Genome sequencing technologies, assembly, variant calling and statistical genomics

Dates: Lectures: 22 October – 2 November 2018. Presentation of project and exam: 29 – 30 November

Location: University of Oslo

Organisers: Arvind Sundaram, Torbjørn Rognes

Course code: IN-BIOS9000

Course webpage: UiO webpage here, detailed course page here

Registration: September 10

Credits: 10 ECTS
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 here by August 16
  • External students must register as visiting PhD students here by August 1

 

Lecturers:

  • Arvind Sundaram (Bioinformatician, Norwegian Sequencing Centre, Oslo University Hospital)
  • Timothy Hughes (Researcher, NORMENT, Oslo University Hospital)
  • Gregor Gilfillan (Researcher, Norwegian Sequencing Centre, Oslo University Hospital)
  • Ave Tooming-Klunderud (CEES, Faculty of Mathematics and Natural Sciences, University of Oslo)
  • Ivar Grytten (Doctoral Research Fellow, Department of Informatics, University of Oslo)

 

Description:

This 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.

 

Learning outcomes:

After this course you 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
  • 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
  • understand how to apply statistical methods to analyse relationships between annotated features on genomic tracks
  • 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 you should have a basic understanding of molecular biology as provided by an introductory course in bioinformatics, molecular biology, or genetics.
  • No formal background in bioinformatics or computer science is required, however, you must have a basic understanding of the unix shell. You should take an introductory unix course beforehand if you do not have these skills.

 

Evaluation: 

Project work and a written exam. The project work will be evaluated based on an oral presentation. Both exams have to be passed. 80% attendance is also required.