This special topics course introduces participants to the fundamentals of bioinformatics and the computational analysis of next-generation sequencing (NGS) data. Bioinformatics integrates computational methods, statistical techniques, and biological sciences to analyze and interpret large-scale biological datasets. Advances in NGS technologies have transformed modern genomics and biomedical research by enabling rapid, high-throughput sequencing of genetic material.

The course provides both theoretical foundations and practical experience in bioinformatics workflows commonly used in genomics research. Through a combination of lectures, demonstrations, and hands-on laboratory exercises, participants will learn the principles of NGS data processing, analysis, and interpretation using contemporary bioinformatics tools and computational methods.

Topics covered include sequencing technologies, biological data formats, quality control (QC) and preprocessing of sequencing data, sequence alignment and read mapping, variant discovery and variant calling workflows, functional annotation, and interpretation of genomic variants. Participants will also gain exposure to commonly used bioinformatics software, command-line tools, and computational workflows used in modern genomics pipelines.

Emphasis is placed on practical data analysis skills and reproducible computational workflows that can be applied to real-world biological and biomedical research projects. Participants will work with example datasets and develop the ability to perform foundational NGS analyses independently.

Upon successful completion of the course, participants will be able to:

• Understand the foundational principles of bioinformatics and genomics data analysis  
• Explain the workflow of next-generation sequencing data processing  
• Perform quality assessment and preprocessing of sequencing datasets  
• Conduct sequence alignment and read mapping analyses  
• Execute basic variant calling and annotation workflows  
• Interpret genomic analysis results in biological research contexts  
• Utilize bioinformatics software and command-line tools for NGS analysis