300217 PUE Exercises in Population Genetics (2017W)
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Sprache: Englisch
Lehrende
Termine
Lectures : Thursday afternoon 13:30-16:30, either at the Institute for Population Genetics (Computer room, Building HA (4th floor), University of Veterinary Medicine, Veterinärpl. 1, Vienna) or at the Faculty of Mathematics (PC room 2, Faculty of Mathematics, Oskar-Morgenstern-Platz 1, Vienna)
05/10/17 13:30-16:30 Institute for Population Genetics12/10/17 13:30-16:30 Faculty of Mathematics
19/10/17 13:30-16:30 Faculty of Mathematics
09/11/17 13:30-16:30 Faculty of Mathematics
16/11/17 13:30-16:30 Institute for Population Genetics
23/11/17 13:30-16:30 Faculty of Mathematics
30/11/17 13:30-16:30 Institute for Population Genetics
07/12/17 13:30-16:30 Institute for Population Genetics
14/12/17 13:30-16:30 Institute for Population Genetics
11/01/18 13:30-16:30 Faculty of Mathematics
18/01/18 13:30-16:30 Institute for Population Genetics
25/01/18 13:30-16:30 Faculty of Mathematics
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Mindestanforderungen und Beurteilungsmaßstab
Prüfungsstoff
Literatur
Suggested reading:
Hedrick, Genetics of Populations, Jones and Bartlett
Crawley, Statistics: An Introduction Using R, Wiley
Barrett, Linux Pocket Guide: Essential Commands, Reilly
Paradis, R for beginners (available online from CRAN)
Hedrick, Genetics of Populations, Jones and Bartlett
Crawley, Statistics: An Introduction Using R, Wiley
Barrett, Linux Pocket Guide: Essential Commands, Reilly
Paradis, R for beginners (available online from CRAN)
Zuordnung im Vorlesungsverzeichnis
MES 1
Letzte Änderung: Mo 07.09.2020 15:43
Introduction to R and R graphics (ggplot2), Wright Fisher simulations, Coalescent simulations, application of neutrality tests, basic handling of NGS data, simulations of quantitative traitsPre-requisites: basic knowledge of R and of the UNIX command lineGoals:
Students are familiar with the R programming language and commonly used tools in population genetics (MS, PAML, alignment tools). The students are able to simulate neutral and selective processes in populations. They can apply widely used neutrality tests to genome scale data.