following Docker image for these tutorials:

    docker run -p 8080:80

    NOTE: Use the -d flag at the end of the command if you want to automatically download all the data-libraries into the container.

    It will launch a flavored Galaxy instance available on http://localhost:8080. This instance will contain all the tools and workflows to follow the tutorials in this topic. Login as admin with password password to access everything.

    Frequently Asked Questions

    Common questions regarding this topic have been collected on a dedicated FAQ page . Common questions related to specific tutorials can be accessed from the tutorials themselves.


    This material is maintained by:

    AvatarMarzia A Cremonaorcid logoAvatarFabio CumboAvatarAnup Kumar

    For any question related to this topic and the content, you can contact them or visit our Gitter channel.


    This material was contributed to by:

    orcid logoAvatarAlireza KhanteymooriAvatarDennis Lal groupAvatarErasmus+ Programmeorcid logoAvatarDaniel Blankenbergorcid logoAvatarBérénice Batutorcid logoAvatarFabio Cumboorcid logoAvatarMarie GrammAvatarAnup KumarAvatarMarzia A CremonaAvatarEkaterina PolkhAvatarKaivan KamaliAvatarVijayAvatarSimon Brayorcid logoAvatarFotis E. Psomopoulos