Next Generation Sequencing Data Analysis with clinical applications

Education facts

Code: BMA231

Human genome sequencing is increasingly used in a variety of health care systems. This laboratory method is used daily to identify changes (mutations or gene expression profiles) that may contribute to a diagnosis and/or treatment selection. In this course we will focus on the analysis and interpretation of clinical NGS data by applying various bioinformatics webtools. <br> We will cover essential concepts in molecular biology and genetics, principles on NGS applications (with a focus on targeted resequencing and RNA sequencing). Besides, you will practice how to analyze NGS data from its quality assessment, pre-processing (filtering and mapping), variant calling and gene expression to its functional interpretation and visualization. Most analyses will be performed using Galaxy ([https://usegalaxy.eu/)](<https://usegalaxy.eu/)>), an open source, web-based platform for data intensive biomedical research. Note that no command line tools will be used. For data visualization and statistical analysis, you will be introduced to R, a widely used statistical tool (no prior knowledge is require). <br> The course will be given in English and it includes a combination of lectures, practical sessions and home assignments.<br> Computer and internet access are required since all communication concerning the course and relevant documents, such as lectures, exercises and literature, will be posted at the virtual learning environment.

Entry requirements

For admission to the course, a Bachelor's degree is required of 180 credits or equivalent in any of the fields of medicine, nursing or natural sciences and English 6/English, level 2.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Next Generation Sequencing Data Analysis with clinical applications

  University of Gothenburg

  Start date: 31 August 2026

  End date: 20 December 2026

  Pace of study: 33 %