Master Metagenomics and Microbiome Data Analysis Using Linux

Are you ready to unlock the secrets of microbial communities that live inside us and all around us. Whether you're a life sciences student, a research scientist, or simply curious about the invisible world of microbes, this course will equip you with the essential skills to perform real-world metagenomics and microbiome data analysis using industry-standard tools like QIIME2, Kraken2, Bracken, and Linux-based pipelines. "Master Metagenomics and Microbiome Data Analysis Using Linux" is a comprehensive, hands-on course designed to take you from raw sequencing data to meaningful biological insights.

With a practical approach and clear guidance, this course will help you navigate the complex but exciting world of microbial community profiling using both 16S rRNA gene sequencing and whole-genome shotgun metagenomics. You will start by understanding the fundamentals of metagenomics, microbiomes, and how they are transforming fields like human health, agriculture, and environmental science. You'll explore the difference between 16S rRNA sequencing and shotgun sequencing, and learn where and how to access public datasets for your own analysis.

Next, you'll set up your Linux-based bioinformatics environment, either through WSL (Windows Subsystem for Linux) or VirtualBox, and get comfortable using basic Linux commands that are crucial for data preprocessing, file management, and running bioinformatics tools. From there, we dive deep into QIIME2, one of the most widely used platforms for microbiome analysis. You'll learn how to import your sequencing data, perform quality control, denoise reads using DADA2, and generate interactive visualizations.

We'll walk you through computing alpha and beta diversity, taxonomic classification, differential abundance testing, and how to create publication-quality plots that explain microbial community structure and variation. But we don't stop at 16S. This course also takes you into the powerful world of shotgun metagenomics using Kraken2, Bracken, and Krona for high-resolution taxonomic classification and microbial abundance estimation.