MED3069 – Statistics for modern biomedical data: a gentle introduction with Rstudio

The analysis of large databases is becoming increasingly crucial both to biomedical research and to the clinical practice. In such settings, the number of variables associated with each observation is very large, thus challenging classical statistical methods. Prominent examples in biomedicine include omics data, where many measurements across the genome, proteome, or metabolome are available, as well as electronic health records data that have large numbers of variables recorded for each patient. The statistical analysis of such data thus requires knowledge of complex methods adapted to the respective research questions. In this course, you will learn the basic principles and concepts in the statistical analysis of modern biomedical data. The course will focus on the three main tasks that are frequently involved in this setting: exploratory data analysis (visualization, clustering), identification of informative variables and multiple testing, prediction. You will also get a practical introduction to RStudio, a powerful open-source statistical software that will enable you to perform basic programming tasks, and to visualise and analyse modern data in biomedicine.

Knowledge

Upon completion of this course, you will be able to:

• identify specific statistical challenges associated with the analysis of large databases in biomedicine

• explain the analytical solution targeted to the large-data case and to the aim of the analysis, by understanding their underlying statistical properties

• have in-depth knowledge of research methods used in medicine and health sciences (common for all electives)

Skills

Upon completion of this course, you will be able to:

• identify the data analysis problem, and choose the appropriate type of statistical method

• implement a complete data analysis pipeline in RStudio: data loading and handling, visualisation, basic analyses

• critically evaluate the visualisation tools and analyses that are chosen in publications reporting molecular biology or molecular medicine findings

• manage practical tasks involved when analysing large datasets

• use RStudio for basic statistical analyses

General competence

Upon completion of this course, you will be able to:

• reflect on the statistical challenges specific to large data in biomedicine, due to the peculiar characteristics of such data setting, and draw consequent method choices

The course is reserved for students at the professional study in medicine.

Separate deadlines apply for admission to this course. See admission information and deadlines for elective courses.

The course admits up to 35 students

You must have completed the teaching and have attended or have a valid absence on the exam in MED2200 - Medisinstudiet, modul 2 in order to present yourself to the examination in the elective courses in the first elective period.

Teaching

• Full time study

• Form of teaching: lecturesfollowed by practical sessions with RStudio, including group discussions

• Students are expected to prepare to the teaching activities

• Course materials in the course content pages and in My Studies may not be distributed or published without special permission from the owner of the copyright to the material. The study of medicine is a full-time study

Presentation in groups.

Examination will take place in-class during the last day of the seminar.

Information about exams and grading, including previous exam papers and grading guidelines, at the Faculty of Medicine

You may submit your response in Norwegian, Swedish, Danish or English.

Grades are awarded on a pass/fail scale. Read more about the grading system.

All students who fail or have a valid reason for absence from the regular exam will be registered for a resit/deferred exam. In case of failing or having a valid reason for absence from the resit/deferred exam, the student may continue in the study program and take the exam in the subsequent elective period (the following January). The student must have taken and passed the elective course by the end of the second elective period in the study program at the latest.

Students who fail or have a valid reason for absence from the regular exam may be given a different form of assessment in the resit/deferred exam.