Biological data analysis

Teacher(s)

Segers Johan; SOMEBODY;

Language

French

Main themes

Taking into account the most frequently encountered needs of researchers in Biology, as well as the time
constraints, the course offers of two main modules : Linear Modeling, and Methods of Multivariate Analysis.
The examples presented are mainly drawn from researches in Ecology.

Aims

At the end of this learning unit, the student is able to :
1	The objectives are that, as a result of successfully attending this course, the students : ' Are aware of the necessity of planning any scientific experiment before it is started. ' Have practiced, in the frame of a personal scientific question, the principles of experimental design. ' Are able to review, choose, and apply knowingly the best adapted methods for modeling and analysing data from their domain of expertise in Biology. ' Are able to set up a scientific experiment, to manage the data generated by this experiment, to analyse them (usually with the help of a computer software), and to interprete critically the results. ' Have shown their ability to report a scientific experiment in a written document and through an oral communication. These reports may be elaborated in groups of two or three students.

Content

Module 1 (UCLouvain): Linear statistical modeling
– Simple and multiple linear regression, AN(C)OVA included
– Generalised linear models: logistic and Poisson regressionoisson
– Linear mixed models
– Implementation in R
Module 2 (UNamur): Multivariate data exploration
– Data matrices
– Useful techniques from matrix algebra
– Multiple linear regression (no inference)
– Principal component analysis
– Classification
– Canonical correspondence analysis
– Implementation in R and Excel

Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Lectures and exercise classes in computer rooms.
For Module 2 (UNamur), self-learning sessions and flipped classrooms; instructions will be given in the first course hour.

Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Each of the two teachers will give a grade on 10 and this will grade will count for 50 % in the total. To succeed, the sum of the two grades should at least be 10/20 and each grade should at least be 4/10. Partial grades of 5/10 and higher are credited for the running academic year.
Module 1 (UCLouvain) : written exam during the exam session. Dispensatory test for a part of the exam near the end of the lectures.
Module 2 (Unamur) : Continuous evaluation during flipped classrooms (50%) : multivariate analyses in Excel and interpretation of the results. Evaluation during exercise classes (50%) : multivariate data analyses in R and interpretation of the results. No second session.

Online resources

Moodle page: https://moodleucl.uclouvain.be/course/view.php?id=7525
Module 1 (UCLouvain): R scripts of the recommended book: http://highstat.com/index.php/analysing-ecological-data
Module 2 (UNamur)
– Self-study website: http://webapps.fundp.ac.be/umdb/biostats2017/
– Videos:
http://medias.save.fundp.ac.be/videos/webcampus/2016-cours-biostatistique-Depiereux/module-200-10.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2016-cours-biostatistique-Depiereux/module-210-10.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2016-cours-biostatistique-Depiereux/module-220-10.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2016-cours-biostatistique-Depiereux/module-220-20.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2016-cours-biostatistique-Depiereux/module-220-30.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2016-cours-biostatistique-Depiereux/module-230-10.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2017-cours-biostatistique-Depiereux/module-240-10.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2017-cours-biostatistique-Depiereux/module-240-20.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2017-cours-biostatistique-Depiereux/module-240-30.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2017-cours-biostatistique-Depiereux/module-240-40.mp4
http://medias.save.fundp.ac.be/videos/webcampus/2017-cours-biostatistique-Depiereux/module-240-50.mp4

Bibliography

• Dias cours magistraux, syllabus TP, bases de données, codes informatiques. Site web auto-apprentissage.
• Alain F. Zuur, Elena N. Iono, Graham M. Smith, Analysing Ecological Data, Springer Science, 2007 (non-obligatoire)

Teaching materials

• Dias cours magistraux, syllabus TP, bases de données, codes informatiques. Site web auto-apprentissage.

Faculty or entity

BIOL