Genomics in Clinical and Biomedical Research

PhD course.

This course is available as a singular course.

The course will offer an overview of modern sequencing technologies. Including a practical introduction to bioinformatics using the R statistical language. This includes hands-on training in data preprocessing and normalization, as well as methods to explore results such as principal Component Analysis (PCA), clustering, annotation, pathway analysis, Gene Set Enrichment Analysis (GSEA), and how to use online databases and software tools. Course examples will be taken from genomic methods applied in medical research and practice.

PhD students and students at the Student Research Programme, or holders of a Norwegian master´s degree of five years or 3+2 years (or equivalent) may be admitted.

External applicants apply for the right to study by June 1st for courses that are taught in the autumn semester. Application is sent through SøknadsWeb. Please use the appliction code "9301 - Singular courses at the PhD level". If granted admission to the course students must register for class and exam in Studentweb by September 1st for autumn semester.

The course has a capacity of 12 students. If there are less than 8 applicants, the course will be cancelled.

If there are more applicants than available spaces in the course, students will be given priority from category 1 to 4:

1. PhD students, research fellows and students participating in the Student Research Programme at UiT, The Arctic University of Norway.

2. Participants in the Associate Professor Programme.

3. PhD students and students at a Medical Student Research Programme at other universities.

4. People who have minimum a master's degree or equivalent but have not been admitted to a PhD programme.

Recommended prerequisites: Basic course in statistics (bachelor's level).

Knowledge

The students should

• be able to assess how the genome, epigenome and transcriptome can contribute in a biomedical context familiar to them.
• understand how differences between cell- types influence results of genomic studies and be able to discuss advantages and disadvantages with bulk samples, liquid biopsies or cell sorting vs. single-cell and spatial methods.
• critically assess data analytical strategies in genomics in light of both statistical and the biomedical problems.
• recognize the ethical challenges in genomic research and data handling.
• provide an overview of the main databases where publicly available genomics data is deposited.

Skill

Students can

• critically examine a data analysis strategy within their own research area.
• chose a relevant data analysis methodology and carry it out on a dataset within their area of study.
• critically examine experimental designs in sequencing experiments.

General expertise

The student will be able to

• evaluate the opportunities but also the challenges presented by genomic data and assess new methods and technologies.

If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:

• BIO-8101 Functional genomics 4 ects

Language of instruction and examination

Schedule

More info about the coursework requirements

Re-sit examination