2023-2024 / GBIO0030-1

Computational approaches to statistical generics


25h Th, 15h Pr, 35h Proj.

Number of credits

 Master of Science (MSc) in Biomedical Engineering5 crédits 
 Master of Science (MSc) in Data Science5 crédits 
 Master of Science (MSc) in Computer Science and Engineering5 crédits 
 Master of Science (MSc) in Data Science and Engineering5 crédits 
 Master of Science (MSc) in Computer Science5 crédits 


Kristel Van Steen

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

In this course we focus on "from statistical to biological interactions" or "family-based designs", depending on the student population. The course is not a classic course but a project-driven one, with face-to-face meeting moments to give theoretical and practical background information.
The actual content of the course may be adapted during the year, depending on needs of the students. Theoretical parts may look as follows:
"From statistical to biological interactions:

  • Biological interactions (what, why, how)
  • Statistical interactions (what, why, how)
  • Bridging the gap between both (what, why, how)
  "Family-based designs":

  • Family-based designs in the genomic and post-genomic era (what, why, how)
  • Family-based association studies (what, why, how)
  • Family structure and population genetics (what, why, how)

Learning outcomes of the learning unit

The following aspects of the analysis pipeline constitute "learning outcomes": 1) data cleansing (quality control), 2) selection of the appropriate tool and correct implementation of it, 3) understanding the pros and cons of the selected tool, 4) grasping the analysis context, 5) being able to adequately interpret the analysis results.

This course contributes to the learning outcomes II.1, II.2, II.3, III.1, III.2, III.3, III.4, IV.1, IV.2, VI.1, VI.2, VI.4, VII.3, VII.4, VII.5 of the MSc in biomedical engineering.

This course contributes to the learning outcomes II.1, II.2, II.3, III.1, III.2, III.3, III.4, IV.1, IV.2, VI.1, VI.2, VI.4, VII.3, VII.4, VII.5 of the MSc in computer science and engineering.

Prerequisite knowledge and skills

A background in biostatistics, (bio)informatics or statistical genetics is a pro. Alternatively, one has taken either one of the following courses: GBIO0002, GBIO0009.

Planned learning activities and teaching methods

The course is a project-driven one: assignments are given that, all together, constitute a project. Approximately 4 theoretical sessions are organized, during which general aspects related to the project work are explained (see "course content"). In-between sessions may be organized to help out the students with the practical work (upon request).

Mode of delivery (face to face, distance learning, hybrid learning)

In-person or online depending on COVID-19 evolutions.

Recommended or required readings

There is no mandatory textbook. Useful references will be given as the course progresses. All course material is posted on the course website, which is accessible via http://bio3.giga.ulg.ac.be/archana_bhardwaj/?Courses

Students are assessed via project work, the defense of which serves as oral exam. This holds true for both examination sessions (i.e., in June and in September).
Evaluation criteria are:

  • the clarity of the presented work (via slides + report)
  • correctness and accuracy
  • originality and provided background information (with links to the theoretical course notes)
  • presentation skills
  • general understanding (assessed via questions-answers while discussing the presented work)
Details about the final grade repartition will be provided on the course website. Handing in all intermediate project work, in time, as well as taking the oral exam, is necessary to pass this course. The second term exam is based on ameliorating the worst component of the project work and will be organized in the same format as the first term exam.

Work placement(s)

Organisational remarks and main changes to the course

Course language: English
The course is organized in the second semester. The detailed calendar and announcements are available on the course website.
Depending on the number of students who enrol on this course, content and practical organization of group work may be adapted, to maximize the experience in a multi-disciplinary environment.


Kristel Van Steen - e-mail kristel.vansteen@ulg.ac.be
Assistant: to be communicated
Preferred contact mode: e-mail (include GBIO0030 in the subject title) or personal contact, after a lecture or by appointment. Online meetings when the COVID-19 situation requires doing so.

Association of one or more MOOCs