2024-2025 / GENE0448-1

Phylogenetic methods

Duration

20h Th, 15h Pr

Number of credits

 Master in biology of organisms and ecology, research focus3 crédits 
 Master in biology of organisms and ecology, teaching focus3 crédits 
 Master in biology of organisms and ecology, professional focus in integrated management of aquatic resources and aquaculture3 crédits 
 Master in biology of organisms and ecology, professional focus in conservation biology : biodiversity and management3 crédits 

Lecturer

Denis Baurain

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

[UPDATED IN 2024] This course aims to provide the bases of phylogenetic methodology required for the understanding of the courses of Taxonomy and phylogeny of animals [BIOL2041-1] and Taxonomy and phylogeny of chlorophyll lines [BIOL2040-1].

  • Reminder on (molecular) phylogenetics
  • Sequence alignment - global alignment (NW), local alignment (SW, BLAST), multiple alignment (ClustalW) and profiles
  • Parsimony - phylogenetic trees, tree length (Fitch's algorithm), character state mapping, search heuristics, statistical support (e.g., bootstrap) and congruence among trees
  • Distance methods - distance matrices, W(U)PGMA, NJ and models of sequence evolution
  • Probabilistic methods - likelihood (principle, algorithms, models, advantages and model selection), Bayesian inference (principle and algorithms, strict and relaxed molecular clocks)
  • Phylogenomics - principle, datasets, supertrees, supermatrices, stochastic and systematic errors, CAT model, applications

Learning outcomes of the learning unit

  • Theory: At the end of this course, students will be able to explain the main concepts, methods and algorithms used in phylogenetics. They will have an intuitive understanding of probabilistic methods and will be able to justify their preferential use over other approaches. This requires, above all, to have UNDERSTOOD the course material. In this sense, this course is probably different from some other subjects of the curriculum in biology, in which mere memorization may be enough to pass the examination.
  • Exercises: For some algorithms (specified in class), an APPLICATION using pen and paper to solve a toy example may be requested.
  • Applications: The practical analysis of a dataset in a phylogenetic context will have been covered during computer practicals. Students will thus be able to concretely reproduce it on their own datasets.

Prerequisite knowledge and skills

The course assumes no prerequisites in computer science, but relies on a basic knowledge of mathematics and molecular genetics. In principle, the necessary level in both subjects is reached at the end of the 3rd year of BA in biology.

Planned learning activities and teaching methods

  • Theoretical lectures, demonstrations and supervised exercises: 11 x ~2h.
  • Computer practicals (Seaview and R): 4 x ~3h.

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

Face-to-face course


Additional information:

This is a face-to-face course. Attending the lectures is strongly encouraged as they are designed so as to facilitate understanding and assimilation of the course material.

Course materials and recommended or required readings

Platform(s) used for course materials:
- eCampus


Further information:

Computer practicals will make use of the following book but students are not expected to buy it: Paradis E. (2012) Analysis of Phylogenetics and Evolution with R, 2nd edition, Springer, 386 pages

http://www.springer.com/978-1-4614-1742-2
https://cran.r-project.org/web/packages/ape/index.html

Exam(s) in session

Any session

- In-person

written exam ( multiple-choice questionnaire, open-ended questions )

Other : Computer practical test


Further information:

The assessment is a written exam (January session) comprising two parts:

  • knowledge questions (understanding and reformulation of theory): True/False questions, figures to complete, MCQs and gap-fill texts;
  • know-how questions (algorithms to be applied): standard exercises in which the wording may have been modified compared with the exercises solved in class or available online.
It is possible to practise for the exam on the eCampus platform, which contains a large proportion of the questions (including knowledge questions) likely to be used in the exam. However, on the day of the exam, it will be paper-based and closed-course.

A computer practical test will also be organised on the R servers. This can only increase the mark already obtained (= bonus), from 0 to 2 points. For example, a student who has achieved a mark of 15/20 in the theory exam, but a perfect score in the practical work, will receive a final mark of 17/20 (15+2).

Work placement(s)

Organisational remarks and main changes to the course

Taking notes on a laptop or tablet is allowed. However, students are expected not to surf or chat in the classroom.
Course materials and additional documents will be made available on eCampus.

Contacts

Prof. Denis Baurain
Institut de Botanique B22 (P70)
denis.baurain@uliege.be

Mr. Mick Van Vlierberghe (teaching assistant)
mvanvlierberghe@uliege.be

Mrs Rosa Gago
rgago@uliege.be

Association of one or more MOOCs