Genomics

6 EC

Semester 1, period 1

5234GENO6Y

Owner Master Biomedical Sciences
Coordinator dr. M.J. Jonker
Part of Master Biomedical Sciences, track Oncology, Master Biomedical Sciences, track Cognitive Neurobiology and Clinical Neurophysiology, Master Biomedical Sciences, track Psychopharmacology and Pathophysiology, Master Biomedical Sciences, track Infection and Immunity, Master Biomedical Sciences, track Cell Biology and Advanced Microscopy, Master Biomedical Sciences, track Experimental Internal Medicine, Master Biomedical Sciences, track Molecular Neurosciences, Master Biomedical Sciences, track Physiology of Synapses and Networks, Master Biomedical Sciences, track Developmental and Therapeutic Biology, Master Biomedical Sciences, track Medical Biochemistry and Biotechnology, Major Big Biomedical Data Analysis, year 1Master Biomedical Sciences, track Cardiovascular Sciences, year 1Master Forensic Science, year 2

Course manual 2023/2024

Study materials

Literature

  • Available on Canvas

Practical training material

  • Available on Canvas

Software

  • R or RStudio. All other software will be provided

Objectives

  • Explain basic principles of genomics technologies.
  • Maintain Bioinformatics Labjournal
  • Advanced scripting skills for relevant programming languages; R and Linux bash.
  • Explain the (statistical) concepts and principles of some selected relevant bioinformatics methods that are required for analyzing and interpreting large scale genomics data sets.
  • Is able to clearly structure complex omics data/display in clear figures and tables.
  • Demonstrate that he/she can use selected relevant genomics bioinformatics methods and tools in a correct way, and such that answers can be formulated to biomedical research questions.
  • Demonstrate that he/she can formulate relevant data analysis questions, generate results, and interpret the results such that these data analysis questions can be answered.
  • Demonstrate that he/she can experiment with large scale omics data sets in a data-driven research approach.

Teaching methods

  • Lecture
  • Computer lab session/practical training
  • Self-study
  • Supervision/feedback meeting
  • Working independently on e.g. a project or thesis
  • Presentation/symposium

Lecture: Theoretical background.

Computer lab session/practical training: Training in using software, computer languages, big data analysis, data visualization and statistics.

Presentation: Formulating answers to biomedical and biological research questions.

Self-study: Training in using software, computer languages, big data analysis, data visualization and statistics.

Working independently on a project: Learning how to use genomics data analysis and bioinformatics to answer biomedical and biological research questions.

Learning activities

Activity

Hours

Laptop practicals

150

Self study

18

Total

168

(6 EC x 28 uur)

Attendance

Requirements of the programme concerning attendance (OER-B):

  1. Attendance during practical components exercises is mandatory.

Additional requirements for this course:

Attendance during practical components exercises is mandatory.

Absence must be reported to the coordinator.

Assessment

Item and weight Details

Final grade

Failure to meet a deadline means that the student cannot achieve a score higher than a 6.5

Inspection of assessed work

This is communicated by email

Assignments

The computer practicals can be made in groups and are not graded, feedback is provided in plenary sessions.

The final assignment can be made in groups and is graded (see assessment), feedback is provided in writing.

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 Genome Wide Association Studies See Canvas
2 Variant Calling, ChIPseq Analysis See Canvas
3 MetaGenomics, Genome analysis with long read data See Canvas
4 Assignment See Canvas
5    
6    
7    
8    

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

  • dr. M.J. Jonker