Subject description for 2020/2021

Population genomics


This course brings together an international collection of lecturers and course participants to study techniques for the analysis of population genomic data.

Course description

Topics include population genetic theory, introduction to command line, data formats, coalescence/population demography, analysis of population structure, adaptive evolution and inferring selection, gene-environment interactions, landscape genomics, and the analysis of admixture/hybridisation.

This is an intensive one-week course with lectures (including discussions) and hands-on exercises, Monday to Friday. About half the time will be devoted to lectures, and the other half to exercises. Lectures and exercises are 35 hours in total, and self-study is estimated to 30 hours. Preparation time for written report (home exam) is estimated to 35 hours. The total workload is thus about 100 hours.


The course consists of two sessions per day:

· Session 1: welcome, practicalities, course introduction

· Session 2: introduction to command line (unix), data formats, data conversion

· Session 3: population genetic theory

· Session 4: introduction to R

· Session 5: analysis of population structure

· Session 6: population history, demographic inference, coalescence

· Session 7: genomic basis of adaptive evolution and inference of selection

· Session 8: landscape genomics, gene-environment correlations

· Session 9: admixture and introgression/hybridization

· Session 10: Open lab and introduction to the home exam


Students bring their own laptops with the last version of R and RStudio installed. Some R packages will also be needed. The students will receive a reading list and software installation instructions before the start of the course and are expected to prepare well.


The evaluation will be report-based. The students will analyze a population genomic dataset (preferably their own data or data related to their own research topic), interpret and write a report. The students deliver the report within a month after the end of the course.


Basic knowledge of genetics and statistics. Prior experience with command-line programs (in particular R/Rstudio) or Unix will be an advantage


No tuition fees. Costs for semester registration and course literature apply.

Learning outcomes

After having completed the course, the students should:


  • have acquired in-depth understanding of topics, theories, processes, tools and methods used in population genomics.


  • have acquired the tools and abilities to conduct population genomic analyses, including data quality control, analyses, and interpretation of results.

General competencies:

  • be able to exchange views and experiences with evolutionary and molecular biologists and contribute to the development of good practice;
  • develop an understanding of modern scientific research in population genomics.

Course type

Elective: PhD Aquatic Biosciences

Teaching activities and methods

The course consists of a series of lectures, demonstrations and computer laboratories that cover theory and practice of population genomics analyses.

Recommended prior knowledge

Basic knowledge of genetics and statistics. Prior experience with command-line programs (in particular R/Rstudio) or Unix will be an advantage.

Course evaluation

Evaluation using mid-term and final surveys. Students are also encouraged to participate in the central quality surveys.

Assessment and examinations

Assignment, grading scale Bestått - Ikke bestått
  • Compulsory participation , comprises 0/100 of the grade, grading scale Godkjent - Ikke godkjent.
Course coordinator
Start semester Spring 2021 Teaching language English ECTS Credits 5 Course location Bodø Faculty
Faculty of Biosciences and Aquaculture