Module 1: Quality Control & Preprocessing

This module introduces the essential first step of any metagenomic workflow: assessing and improving the quality of raw sequencing reads. You will learn how to evaluate data with FastQC, trim adapters and low-quality bases using fastp, and perform precise adapter removal with Cutadapt.

Tutorial	Slides	Description	Learning Objectives	Estimated Time
Metagenomic Quality Control & Preprocessing		This tutorial introduces the workflow for assessing sequencing quality with FastQC, trimming adapters, and removing low-quality bases using fastp and Cutadapt.	Generate and interpret FastQC reports for raw data. Apply sliding window quality trimming and poly-G removal using fastp. Trim remaining adapter sequences using Cutadapt. Validate preprocessing results to ensure high-quality input for downstream assembly.	1H

Module 2: Metagenome Assembly

This module covers the principles and hands-on application of metagenome assembly. You will learn about de Bruijn graph approaches, k-mer selection strategies, and metagenome-specific challenges such as uneven coverage and strain diversity. Several assemblers (MEGAHIT, metaSPAdes, Velvet, Ray, IDBA-UD) will be applied and compared.

Tutorial	Slides	Description	Learning Objectives	Estimated Time
Metagenome Assembly: concepts and hands-on comparison of assemblers		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.	Recognize common sources of assembly ambiguity, such as repeats, sequencing errors, and uneven species abundance. Run multiple metagenome assemblers on sequencing reads and generate assembly statistics.	1H

Module 3: Assembly Evaluation

This module introduces methods for evaluating assembly quality by mapping reads back to contigs, visualizing alignments in IGV, and computing comprehensive assembly metrics using MetaQUAST against reference genomes.

Tutorial	Slides	Description	Learning Objectives	Estimated Time
Assembly Evaluation		This tutorial introduces the workflow for evaluating metagenomic assemblies by mapping reads back to contigs and computing assembly metrics using MetaQUAST.	Index and map Illumina reads to assembled contigs using BBMap. Process BAM files with samtools for downstream analysis and visualization. Visualize read assemblies in the IGV genome browser. Evaluate and compare multiple assemblies using MetaQUAST with reference genomes. Interpret QUAST metrics to assess assembly completeness and accuracy.	1H

Module 4: Binning and Classification

This module covers the recovery of individual genomes from metagenomic assemblies through binning, the application of standardized taxonomic classification using GTDB-Tk, and the quality assessment of metagenome-assembled genomes (MAGs) with CheckM2.

Tutorial	Slides	Description	Learning Objectives	Estimated Time
Metagenomic Binning and Classification		This tutorial introduces the workflow for clustering assembled metagenomic contigs into genomes (binning), evaluating their quality, and assigning taxonomic labels using modern bioinformatics tools.	Prepare coverage profiles from mapped sequencing reads for binning algorithms. Execute MaxBin and MetaBAT to cluster contigs into putative genomes. Classify recovered bins using GTDB-Tk for standardized, phylogeny-aware taxonomy. Evaluate bin quality (completeness, contamination, strain heterogeneity) with CheckM2. Apply MIMAG quality standards to select high-quality MAGs for downstream analysis.	1H

Module 5: Metagenomics Toolkit (Jupyter)

This module introduces the Metagenomics Toolkit, a comprehensive workflow for metagenomics analysis. You will learn how to prepare sequencing data, run the initial analysis workflow, and explore first steps of metagenomic data processing and interpretation.

Tutorial	Slides	Description	Learning Objectives	Estimated Time
Introduction to the Metagenomics-Toolkit		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.	Configure YAML parameter files for a multi-module metagenomics pipeline including QC, assembly, binning and annotation. Execute the full pipeline with Nextflow and understand the role of entry points. Navigate the hierarchical output structure of the Toolkit and locate key analysis results. Explore and visualize binning results, MAG quality metrics, and taxonomy with a Jupyter Notebook.	1H