Targeted Metagenomics for Gut Microbiome
Unlock the secrets of the human gut! This crash course is designed to take you from raw sequencing data to meaningful biological insights using Targeted Metagenomics. Whether you are a student or a professional, this course will equip you with the high-demand bioinformatics skills needed to navigate the "second genome" of the human body.
- 5.0/5
- English
- Updated Sep 2026
About this course
The human gut microbiome is a powerhouse of health, influencing everything from immunity to mental health. This course provides a comprehensive deep dive into Targeted Metagenomics, specifically focusing on 16S rRNA amplicon sequencing.
Unlike broad shotgun approaches, targeted metagenomics is a cost-effective, high-resolution method for identifying microbial diversity. Participants will journey through the entire bioinformatics pipeline: from raw sequence quality control and chimera removal to taxonomic classification and advanced statistical visualization. You will work with real-world gut microbiome datasets to identify biomarkers for health and disease.
🌟 Why This Course?
Clinical Relevance: Learn how microbial dysbiosis links to IBD, obesity, and diabetes.
Industry Demand: Bioinformaticians with microbiome expertise are highly sought after in pharma, diagnostics, and AgTech.
Hands-on Learning: Move beyond theory with practical labs using industry-standard tools like QIIME2 and R.
What you will learn
Skills you will gain
Certification
Available
Issued by Dr. OmicsCourse curriculum
1 moduleWhat you need to start
- Basic Biology: Understanding of genetics and microbiology.
- Technical Basics: Familiarity with the Linux/Unix command line (preferred but not mandatory—introductory modules provided).
- Software: A laptop with at least 8GB RAM.
Who this course is for
- Bioinformatics Students: Looking to specialize in a high-growth niche.
- Microbiologists: Wanting to transition from culture-based methods to "in silico" analysis.
- Medical Researchers: Seeking to incorporate microbiome signatures into clinical studies.
- Data Scientists: Interested in biological Big Data and ecological modeling