The focus of this course in Spring 2003 is on statistical genomic
issues arising primarily in gene mapping for experimental
crosses. Much attention will be on quantitative trait loci (QTL), with
emphasis on practical issues of "model selection", finding the genetic
architecture "best" supported by the phenotypic and genotypic data in
hand. We will devote considerable attention to recent studies that use
microarray data as complex phenotypic traits.
Strategies for fine-mapping will be addressed along the way.
The primary text is the
draft of a book being written joingly
with Zhao-Bang Zeng, Gary Churchill, and Karl Broman.
Intended audience is primarily biologists wanting to gain a deeper
understanding of concepts and strategic issues. Basic ideas of key
methods will be developed with considerable attention to analysis of published data.
The objective of this course is to familiarize students with
state-of-the-art statistical methods for analyzing experiments
involving genomic data in the form of molecular markers,
genetic linkage maps and complex phenotypic (quantitative) traits
[including gene expression microarray data across multiple
conditions].
Issues involving whole-genome analysis and model selection for genetic
architecture will be highlighted.
This is designed for
biology students with a year sequence in statistical methods
(Stat/For/Hort 571-572 or equivalent)
and a general introduction to concepts of Mendelian inheritance
(Genetics 466 or equivalent).
Credits 3
Class Number Stat 692
Class Hours 9:30-10:45 tue/thu
World Wide Web http://www.stat.wisc.edu/~yandell/statgen/course/
Instructor Brian Yandell, 4367 CSSC, 262-1157
yandell@stat.wisc.edu
Grading is being sorted out this Fall. There will be a few assignments
during the semester, and an opportunity for class
projects. Assignments will attempt to mimic research conditions, with
the goal often being to infer QTL and/or make decisions on model
architecture. Term projects may in some cases be done as joint
collaborations.
Return to Statistical Genomics Page.
www.stat.wisc.edu/~yandell/statgen/course/
by Brian Yandell
(yandell@stat.wisc.edu)