Course content

This course provides a comprehensive introduction to central concepts and methods within modern genomics, with a primary focus on Next Generation Sequencing (NGS) technologies. NGS has fundamentally transformed biological and medical research by enabling rapid and accurate mapping of large volumes of DNA and RNA sequences. Today, the technology is a key research tool across a wide range of biological and medical disciplines and is used in diverse experimental and clinical applications.

Through lectures and practical exercises, students will gain insight into the entire sequencing workflow, from sample handling and library preparation to sequencing, data management, and analysis. The course covers the principles behind various sequencing technologies, current methods and protocols for DNA and RNA sequencing, and approaches for assessing the quality and reliability of experimental data.

Furthermore, the course introduces basic bioinformatic methods relevant for experimental design, data formats, quality control, preprocessing, and analysis of sequencing data. Through hands-on laboratory and bioinformatics exercises, students will gain experience with representative tools and workflows used in modern genomics research.

Learning outcome

Knowledge

Upon successful completion of the course, the candidate shall:

• be at the forefront of knowledge within high-throughput sequencing (Next Generation Sequencing, NGS), and master the scientific principles, challenges, and methods of the field.
• be able to evaluate the applicability and use of different NGS methods (for DNA and RNA sequencing) and associated bioinformatic processes in research and professional development projects.
• be capable of contributing to the development of new knowledge, methods, and interpretations within genomics and sequencing technology.
• be able to apply and continuously update their knowledge in new areas of the field.
• have in-depth knowledge of the most common data formats and bioinformatic methods used for processing and analysing datasets generated by NGS.

Skills

Upon successful completion of the course, the candidate shall:

• be able to formulate relevant research questions, plan, and carry out research and development work involving NGS.
• be able to conduct research and professional development work in NGS and genomics at a high international level.
• be able to handle complex scientific problems and critically assess established methods and practices within sequencing technologies and bioinformatics.
• be capable of collaborating effectively in interdisciplinary environments, particularly with bioinformaticians, regarding analysis and interpretation of datasets from NGS studies.
• be able to critically assess and interpret results from completed NGS projects.

General competence

Upon successful completion of the course, the candidate shall:

• be able to identify and reflect on new and relevant ethical issues related to the use of NGS technologies in research, and conduct their work with high scientific integrity.
• be able to initiate, lead, and manage complex research and development projects within genomics and sequencing technology.
• be able to communicate NGS-related research and development work through recognized national and international channels, and engage in scientific debates in relevant international forums.
• be able to assess the need for, and contribute to, innovation and methodological development within NGS and related research fields.

Learning methods and activities

Self-study, lectures, laboratory lectures (mandatory), laboratory exercises (mandatory), bioinformatics exercises (mandatory), and a semester project (mandatory).If fewer than 5 students register, learning activities may be adjusted and the feasibility of running the course will be evaluated.

Mandatory Activities

• Attendance at all lectures and exercises (minimum 80% attendance)
• Semester project

Compulsory assignments

• All lectures and excercises
• Semester paper

Recommended previous knowledge

Basic knowledge in molecular biology, molecular cell biology, and data analysis equivalent to:MOL4010, MOL3101, MOL3013, MOL3007, MOL8001, HBIOT2031, BI1001, TBT4170, BI2012, BI2014, BI3016, ST1201, ST1101, TDT4145.

Required previous knowledge

Education at the master’s level or similar, Medical students at the Student Research Programme, other candidates with a lower degree will be individually evaluated.