Learning Pathways

Learning pathways are sets of tutorials curated for you by community experts to form a coherent set of lessons around a topic, building up knowledge as you go. We always recommend to follow the tutorials in the order they are listed in the pathway.

Explore all pathways below, or jump directly to a section:

• For Scientists
• For Teachers, Developers and System Administrators

For Scientists

Introduction to Galaxy and Sequence analysis

This learning path aims to teach you the basics of Galaxy and analysis of sequencing data. You will learn how to use Galaxy for analysis, and will be guided through the most common first steps of any genome analysis; quality control and a mapping or assembly of your genomic sequences.

beginner introduction sequence-analysis assembly

Epigenetics data analysis with Galaxy

Familiarize yourself with the Galaxy user interface and its most important features, then move on to analysis of genomic interval and deep-sequencing data with tools and tool suites like MACS2, bedtools and deepTools.

beginner genomic-intervals epigenetics

Introduction to Galaxy and Single Cell RNA Sequence analysis

This learning path aims to teach you the basics of Galaxy and analysis of Single Cell RNA-seq data. You will learn how to use Galaxy for analysis, and an important Galaxy feature for iterative single cell analysis. You’ll tbe guided through the general theory of single analysis and then perform a basic analysis of 10X chromium data. For support throughout...

beginner single-cell

Detection of AMR genes in bacterial genomes

This learning path aims to teach you the basic steps to detect and check Antimicrobial resistance (AMR) genes in bacterial genomes using Galaxy.

amr bacteria microgalaxy one-health microbiome

Applying single-cell RNA-seq analysis

Gone is the pre-annotated, high quality tutorial data - now you have real, messy data to deal with. You have decisions to make and parameters to decide. This learning pathway challenges you to replicate a published analysis as if this were your own dataset. You will be introduced to a few more tools available for scRNA-seq in Galaxy. Finally, if...

intermediate single-cell

From Zero To Hero with Python

Data analysis and programming are high-demand fields, making them particularly attractive to job seekers and employees across various industries and academic institutions. Are you eager to acquire the foundational skills of coding using the Python programming language? The BioNT consortium is offering a training curriculum for job seekers, SME employers, and everyone who would like to gain new skills in...

python programming introduction beginner

Discovering Galaxy through climate analysis

How to have a complete overview of how Galaxy works going from the user welcome page to use batch tools and finishing by conducting interactive analysis. These set of 3 Climate tutorials allow you to understand and see plenty of the multiple features of Galaxy and learning about the cool subject of climate analysis.

climate

Clinical metaproteomics workflows within Galaxy

This learning path aims to teach you the basics of how to perform metaproteomics analysis of the clinical data within the Galaxy platform. You will learn how to use Galaxy for analysis and will be guided through the most common first steps of any metaproteomics database generation to searching the database, verifying the proteins/peptides, and data analysis.

beginner proteomics

Bioinformatics Projects: Using deconvolution to get new insights from old bulk RNA-seq data

Are you an educator looking for project ideas for students to practice independent enquiry and research skills? Are you a student looking for a project idea? Look no more - here, you will find a learning pathway of tutorials that can guide you through the skills to find old data and transform it into new results! To be clear, we...

advanced single-cell

FAIR Data Management

The FAIR data management training learning pathway teaches you how to organise, describe, and store research data according to the FAIR principles (Findable, Accessible, Interoperable, Reusable).

fair dmp data management data stewardship

Genome annotation for eukaryotes

Learn how to annotate an eukaryotic genome sequence: identify repeated regions, find the position and function of genes, and even set up a manual curation environment with Apollo.

genome-annotation eukaryote

Genome annotation for prokaryotes

Learn how to annotate a prokaryotic genome sequence: find the position and function of genes, and even set up a manual curation environment with Apollo.

genome-annotation prokaryote

Introduction to Galaxy and Ecological data analysis

This learning path aims to teach you the basics of Galaxy and analysis of ecological data. You will learn how to use Galaxy for analysis, and will be guided through the common steps of biodiversity data analysis: download, check, filter and explore biodiversity data and analyze abundance data through modeling.

