Dates: 28th October to November 8th, 2024.
Location: University of Oslo.
Organiser: Torbjørn Rognes. Please contact Torbjørn for course related questions.
Course webpage: HERE. Link to ReadTheDocs HERE.
Course code: IN-BIOS9000.
Credits: 10 ECTS.
Evaluation: There will be a 2-hour written exam, and the project work will be evaluated based on an oral presentation. Both exams have to be passed in the same semester. 80% attendance is required to be allowed to take the exams.
Registration: HERE. Registration deadline: 16th September. Kindly indicate in the registration form whether or not you intend to earn credits. If you know already now that you want to follow this course, please sign up through the options below:
UiO students must register at Studweb by September 15th.
External students must, in addition, get register as visiting PhD students:
NOTE: All NORBIS students who are travelling to attend this course must send a detailed budget to contact-norbis@uib.no to ensure travel funding to this course.
Lecturers:
- Arvind Sundaram, Research scientist, Norwegian Sequencing Centre, Oslo University Hospital.
- Ave Tooming-Klunderud, CEES, Faculty of Mathematics and Natural Sciences, University of Oslo.
- Bastiaan Star, CEES, Dept. of Biosciences, University of Oslo.
- Rolf Skotheim, Dept. of Informatics, University of Oslo
- Karin Lagesen, Section for Epidemiology, Norwegian Veterinary Institute.
- Milena Pavlovic, Dept. of Informatics, University of Oslo.
- Sigve Nakken, Oslo University Hospital.
- Thomas Haverkamp, Section for Epidemiology, Norwegian Veterinary Institute.
- Torbjørn Rognes, Research Group for Biomedical Informatics / Centre for Bioinformatics, Dept. of Informatics, University of Oslo.
- Trine B. Rounge, Centre for Bioinformatics, Dept. of Pharmacy, University of Oslo.
- Ying Sheng, Dept. of Medical Genetics, Oslo University Hospital.
Course description
The course provides knowledge of sequencing technologies and hands-on experience with the analysis of data from several sequencing platforms and for various applications. The two main applications that will be covered are de novo genome assembly and variant calling (SNPs and structural variants), while other aspects like control of quantity and quality of data will also be included. Furthermore, the course will show how to use statistical genomics to analyse features of annotated genomes.
Course program
The course will start with 2 continuous weeks (weeks 44 to 45) of lectures and hands-on exercises Monday to Friday each week, from 9.15 to 17.00, including 1 hour lunch break. This starts on Monday 28 October 2024 and ends on Friday 8 November 2024. During the evenings the students are supposed to self-study for 2 hours by reading articles etc. A detailed course schedule can be found HERE.
The exam will be a combination of the following two parts:
- An individual home project combined with an oral exam presentation of the home project followed by questioning / discussion on December 9th and 10th. Students will present their work to 2 teachers, followed by some questioning (approx 20 minutes in total for each student). This home exam will be handed out to all participants after the lectures. Time slots will be assigned randomly.
- A 2 hour written digital exam on December 10th.
Learning outcomes and competence
After completing this course, the students will:
- Understand the differences, benefits and drawbacks of the most current high throughput sequencing (HTS) technologies, and be able to decide which platform to use in what way for the different applications of HTS, in particular genome assembly and variant calling.
- Be able to evaluate data quality and quantity as well as perform bioinformatics analysis, both on the command-line and through web-based frameworks, with data tailored towards applications like genome assembly and variant calling.
- Know the algorithms and statistical methods involved in sequence alignment, mapping, assembly and variant calling.
- Be able to report on bioinformatics analysis in such a way that the methods used and steps taken are transparent, thus enhancing reproducibility.
- Be aware of, and know to deal with, the ethical and data-sensitivity issues surrounding sequencing data derived from human subjects.
- Be able to critically evaluate, validate and judge the results of bioinformatics analysis of HTS experiments in terms of underlying assumptions, reliability, sensitivity and specificity, and evaluate their value for answering biological questions.
Prerequisites
We recommend that participants should have a basic understanding of molecular biology as provided by an introductory course in bioinformatics, molecular biology, or genetics.
No formal background in computer science is required, however, students must have a basic understanding of the unix shell. Students should take an introductory unix course beforehand if they do not have these skills. The university offers Software Carpentry workshops that enable participants to fulfill this requirement.