PHVIT9560 Bioinformatikk med fordypning i analyse av data fra massiv parallell sekvensering Emneplan

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

This course adopts a basis and critical perspective of Needs Led Research. The process linked to the first step in the research pathway dealing with the identification and prioritization of research issues. Needs Led Research is characterized by two parallel processes; user involvementandidentification and verification of evidence gaps by systematic searches in databases.

User involvementis characterized by processes in which users/stakeholders (eg patients, relatives, health workers) suggest, discuss, prioritize and agree on research questions they consider important. Several frameworks and methodologies for user involvement in research exist, of which the most relevant ones will be focused on in this course.

Identification and verification of evidence gaps, being the core of evidence-based research, is based on a systematic and transparent review of existing research in order to guide new studies in answering relevant and valid research questions. The course will focus on how to identify, verify and document evidence gaps by systematically searching the existing evidence.

The course will be run as a five-day course over three months.

This course is primarily aimed at PhD candidates admitted to the PhD Programme in Health Sciences but is also open to other applicants. Admission requirements are a completed major, master's degree (120 ECTS credits) or equivalent qualification.

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.

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

Knowledge

The PhD candidate:

• has an outstanding insight into the most relevant methodologies for user involvement in decision-making processes for identifying relevant research questions
• is at the forefront of knowledge about how to identify and verify evidence gap.

Skills

The PhD candidate can:

• identify, facilitate and use the most suitable methodology in which users/stakeholders suggest, discuss, prioritize and agree on research questions they consider important, in a given context/study
• identify, verify and document evidence gaps by systematically searching the existing evidence, that is, conducting literature searches and selecting relevant and high-quality articles

​​​​​​​General competence

The PhD candidate can:

• utilize processes for user involvement, as well as identification and verification of evidence gaps, in order to identify relevant and unanswered research questions.
• facilitate Needs Led Research in close collaboration with the relevant field of practice
• develop project management and communication skills.

Work and teaching methods consist of lectures, seminars, small group work and discussions, self-study, and practical exercises. In the seminars the students will present and discuss the status of their work and progress in plenary sessions.

None

Individual home examination, to be submitted no more than two weeks after the end of the course. The candidates must submit an essay, which will describe the background and validation of the Needs Led Research questions to be answered. The essay, consisting of up to 5000 words, must describe the methodology and process for developing the Needs Led Research questions. This includes description of the process for user involvement, as well as the process for identification and verification of evidence gaps.