91̽»¨

The course is included in the master´s program in Bioinformatics, but is also offered as a freestanding course that can be included in e.g. master’s degrees in Biology, Molecular biology or Marine biology.

For admission to the course, at least 120 credits (or equivalent) in any of the following fields: natural sciences (including mathematics), medicine or pharmacy.

In addition, English proficiency is required to the level of English 6/English Course B from Swedish Upper Secondary School, or be certified by an internationally recognized test, for example TOEFL or IELTS or equivalent.

This course is an introduction to genomics and genomic variation with a focus on applying bioinformatical methods for analysing and comparing genomic data, primarily from bacteria. The course will cover different sequencing methods, the principles for sequencing data quality control, *de novo *genome* *assembly, and gene prediction and annotation. Tools for comparative bacterial genomics will be introduced. The course will emphasize analytical methods and how scientific questions guide methodological choices.

Many bioinformatics tools are command line-based, thus the course contains introductions to UNIX/BASH programming and the basics of Python programming with applications to sequence data. During the course. aspects of coding best practices, data sharing, and database quality will be discussed. The course is useful for those who wants to learn to apply bioinformatical methods for comparative sequence analysis with the aim of understanding evolution and function of genome-, gene-, and protein sequences.

The course is divided in sub-courses.

Sub-course 1; Command Line basics for bioinformatics, 4 credits.

Sub-course 2; Introduction to Python for bioinformatics, 4 credits.

Sub-course 3; Bioinformatics in Genomics final project, 7 credits.

On successful completion of the course the student will be able to:

Knowledge and understanding

• Demonstrate general knowledge of genomes and genomic variation.
• Describe different DNA sequencing technologies.
• Describe the principles behind de novo assembly, alignment, and annotation.
• Describe workflows in the analysis of next generation sequencing data.
• Identify bioinformatics tools used in genome analysis.

Competence and skills

• Find and download data for genomic analyses from public databases.
• Find information about bioinformatics tools and how to download, install and use them.
• Apply common tools to execute NGS data quality control, *de novo *assembly, and annotation of genomes.
• Utilize common tools for comparative genomics.
• Navigate and execute bioinformatics software in a command line interface.
• Write and use Python code for basic applications in bioinformatics.
• Perform basic code trouble shooting and refinement

Judgement and approach

• Critically assess the output from bioinformatics methods.
• Implement for code best practices in order to generate reproducible analyses.
• Make biological interpretations from genomic data.
• Understand the purpose of different methods and be able to select methods suitable for their own scientific application.

Sub-course 1; The learning activities of the sub course consists of lectures, practical data analysis and coding exercises in groups and individually.

Compulsory parts of the sub course are the practical sessions as shown in the course schedule.

Sub-course 2; The learning activities of the sub course consists of lectures, practical data analysis and coding exercises in groups and individually.

Compulsory parts of the sub course are the practical sessions as shown in the course schedule.

Sub-course 3; The sub course consists of a practical project that will be presented orally and in a written report. The project can be performed either individually or in pairs but the oral presentation and the written report are to be handed in individually.

The compulsory part of the sub course is the final oral project presentation and the written report.

Sub-course 1; The fulfilment of the Learning outcomes will be assessed through practical coding exercises.

Sub-course 2; The fulfilment of the Learning outcomes will be assessed through practical coding exercises.

Sub-course 3; The fulfilment of the Learning outcomes will be assessed through an individual project where the students are expected to analyse their own and/or publicly available genome data and present the results both orally and in a written report.

If a student who has been failed twice for the same examination element wishes to change examiner before the next examination session, such a request is to be granted unless there are specific reasons to the contrary (Chapter 6 Section 22 HF).

If a student has received a certificate of disability study support from the University 91̽»¨ with a recommendation of adapted examination and/or adapted forms of assessment, an examiner may decide, if this is consistent with the course’s intended learning outcomes and provided that no unreasonable resources would be needed, to grant the student adapted examination and/or adapted forms of assessment.

If a course has been discontinued or undergone major changes, the student must be offered at least two examination sessions in addition to ordinary examination sessions. These sessions are to be spread over a period of at least one year but no more than two years after the course has been discontinued/changed. The same applies to placement and internship (VFU) except that this is restricted to only one further examination session.

If a student has been notified that they fulfil the requirements for being a student at Riksidrottsuniversitetet (RIU student), to combine elite sports activities with studies, the examiner is entitled to decide on adaptation of examinations if this is done in accordance with the Local rules regarding RIU students at the University 91̽»¨.

Sub-course 1; Command Line basics for bioinformatics: 4 credits (Pass or Fail only)

Sub-course 2; Introduction to Python for bioinformatics: 4 credits (Pass or Fail only)

Sub-course 3; Bioinformatics in Genomics final project 7 credits (Pass with distinction, Pass or Fail).

Final grade; The grading scale comprises: Pass with Distinction (VG), Pass (G) and Fail (U).

Requirements for Pass (G): Passed practical exercises and passed oral and written presentation of the final project. Pass with distinction (VG) will only be awarded based on the final project.

The results of and possible changes to the course will be shared with students who participated in the evaluation and students who are starting the course.