ECOS1179 Current topics in evolutionary genetics (5 cr)

Study level:
Advanced studies
Grading scale:
Responsible organisation:
Department of Biological and Environmental Science
Curriculum periods:
2020-2021, 2021-2022, 2022-2023

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Current topics in evolutionary genetics


The course teaches the students to use bioinformatics methods to analyse genetic and genomics data, so that they can understand processes affecting genetic diversity in wild populations. The course focuses on using variation in DNA sequences / genomes to understand selection pressures in wild populations.

After providing guidance intobasic sequence analysis and an introduction to using UNIX, the course then instructs students how to assemble and annotate next generation sequence data, and also how to map reads and call genetic variants (polymorphisms) from the data, and also how to view the data and associated annotation files. The course includes introductore lectures, demonstrations and computer-based practical exercises for genetic and genomic data analysis. Students are expected to complete independent and group interpretation tasks.

Learning outcomes

After completing the course, the student will

· is able to search genetic and genomics databases to retrieve appropriate data,

· understands principles behind different types of NGS technology,

· has skills to use UNIX command line to manipulate large data sets,

· can use appropriate bioinformatics tools to assemble and annotate a small genome,

· can identify and quantify genetic variation from genomic data,

· can identify signs of selection in samples, and

· can interpret his/her research critically and report back to others.

Additional information

Topic is announced at the beginning of the academic year when the course is offered. The course is offered every other year (odd years; spring semester) and involves hands-on data analysis.

Description of prerequisites


Completion methods

Method 1

Topics addressed in the course can change according to active research projects being pursued in the department. The course includes hands-on data analysis using modern methods.
Evaluation criteria:
1. Learning diary (35%) 2. Presentation (20% 3. Project (35%) 4. Course participation (10%)
Time of teaching:
Period 4
Select all marked parts
Parts of the completion methods

Participation in teaching (5 cr)

Participation in teaching
Grading scale:
Evaluation criteria:
Course participation; analysis project; report
Study methods:

The course includes hands-on data analysis using modern methods.