beginner ecology

From R to Machine Learning; an introductory course

This learning path aims to teach you the basics of Machine Learning using R. Initially you will learn how to code in R within the Galaxy platform, gaining some familiarity into how to wrangle and analyze data. Then, you will be guided through the various types of Machine Learning techniques, developing some simple models using R.

beginner statistics data-science

Machine learning

This learning path teaches machine learning from simple concepts to complex ones. You start with a basic introduction to Machine learning. Then you move to different aspects of supervised machine learning such as classification and regression. Further topics introduce you to deep learning concepts such as convolutional and recurrent neural networks and conclue with fine-tuning a large language like model...

beginner machine learning

Metagenomics data processing and analysis for microbiome

This learning path aims to teach you the basics of Galaxy and analysis of metagenomics data. You will learn how to use Galaxy for analysis, and will be guided through the common steps of microbiome data analysis: quality control, taxonomic profiling, taxonomic binning, assembly, functional profiling, and also some applications

microbiome

Artificial Intelligence and Machine Learning in Life Sciences using Python

Artificial intelligence (AI) has permeated our lives, transforming how we live and work. Over the past few years, a rapid and disruptive acceleration of progress in AI has occurred, driven by significant advances in widespread data availability, computing power and machine learning. Remarkable strides were made in particular in the development of foundation models - AI models trained on extensive...

elixir ai ml

Neoantigen discovery using the iPepGen pipeline

This learning path introduces a comprehensive immunopeptidogenomics (iPepGen) workflow for neoantigen discovery using label-free mass spectrometry data. The modules guide you through fusion and variant database generation, peptide identification with FragPipe, peptide validation using PepQuery2, and immunogenicity assessment through HLA binding predictions and IEDB screening.

intermediate immunopeptidomics cancer proteogenomics label-free

Proteogenomics

This learning path aims to teach you the basics of how to perform proteogenomics analysis of the Mass spectrometry data within the Galaxy platform. You will learn how to use Galaxy for analysis and will be guided through the most common first steps of any proteogenomics database generation to searching the database, followed by novel peptide data analysis.

beginner proteomics

Introductory Python

This is an introductory course of Python, as it was taught in Avans Hogeschool in the Netherlands.

python real-course data-science

Applying single-cell RNA-seq analysis in Coding Environments

Gone is the pre-annotated, high quality tutorial data - now you have real, messy data to deal with. You have decisions to make and parameters to decide. This learning pathway challenges you to replicate a published analysis as if this were your own dataset. You will perform this analysis in coding environments hosted on Galaxy, instead of Galaxy’s button-based tool...

advanced single-cell

Introductory SQL

This is an introductory course of SQL, as it was taught in Avans Hogeschool in the Netherlands.

python real-course data-science

For Teachers, Developers and System Administrators

Onboarding for new contributors

This learning path aims to teach you how to contribute to GTN training materials. From editing typos to rendering test GTN sites, you will progress from being a user to a contributor. For support throughout these tutorials, join our Galaxy training network on Matrix to ask questions!

introduction contributing cofest

Admin Training Course

Learn how to setup, configure, and maintain your own Galaxy server. This learning pathway will guide you through all the steps required to setup your own Galaxy server with Ansible, configuring it, and making it production ready.

Galaxy administrators 5-day course admin

Tool development for a nice & shiny subdomain

Discover Galaxy’s communities and learn how to create your subdomain and enrich it by writing, testing and submiting your tools on Galaxy. This learning pathway will guide you through all the steps required to build a tool for Galaxy with Planemo for batch tools and how write an interactive tool.

subdomain community tool development 3-day course dev

Creation of a Community CoDex and lab (and optionally of a Special Interest Group (SIG))

The Galaxy Communities Dock or Galaxy CoDex is a centralized repository that ensures the versioning and documentation of the community components (Batut et al., 2024; Nasr et al., 2024). The codex is composed of : A GitHub repository specific to each community with curated lists of tools, workflows and tutorials relevant to the community. For example : The curated resources...

community codex lab sig

Train the Trainers

This pathway introduces trainers to learning principles, training techniques, lesson, session, course, and material design as well as assessment and feedback. This is has been developed for by trainers in the bioinformatics but is suitable for all trainers and educators in higher education.

training trainers teaching community