Microbiome Bioinformatics Training: Linux, 16S & Metagenomics

Linux, 16S rRNA & Metagenomics Using QIIME 2

Instructor: Dr. Scott Kelley

Dr. Kelley is a Professor in the Department of Biology at SDSU and current Leader of the Biomedical Methods Group. Dr. Kelley earned his PhD in Molecular Systematics at the University of Colorado, Boulder. His primary research interests are in Bioinformatics, Human Microbiome, Viral Genomics and Diversity, Microbial Diversity and Phylogenetics, and Microbiology of the Built Environment. He is a pioneer in the studies of built environment contamination, publishing the first molecular study of the microbiology of the indoor settings and has decades of experience studying air and water environmental microbiology. Dr. Kelley also invented SourceTracker, considered a seminal advance in the ability to determine sources of microbial contamination in complex mixed communities such as polluted water systems. He has extensive experience in bioinformatic tool development and analysis of microbial diversity. Dr. Kelley is currently a subcontract PI for an R01 studying the role of the gut microbiome in Polycystic Ovary Syndrome. Dr. Kelley’s research has produced over 90 peer-reviewed publications.

This three-day (9-hour) workshop introduces the basics of microbiome data analysis using hands-on exercises. Participants will learn how to work in a Linux environment, analyze 16S rRNA gene sequencing data using QIIME 2, and explore metagenomics concepts including quality control, taxonomy, and functional interpretation.

Session 1 · Day 1 (3 hours)

June 2026 · 1:00 PM – 4:00 PM PST · 6330 Alvarado Court, Suite 220-01, San Diego, CA 92120

Introduction to Linux and the command line
Navigating the file system (directories, paths, permissions)
Basic commands
Viewing and editing files
Installing and managing software environments

Session 2 · Day 2 (3 hours)

June 2026 · 1:00 PM – 4:00 PM PST · 6330 Alvarado Court, Suite 220-01, San Diego, CA 92120

Introduction to microbiome data and 16S rRNA sequencing
Overview of analysis workflows using QIIME 2
Importing sequencing data
Quality control and sequence denoising
Feature table construction and representative sequences
Taxonomic classification of microbial communities
Generating and interpreting basic visualizations

Session 3 · Day 3 (3 hours)

June 2026 · 1:00 PM – 4:00 PM PST · 6330 Alvarado Court, Suite 220-01, San Diego, CA 92120

Introduction to shotgun metagenomics and its applications
Differences between 16S rRNA and whole metagenome sequencing
Quality control and preprocessing of metagenomic reads
Taxonomic classification using Kaiju and reference databases
Metagenome assembly using MEGAHIT
Binning of assembled contigs into genomes using MaxBin
Functional annotation and pathway analysis
Microbial diversity and community structure from metagenomic data
Interpreting taxonomic and functional profiling results

Linux Commands

Navigate and manage files and directories in a Linux environment
Execute basic command-line operations and edit files
Install and manage bioinformatics software and environments

16S rRNA Analysis

Understand the principles of 16S rRNA gene sequencing
Perform microbiome data analysis using QIIME 2
Conduct quality control and sequence denoising
Generate feature tables and representative sequences
Assign taxonomy and interpret microbial composition
Create and interpret basic microbiome visualizations

Metagenomics Analysis

Distinguish between 16S rRNA and shotgun metagenomics approaches
Perform preprocessing and quality control of metagenomic data
Conduct taxonomic classification of metagenomic reads
Assemble sequencing reads into contigs and genomes
Perform genome binning and functional annotation
Interpret taxonomic and functional profiles of microbial communities

Data Interpretation and Application

Evaluate microbial diversity and community structure
Interpret results from both 16S and metagenomic workflows
Apply bioinformatics tools to real-world microbiome research questions

Hardware	Who Provides	Notes
Laptop, 1 per student	Attendee	—

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