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 () and tutorial () buttons below.

Requirements

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

Material

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

    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 quay.io/galaxy/statistics-training

    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.

    Maintainers

    This material is maintained by:

    AvatarMarzia A Cremona AvatarFabio Cumbo AvatarAnup Kumar

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

    Contributors

    This material was contributed to by:

    AvatarAnup Kumar AvatarEkaterina Polkh AvatarAlireza Khanteymoori AvatarSimon Bray AvatarKaivan Kamali AvatarMarzia A Cremona AvatarFabio Cumbo AvatarFotis E. Psomopoulos AvatarErasmus+ Programme AvatarBérénice Batut AvatarVijay AvatarDaniel Blankenberg AvatarMarie Gramm AvatarDennis Lal group