262-0200-00L Bayesian Phylodynamics – Taming the BEAST
| Semester | Spring Semester 2021 |
| Lecturers | T. Stadler, T. Vaughan |
| Periodicity | yearly recurring course |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 262-0200-00 G | Bayesian Phylodynamics – Taming the BEAST Block course in first week after the semester (June 7-11); all day. The whole course can be followed virtually and – given the pandemic situation allows – will be held at D-BSSE in Basel. | 2 hrs |
| T. Stadler, T. Vaughan | |||||||||||||||
| 262-0200-00 A | Bayesian Phylodynamics – Taming the BEAST | 2 hrs | T. Stadler, T. Vaughan |
Catalogue data
| Abstract | How fast is COVID-19 spreading at the moment? How fast was Ebola spreading in West Africa? Where and when did these epidemic outbreak start? 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 | During the first part of the block course, the theoretical concepts of Bayesian phylodynamics will be presented by us as well as leading international researchers in that area. The presentations will be followed by attendees using the software package BEAST v2 to apply these theoretical concepts to empirical data. We will use previously published datasets on e.g. COVID-19, 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 choose an empirical dataset of genetic sequencing data and possibly some non-genetic metadata. They then design and conduct a research project in which they perform Bayesian phylogenetic analyses of their dataset. A final written report on the research project has to 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. |
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. Stadler, 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, 1.5 line spacing). Report has to be submitted by August 31. |
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. |
