Computational Methods in Population Genetics Lecture, WS 2009/2010
Lecture with Exercises (Vorlesung mit Übung): (3 Credit Points)
Instructor: Prof. Dr. Dirk Metzler
Time:
Lecture: Each Monday from 10:15 to 11:45 in room C00.013
Exercises: Each Monday from 12:30 to 14:00 in computer room C00.005
Contents
Given population genetic data, how can we infer evolutionary and
ecological features like population substructure, change of population
size, recent speciation, natural selection and adaptation? Many
computational methods for this purpose have been proposed and most of
them are freely available in software packages. In this course we will
discuss the theoretical and practical aspects of these methods. The
theoretical aspects are the underlying models, statistical principles
and computational strategies. In the practical part we will try out
various software packages and explore under which circumstances they
are appropriate. Among the models that we discuss are the coalescent
process and its variants with structure and demography, the ancestral
selection graph, and the ancestral recombination graph. Among the
parameter estimation strategies are full-likelihood and full-Bayesian
methods, methods based on summary statistics, and Approximate-Bayesian
Computation. These methods use computational strategies like
importance sampling and variants of MCMC. Software: LAMARC, GENETREE,
Hudson's MS, IM/IMa, MIMAR,
etc...
Language: English
Announcement in official LMU course overview
web page last updated: Dirk Metzler, November 3, 2009