Bioinformatics Methods for next Generation Sequencing Analysis

Dates: 3 – 7 October 2022.

Location: St.Olavs Hospital/NTNU, Trondheim.

Organiser: Morten Beck Rye.

Evaluation: Report based with grade pass/fail.

Course code: MOL8008

Registration: Is Closed. If you wish to earn credits, you will find information about this HERE.

Registration deadline: September 2nd, 2022.

Credits: 7,5 ECTS.

 

Lecturers:

  • Morten Beck Rye (NTNU)
  • Vidar Beisvåg (NTNU)
  • Pål Sætrom (NTNU)

 

Course description

The course will introduce bioinformatic approaches, tools and pipelines for computational analyses of Next Generation Sequencing (NGS) data. Focus will be on analysis methods for coding and non-coding RNA from RNA-seq, and transcription factors and epigenetic markers from ChIP-Seq. The course will cover strategies, methods and workflows used for analyses of such data, including mapping to reference genomes, feature extraction, and statistical analysis. In addition, the biological interpretation of output from such analyses will be presented as case studies from scientific journals.

 

Course program

There will be a one week intensive period with combined lectures (50%) and hands-on exercises (50%). This is followed by a ~1 month period of self-study and project work. The grading will be based on the project work.

 

Learning outcomes and competence

After completing the course the student should be able to: Create and use an analysis pipeline for topics introduced Understand the bioinformatics approaches used for different tasks in NGS Have an overview of the type of biological questions that are typically assessed using NGS Assist in the design and implementation of an experiment using NGS at their own facility.

 

Prerequisites

Recommended previous knowledge: Attending students should be familiar with basic high-level programming of scripting languages like Python, R and Matlab. Some basic knowledge in applied bioinformatics is recommended. Required previous knowledge: Masters degree in relevant programmes. Medical Doctors degree or medical students at The Student Research Programme. Candidates with other or lower degree will be assessed individually.