Phylogenetic methods

Duration

20h Th, 15h Pr

Number of credits

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 2019] 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: 10 x 2h.
• Computer practicals (Seaview and R): 4 x 4h.

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

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.

Organisational adjustments related to the current health context

The remaining courses will be delivered online using eCampus. The theoretical exam might be turned to an online exam. Computer practicals are very likely to be delivered online too.
As announced during the last lesson, and due to the health crisis, the course evaluation will be adapted as follows: the overall mark will be that of the theoretical exam organized in January 2021 on the eCampus platform (such as T/F, MCQ, exercises, short answers). However, students who take the trouble to complete the optional personal assignment related to practical work (cf. message of 7/12/2020 sent by D. Sirjacobs) may, if successful, see their mark increased by one or two points (upwards, obviously, but with a maximum of 20/20 for the overall mark).

Recommended or required readings

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 http://ape-package.ird.fr/APER.html

Assessment methods and criteria

Below you will find information on the evaluation methods planned for in-person and remote exams as well as those planned for hybrid sessions. Depending on how the health crisis evolves, the chosen method will be communicated to you no later than one month before the start of the exam session.

Evaluation has two parts:

• 75% : written examination (January session) including three theory questions (free-form explanation of a theoretical concept) and one exercise (algorithm to be applied);
• 25% : computer practical examination (at the end of the course) where one has to analyze a new dataset (praticals and practical examination are mandatory and organized only once a year).

Work placement(s)

Organizational remarks

Taking notes on a laptop or tablet is allowed. However, students are expected not to surf or chat in the classroom.

Contacts

Prof. Denis Baurain Institut de Botanique B22 (P70) denis.baurain@uliege.be
Assistant: Dr. Damien Sirjacobs Institut de Botanique B22 (P70) 04/366.38.54 D.Sirjacobs@uliege.be