Explore our curated collection of training materials covering a wide range of topics in cloud computing, bioinformatics, and data science. These tutorials are designed for hands-on learning and support both beginners and advanced users.
For some tutorials, multiple versions are available, allowing you to access different iterations of the same lesson. By default, select the "main" version to access the most up-to-date materials. Other versions may be useful for following older course editions or reproducing previous training sessions.
Lesson materials are all available online under a CC BY 4.0 license, for self-directed study or for adaptation and re-use in your own training sessions.
Unix
Tutorials focused on basic Unix / Linux commands and shell usage.
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|---|---|---|---|---|
| Introduction to basic Unix commands |
main
spring-school-2024 |
spring-school-2024 (PDF) | This is the introduction to the basic shell commands. | 2H |
Cloud computing
Tutorials focused on using the de.NBI Cloud infrastructure and project types.
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|---|---|---|---|---|
| SimpleVM Workshop | main | Tutorial shows how to identify pathogenic bacteria within publicly available metagenomic datasets and scale up a bioinformatics workflow using SimpleVM. | 2H | ||
| BiBiGrid Hands-on | main | Tutorial shows how to provision and operate a small HPC cluster on OpenStack using BiBiGrid | 2H |
Cloud application deployment
Tutorials in this group offer hands-on experience in building, containerizing, and deploying applications from local development environments to the cloud.
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|---|---|---|---|---|
| Build a Simple Dataset Web App on EMBL Cloud Infrastructure | main | Learn to create and deploy a web application using Python, Streamlit, Docker/Podman, and Kubernetes on EMBL cloud computing infrastructure | 2H |
Machine Learning on Cloud infrastructure
Tutorials focused on setting up machine learning toolkits and applications on cloud infrastructure.
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|
PATCH Tutorials
Tutorials in this group contain learning material about the tools contained inside the pangenomics toolbox PATCH
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|
Genomics and Metagenomics
Tutorials focused on handling of genomics and metagenomics sequencing data
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|---|---|---|---|---|
| Metagenomic Quality Control & Preprocessing | main | This tutorial introduces the workflow for assessing sequencing quality with FastQC, trimming adapters, and removing low-quality bases using fastp and Cutadapt. | 1H | ||
| Metagenome Assembly: concepts and hands-on comparison of assemblers |
main
main |
This tutorial introduces the principles and challenges of metagenome assembly, including de Bruijn graph-based approaches, k-mer selection, and metagenome-specific assembly strategies. You will apply several assemblers, including Velvet, MEGAHIT, metaSPAdes, IDBA-UD, and Ray, and compare their assembly performance. | 1H | ||
| Assembly Evaluation | main | This tutorial introduces the workflow for evaluating metagenomic assemblies by mapping reads back to contigs and computing assembly metrics using MetaQUAST. | 1H | ||
| Metagenomic Binning and Classification | main | This tutorial introduces the workflow for clustering assembled metagenomic contigs into genomes (binning), evaluating their quality, and assigning taxonomic labels using modern bioinformatics tools. | 1H | ||
| Introduction to the Metagenomics-Toolkit | main | This tutorial will guide you through the first steps to run the Metagenomics-Toolkit on paired-end metagenomic sequencing data. It covers pipeline configuration, execution, result inspection, and interactive analysis with Jupyter notebooks. | 1H | ||
| Basics of Amplicon Quality Processing | main | Basic steps to do manually quality processing of 16S data step by step with individual tools instead of using integrated solutions like qiime2 / dada2 / deblur. | 2H | ||
| Basecalling and QC of ONT data | main | This tutorial introduces the preprocessing workflow for Oxford Nanopore Technologies (ONT) sequencing data, from raw signal files to quality-controlled reads for downstream analysis. | 2H | ||
| Introduction to Long-Read Metagenomics using the Metagenomics-Toolkit | main | This tutorial will guide you through the first steps to run the Metagenomics-Toolkit on ONT data | 1H | ||
| Prokaryotic Genome Annotation (hands-on) | main | Learn the steps of prokaryotic genome annotation by generating and comparing annotations with Prokka and Bakta. The tutorial also introduces EDGAR for comparative genome analysis, including core-genome, pan-genome and ortholog identification. | 2H | ||
| Assembly and assembly evaluation (hands-on) | main | This tutorial demonstrates how to assemble a prokaryotic genome using Oxford Nanopore and Illumina sequencing data, evaluate assembly quality, improve assemblies through polishing and hybrid assembly approaches, and assess the final results. | 2H |
Data Management on the Cloud
Tutorials focused on data management best practices, solutions on the Cloud, including how to adapt a solution to the cloud (Kubernetes and S3 storage)
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|---|---|---|---|---|
| Basic Data Management in the de.NBI Cloud | main | Basic Data Management in the de.NBI Cloud. Intended for a cloud-naive audience. | 8H | ||
| Using the cross-domain Data-Management Platform repository | main | A step-by-step overview of how to use the repository. | 40M |
Incubator
Tutorials in this group are under review.
| Tutorial | Versions | Slides | Description | Contributors | Estimated Time |
|---|---|---|---|---|---|
| RDM Microbial Training Course | main | ||||
| Ansible | main | ||||
| Deploying Machine Learning workflow using FastAPI | main | 3H | |||
| Setting up ML project in the cloud infrastructure | main | Transform a trained model into an online service with a UI using Streamlit. | 5H | ||
| PanBench | main | Introduction to using the web interface of panbench.eu | 10M |