Microbiome data analysis

The basic contents of the course are listed in this field.

• Introduction to the microbiome and its importance in human health and disease
• Overview of microbiome research workflows, including study design and common applications
• Sample collection and preservation strategies for microbiome studies
• DNA isolation from microbiome samples and key considerations for microbial sequencing
• Principles of PCR amplification and barcoded sequencing used in next-generation sequencing (NGS)
• Introduction to microbial marker gene sequencing (e.g., 16S rRNA gene sequencing)
• Introduction to the QIIME 2 bioinformatics platform for microbiome data analysis
• Importing and managing sequencing datasets in QIIME 2
• Microbial diversity analysis using alpha and beta diversity metrics
• Taxonomic classification of microbial sequences
• Visualization and interpretation of microbial community composition and relative abundance
• Practical exercises using the QIIME 2 Moving Pictures example dataset.

• Explain the basic principles of microbiome research and the importance of microbial communities in human health and disease
• Describe the main experimental steps in microbiome studies, including sample collection, preservation, DNA isolation, and PCR amplification for sequencing
• Conduct microbial diversity analyses using common alpha and beta diversity metrics
• Assign microbial taxonomy and interpret microbial community composition and relative abundance profiles
• Interpret and visualize microbiome analysis results generated using QIIME 2

Students should have a basic understanding of molecular biology and sequencing concepts. Prior exposure to microbiology, genomics, or bioinformatics is beneficial but not required.
Participants are expected to use their own laptops / computers for the practical sessions. Students should install the QIIME 2 software environment on their laptops / computers (ask help from ICT if you don’t have admin rights to install it), following the official installation instructions provided on the QIIME 2 website.
Install QIIME 2 Amplicon Distribution following the instructions provided in the link below.
https://docs.qiime2.org/2024.10/install/native/
Contact Tejesvi Mysore (mysore.tejesvi (at) oulu.fi) if you need further information / details.

Tejesvi Mysore, PhD, Docent,

Research Unit of Clinical Medicine,

Faculty of Medicine.

Email: mysore.tejesvi (at)oulu.fi

The course will use a combination of lecture materials, online resources, and practical tutorials.

• Lecture slides and course notes provided by the instructor through Moodle
• QIIME 2 official documentation and tutorials, particularly the Moving Pictures tutorial dataset
• Selected scientific articles on microbiome research and microbial community analysis
• Online resources related to microbiome sequencing workflows and bioinformatics analysis

All required materials, datasets, and instructions for the practical exercises will be made available to students through the Moodle learning environment.

The course will be delivered through online lectures and guided practical exercises. Students will participate in live teaching sessions via Zoom that introduce the theoretical background of microbiome research and the computational workflow used in microbiome data analysis.
Learning tasks include:
• Attending online lectures covering microbiome concepts, sample processing, sequencing strategies, and bioinformatics analysis
• Following guided demonstrations and hands-on exercises using the QIIME 2 platform
• Working with the QIIME 2 Moving Pictures dataset to perform microbiome sequence analysis
• Completing analysis steps including data import, sequence quality control, diversity analysis, taxonomic classification, and visualization of microbial communities
• Reviewing course materials and analysis outputs provided through the Moodle learning platform

Students are expected to actively follow the analysis workflow and participate in the practical sessions to complete the course.

The course will be delivered as online teaching. All teaching sessions will take place via Zoom, and the Moodle learning environment will be used to distribute course materials, instructions for practical exercises, datasets, and additional learning resources.
Teaching consists of online lectures combined with guided practical demonstrations and exercises in microbiome data analysis using the QIIME 2 platform. Students will follow the analysis workflow and perform the steps during the sessions using the provided example dataset.
The workload is structured as follows:
• Guided teaching: approximately 8–10 hours of online lectures and guided practical demonstrations
• Independent study: approximately 12–17 hours for reviewing course materials, following the QIIME 2 analysis workflow, and practicing the analysis steps independently
Teaching methods and learning activities include:
• online lectures introducing microbiome concepts and sequencing workflows
• guided demonstrations of microbiome data analysis using QIIME 2
• practical hands-on exercises using the QIIME 2 Moving Pictures dataset
• independent work where students repeat and practice the analysis steps
• online learning through Moodle, including access to lecture slides, datasets, and analysis instructions