262-0200-00L Bayesian Phylodynamics
| Semester | Spring Semester 2024 |
| Lecturers | T. Vaughan, T. Stadler |
| Periodicity | yearly recurring course |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | |
|---|---|---|---|---|
| 262-0200-00 G | Bayesian Phylodynamics Block course in the second week after the semester (10-14 June 2024); all day. Lecture will take place in classroom in Basel. Further details will be communicated by the lecturer to registered students in due time. | 2 hrs | T. Vaughan, T. Stadler | |
| 262-0200-00 A | Bayesian Phylodynamics | 2 hrs | T. Vaughan, T. Stadler |
Catalogue data
| Abstract | How fast is the latest variant of COVID-19 spreading? How fast was Ebola spreading in West Africa? Where did these epidemics come from? How can we construct the phylogenetic tree of great apes, and did gene flow occur between different apes? At the end of the course, students will have designed, performed, presented, and discussed their own phylodynamic data analysis to answer such questions. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Attendees will extend their knowledge of Bayesian phylodynamics obtained in the “Computational Biology” class (636-0017-00L) and will learn how to apply this theory to real world data. The main theoretical concepts introduced are: * Bayesian statistics * Phylogenetic and phylodynamic models * Markov Chain Monte Carlo methods Attendees will apply these concepts to a number of applications yielding biological insight into: * Epidemiology * Pathogen evolution * Macroevolution of species | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | In the first part of the block course, we will present the theoretical concepts of Bayesian phylodynamics. This will involve both lectures and tutorials, during which students will gain experience in using the software package BEAST 2 to apply these theoretical concepts to empirical data. We use previously published datasets on e.g. Ebola, Zika, Yellow Fever, Apes, and Penguins for analysis. Examples of these practical tutorials are available on https://taming-the-beast.org/. In the second part of the block course, students will choose a set of real genetic sequence data and possibly some non-genetic metadata. They will then design and conduct a research project in which they perform Bayesian phylogenetic analyses of their chosen data. A final written report on the research project will be submitted after the block course for grading | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | All material will be available on https://taming-the-beast.org/. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | The following books provide excellent background material: • Drummond, A. & Bouckaert, R. 2015. Bayesian evolutionary analysis with BEAST. • Yang, Z. 2014. Molecular Evolution: A Statistical Approach. • Felsenstein, J. 2003. Inferring Phylogenies. More detailed information is available on https://taming-the-beast.org/. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | This class builds upon the content which we teach in the Computational Biology class (636-0017-00L). Attendees must have either taken the Computational Biology class or acquired the content elsewhere. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competencies |
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Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 4 credits |
| Examiners | T. Vaughan |
| Type | graded semester performance |
| Language of examination | English |
| Repetition | Repetition only possible after re-enrolling for the course unit. |
| Additional information on mode of examination | Written report about the conducted research project (max. 5 pages, min font size 11). Report has to be submitted by August 30, 2024. |
Learning materials
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |