PHVIT9560 Bioinformatics with emphasis on analysis of high throughput sequencing data Course description

The course will introduce students to basic bioinformatics including best practice when setting up and managing bioinformatics projects. The course covers introduction to high throughput sequencing technologies and will give students hands-on experience with the analysis of data from various sequencing platforms. Applications that are included in the practical part are processing of raw data reads, control of quantity and quality of data (FASTQC), expression analysis of small RNA sequencing data (miRNA) and transcriptome sequencing (mRNA-seq) data, genomic DNA sequencing. Some post-analytical tools like gene ontology enrichment analysis and clustering/heat-maps of differentially expressed genes are introduced to students and included in the hands-on exercises.

This course is primarily aimed at PhD candidates admitted to the PhD programme in Health Sciences. General terms for admission to the course is a completed master’s degree in molecular biology or equivalent qualification (e.g. completed MABIO4410). Priority will be given to PhD candidates from OsloMet.

Note that all students must have a laptop not more than 2 years old (mac is easiest, but windows with linux also works). The laptop must be able to connect to a wireless network, and the student must have administrative rights to download and install software and bioinformatic packages.

The course can also be offered to students who have been admitted to the "Health Science Research Programme, 60 ECTS", by prior approval from the supervisor and based on given guidelines for the research programme.

Admission to the course may also be offered to master students attending the Master’s Programme in Biomedicine / Master in Health and Technology, by prior approval from the thesis supervisor and depending on course capacity. These students must have completed the first 60 ECTS credits of the Master’s programme including MABIO4410, and write a master’s project where this course is considered relevant.

On completion of the course, the PhD candidate has achieved the following learning outcomes, defined in terms of knowledge, skills, and general competence:

Knowledge

The PhD candidate

• knows how to conduct bioinformatics analysis projects in agreement with best practice (transparency and reproducibility) in the field of bioinformatic science’s philosophy
• is in the forefront of knowledge about the current high throughput sequencing (HTS) technologies and understands the differences, benefits and drawbacks of these HTS technologies
• can evaluate and make sound decisions on which platform and bioinformatic approach to use for different HTS projects
• can contribute to development of new knowledge and interpret results from various HTS applications

Skills

The PhD candidate can

• plan a HTS research project and choose optimal sequencing platform
• carry out the relevant bioinformatic analyses both on the command-line (unix) and R-studio and utilize web-based resources like Geneontology.org and Genbank E-utilities.
• interpret the results of bioinformatics analysis of HTS (e.g. reliability, sensitivity and specificity) and judge their value for answering biological questions
• disseminate the results of HTS based research

General competence

The PhD candidate can

• argue in favour of particular HTS technologies or bioinformatic approaches on the basis of current knowledge
• argue in favour of the kind of materials and the number of samples to select/include in different kinds of HTS projects
• can participate in discussions on HTS methodology

The course consists of three weeks consecutive work that includes the following teaching methods: self-study including exercises/questionaries related to background theory and set up labtop for the course (one week). Lectures and seminars, and practical exercises in the use of different software programmes for analysis of HTS data (two week). The outcomes of the practical exercises in last week are discussed in plenary sessions. The practical exercises are obligatory.

It is required that students complete all the obligatory practical exercises.

All obligatory exercises must be completed to take the final exam. The final exam is an individual home examination, 6 hours.

Grades are awarded on the basis of pass or fail.

One internal examiner.