Advanced Genomics Analysis

6 EC

Semester 1, period 3

5053ADGA6Y

Owner Bachelor Biomedische Wetenschappen
Coordinator prof. dr. A.D.J. van Dijk
Part of Exchange Programme Faculty of Science, specialisation BSc Biomedical Sciences, year 1Minor Biomedical Sciences: From basic biology to booming business, Minor Molecular Life Sciences, year 1Bachelor Biology, year 3Bachelor Bèta-gamma, major Biomedische Wetenschappen, year 3Bachelor Biomedical sciences, Frontiers in Medical Biology, year 3Bachelor Biomedical sciences, differentiation Patient Oriented Research, year 3Double Bachelor Biomedical Sciences and Medicine, year 3
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Course manual 2025/2026

Course content

Biomedical research has been revolutionized by the use of “omics” technologies such as Next Generation Sequencing (NGS). For example, transcriptome sequencing is used to quantify the expression level of all genes across the genome. Omics technologies make it possible to analyze which genes respond to experimental treatments, or to determine which genes are relevant for diseases. These type of omics analyses yields large data sets, and analyzing these data to get meaningful results, as well as interpretation of the results, is far from trivial. In particular, it requires expertise with respect to bioinformatics, data analysis, and statistics. It is of great importance for biomedical students to gain experience with such omics data analysis. In this course, we cover this entire data analysis process, based on a real-life experimental data.

Objectives

  • Explain basic principles of transcriptomics technologies
  • Explain the (statistical) concepts and principles of selected bioinformatics methods required for analyzing and interpreting large scale omics data sets
  • Demonstrate advanced scripting skills for R and Linux command line
  • Demonstrate ability to use relevant transcriptomics bioinformatics methods and tools in a correct way, to answer biomedical research questions.
  • Formulate relevant omics data analysis questions, generate results, and critically interpret the results
  • Structure complex omics data and results in clear figures and tables

Teaching methods

  • Self-study
  • Laptop seminar
  • Lecture

Learning activities

Activity

Hours

Hoorcollege

25

Laptopcollege

110

Tentamen

3

Self study

30

Total

168

(6 EC x 28 uur)

Attendance

  • Some course components require compulsory attendance. If compulsory attendance applies, this will be indicated in the Course Catalogue which can be consulted via the UvA-website. The rationale for and implementation of this compulsory attendance may vary per course and, if applicable, is included in the Course Manual.

    • Additional requirements for this course:

    Absence needs to be communicated to the course coordinator.

    Assessment

    Item and weight Details

    Final grade

    1 (50%)

    Tentamen

    		Must be ≥ 5

    1 (50%)

    Project

    		Must be ≥ 5

    The exam is an open book exam (you can use the material provided throughout the course).

    Inspection of assessed work

    Announcement on canvas.

    Assignments

    In the third and fourth week of the course, during the laptop seminars you will work on a project to analyze a transcriptomics dataset. A report on this has to be handed in which will be graded. You will work on this project in pairs.

    In the third and fourth week of the course, during the laptop seminars you will work on a project to analyze a transcriptomics dataset. A report on this has to be handed in which will be graded. You will work on this project in pairs.

    Fraud and plagiarism

    The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

    Course structure

    Weeknummer Onderwerpen Studiestof
    1  introduction RNA-sequencing lecture (slides)
    2 data analysis for interpretating and integrating RNA-sequencing results lecture (slides)
    3 biological interpretation of RNA-sequencing results project handout
    4 self-study, report writing, exam  

    Processed student feedback

    Based on feedback from the previous (first) version of the course, we implemented the following adaptations:

    1. We will further increase options for personal feedback by having an additional teaching assistant available.
    2. We will discuss the interim formative tests.
    3. Course manual is being revised.
    4. At the beginning of the project (week 3) we will make sure that the transition between the guided practical work and the more independent project work goes smoothly, by monitoring more closely how things are going so we can give additional guidance if needed.

    Contact information

    Coordinator

    • prof. dr. A.D.J. van Dijk

    Staff

    • dr. Thijs van Boxtel
    • Szymon Szrajer
    • K. Wissink