Thursday 16-17 or by appointment (coordination needed in any case).
Extra classes on Sunday 17.4 and Tuesday 19.4
(same hour and room).
The goal of this course is to introduce some of the major topics in Genetics, and gain a statistical perspective on them.
We will start with a brief introduction to Genetics concepts, and gradually start elaborating on statistical aspects
of the questions that come up. As needed, we will introduce relevant areas of statistics in some detail.
In the latter part of the course we will pick a hot current research
topic and concentrate on it for a few weeks.
The final grade will be based on a combination of homework (3-4), a final take home exam, and possibly a class presentation.
Tentative topics list (each topic 1-2 weeks):
Introduction to Genetics and quantitative Genetics
Mutation models: stochastic processes; estimation from data
Phylogenetic analysis: algorithms and inference
Human population genetics: statistical inference about human history
Estimation of ancestry
Principal component analysis in Genetics
Genome-wide association studies (GWAS)
Major public data sources like HapMap, 1000Genome project and
4*4 Mutation models: definitions, estimation and hypothesis
Relevant reading material: any textbook in statistical genetics,
such as Yang (2006),
by Huelsenbeck and Crandall which we discussed in class.
STR mutation models: simple random walk and (δμ)2
method; more complex and realistic models; existence of stationary
distribution; estimation and model selection.
Relevant reading material:
11 in Nielsen (2005) on models of microsatellite evolution,
al. (2003) whose data is used in HW1.
Basic knowledge of mathematical foundations: Calculus; Linear Algebra
Undergraduate courses in: Probability; Theoretical Statistics
Statistical programming experience in R is an advantage
Prior basic knowledge in Biology and Genetics is an advantage
Some recommended books
Human Evolutionary Genetics by Jobling, Hurles and Tyler-Smith
An excellent introduction to Human Genetics, with a quantitative flavor Principles of Population Genetics by Hartl and Clark
Comprehensive overview of computational methods in Genetics Statistical Methods in Molecular Evolution edited by R. Nielsen
Collection of tutorials and reviews on major topics in Statistical Genetics