Learning outcomes

Know how to apply regression analyses

Learn how to perform and interpret sequence alignments and cluster trees.

Goals

Know how to apply a variety of tools to perform advanced analyses in science.

This course will introduce students to bioinformatics. Students will learn how to perform sequence alignments, understand how to derive and interpret alignment scores, and learn how to cluster data.

Content

The course comprises two main modules: statistics and bioinformatics.

Statistics:

1.     ANOVA 1 and 2

2.     Non-parametric tests

3.     Multiple linear regression

4.     ANCOVA

5.     Linear mixed models

Bioinformatics

6.     Sequence alignment

7.     Data clustering.

Exercices

Practical sessions on a computer, using R software and sequence alignment software.

Assessment method

The assessment is divided into theoretical questions and resolution of exercises, both for the statistics and bioinformatics modules.

Resolution of exercises: practical sessions scheduled during the semester (2 stats sessions + 1 bioinfo session),

Stats: computer-based, open-book analysis of statistical data with R.

Bioinfo: Sequence analyzes and data clustering, open book.

Theory evaluation:

Stats: Theoretical questions (not obligatory) after the practical work on the subject concerned (10 mins), at the start of the next practical work. During these tests, you will not be able to consult the course or access the internet. These pre-session tests can grant you exemption from the first session theory exam. To obtain the pre-session score, we delete the lowest score, and average the rest. To obtain exemption from the theory exam, the student must have passed a majority of tests (number of tests - 2) and have an average score greater than 10.

Those who do not take the theoretical exams or do not pass, take the theoretical exam in the first session.

Students who, despite passing the mini-tests, wish to take the exam in the first session can do so. This implies that they give up their pre-session mark for the theoretical part.

Bioinformatics: The theory of the bioinformatics module will be evaluated with the practical part. Students are expected to discuss and interpret the results of the practical exercises and answer questions about the underlying theory.

Global mark

The overall mark is left to the discretion of the teaching team based on the mark of the mini-tests or the June exam (40%), the mark of practical work (40%) and the mark of the bioinformatics part (20%). To pass the EU an overall score >10 is necessary. However, a mark of at least 8 in each part (Resolution exercises and theory) for each of the modules, Statistics and Bioinformatics, is necessary to pass the teaching unit (UE). Otherwise the average is capped at 9.

The student's participation during the course can give them a bonus of up to 0.5 points on the first session rating.

Sources, references and any support material

1. Material accessible on webcampus

2. Optional: Mohr, D. L., et al. (2021). Statistical Methods, Elsevier Science.

Language of instruction

Français
Training Study programme Block Credits Mandatory
Bachelor in Biology Standard 0 5
Bachelor in Biology Standard 3 5