SISG 2008

The Department of Biostatistics at the University of Washington and the Department of Statistics at the University of Auckland announce the 2008 Summer Institute in Statistical Genetics (New Zealand) to be held on the campus of the University of Auckland December 9-16, 2008.

Registration and Enquiries

Registration can be completed online or by printing and mailing the online registration page to:

Summer Institute in Statistical Genetics
University of Auckland, Department of Statistics
Private Bag 92019
Auckland 1142

Email enquiries can be sent to s.walker@auckland.ac.nz

Location

SISG 2008 will be held from 9 - 16 December 2008 in Lecture Theatres on ground floor of the Maths/Physics Building (Building 303), 38 Princes Street, Auckland, New Zealand.

Deadlines and Fees

Participation in any module cannot be guaranteed for registrations received after Monday, October 27, 2008. The Registration Fees are NZD $600 per module, reduced to NZD $500 for academic and government participants. These Fees are reduced to NZD $500 per module (NZD $400 for academic and government participants) for registrations received on or before Monday October 27, 2008. The registration fees cover tuition and course materials and coffee breaks. Meals and accommodation are not covered. No textbooks are required or supplied, but books recommended as background reading are listed below.

A NZD $100 processing fee will be deducted from refunds requested after Monday October 27, 2008. No refunds will be processed after Monday December 1, 2008.

Payment can be made with all major credit cards online via a secure server. Mail payments to the mail address shown above can be made with a purchase order (New Zealand companies and organizations only) or by cheque or money order in New Zealand dollars drawn on a New Zealand bank. Cheques should be made payable to the University of Auckland. Please email s.walker@auckland.ac.nz for wire transfer instructions.

Computing

Most modules will incorporate computing and participants are encouraged to bring laptop computers with them. They will have free online access while they are on the University of Auckland campus.

Participants enrolled in Module 6 (Computing for Statistical Genetics) should download and install R and consider installing Bioconductor. To do so, after installing R, enter this at the command line:
source("http://bioconductor.org/biocLite.R")
biocLite()

Participants enrolled in Module 3 (Introduction to QTL Mapping) should download and install Windows QTL Cartographer v2.5.

Accommodation

The Copthorne Hotel on Anzac Avenue http://www.millenniumhotels.co.nz/copthorneanzacavenue/index.html offers a rate of $115 per night (call reservations and mention Summer Institue of Statistical Genetics). However, they are already fully booked for the 8th and 14th of December.

The Quadrant Hotel http://www.thequadrant.com/ has rooms from $130. We don't have a special price for the institute.

There are many other hotels in downtown Auckland: see http://www.tourism.net.nz/region/auckland/auckland---auckland-city/accommodation/hotels/

Budget options for students include Princeton (just across the road) and Grafton Hall of Residence (a little further away, 20-30 minute walk).

Travel

The university is approximately 30 minutes drive from Auckland International Airport. Options for travel between the airport and the university include the Airbus ($15 one way), frequent shuttles (approx. $30) and taxis (approx. $60).

Instructors

Sharon R. Browning

Senior Lecturer in Statistics

University of Auckland

John S. Buckleton

Principal Scientist

ESR, New Zealand

James M. Curran

Associate Professor of Statistics

University of Auckland

Rebecca W. Doerge

Professor of Statistics,

Purdue University

Michel Georges

Professor of Molecular Genetics

Universite de Liege

Kent E. Holsinger

Professor of Ecology and Evolutionary Biology,

University of Connecticut

Thomas Lumley

Associate Professor of Biostatistics,

University of Washington

William M. Muir

Professor of Genetics

Purdue University

Dahlia M. Nielsen

Research Assistant Professor of Genetics,

North Carolina State University

Kenneth M. Rice

Assistant Professor of Biostatistics,

University of Washington

J. Bruce Walsh

Professor of Ecology and Evolutionary Biology

University of Arizona

Bruce S. Weir

Professor and Chair of Biostatistics, University of Washington;

Adjunct Professor of Statistics, University of Auckland

Zhao-Bang Zeng

Reynolds Distinguished Professor of Statistics and Genetics,

North Carolina State University

Modules

Module 1: Population Genetic Data Analysis

Instructors: Kent Holsinger and Bruce Weir

Dates: Tuesday December 9 and Wednesday December 10

Estimates and sample variances of allele frequencies, testing for Hardy-Weinberg and linkage disequilibrium, characterization of population structure with F-statistics and principal components. A Bayesian approach to disequilibrium and population structure. Relationship estimation. Basis for genotype data cleaning in whole-genome studies. Use of public domain software, including GDA and Hickory. Many of the concepts are illustrated with analyses of HapMap data.

Background reading: Weir, B.S. (1996). ``Genetic Data Analysis II.'' Sinauer.

Module 2: Quantitative Genetics

Instructors: Bill Muir and Bruce Walsh

Dates: Tuesday December 9 and Wednesday December 10

Provides a foundation for Module 3. Quantitative Genetics is the analysis of complex characters where both genetic and environment factors contribute to trait variation. Since this includes most traits of interest, such as disease susceptibility, crop yield, and all microarray data, a working knowledge of quantitative genetics is critical in diverse fields from plant and animal breeding, human genetics, genomics, to ecology and evolutionary biology. The course will cover the basics of quantitative genetics including: Fisher's variance decomposition, covariance between relatives, heritability, inbreeding and crossbreeding, and response to selection. Also an introduction to advanced topics such as QTL mapping, mixed models, correlated characters, and the multivariate response to selection

Background reading: Falconer, D.S. and T.F.C. Mackay. (1996). ``Introduction to Quantitative Genetics, 4th ed.,'' Longman.

Module 3: Introduction to QTL Mapping

Instructors: Rebecca Doerge and Zhao-Bang Zeng

Dates: Thursday December 11 and Friday December 12

Assumes the material in Module 2. This module will systematically introduce statistical methods for mapping quantitative trait loci (QTL) in experimental cross populations. Topics include experimental designs, linkage map construction, single-marker analyses, interval mapping, composite interval mapping and multiple interval mapping. Significance threshold for genome scan and model selection will also be discussed. Use public domain software Windows QTL-Cartographer for computer lab exercises. Emphasis is on procedures for QTL mapping data analysis and appropriate interpretation of mapping results rather than on formulas.

Module 4: Association Mapping

Instructors: Sharon Browning, Michel Georges and Dahlia Nielsen

Dates: Thursday December 11 and Friday December 12

This module is an introduction to association mapping, focusing on human, plant and animal populations and informed by findings from the HapMap project, the Wellcome Trust Case Control Consortium and other whole-genome association studies. Topics include theory of linkage disequilibrium and mapping, population and family-based association techniques for discrete and continuous traits, methods for detecting and accounting for population structure, multiple testing issues, and genotyping strategies. Analysis of dense SNP maps. Phasing and haplotype blocks. Assumes material in Module 1. Examples for real data, including a discussion of linkage disequilibrium in plant and animal populations. Computer exercises will provide hands-on experience with publicly available software packages.

Module 5: Interpreting DNA Evidence

Instructors: John Buckleton, James Curran and Bruce Weir

Dates: Thursday December 11 and Friday December 12

Assumes material in Module 1. The module will be of use to forensic scientists as well as to wildlife biologists. General framework for expressing the quantitative strength of DNA evidence. Genotype probabilities for one or two individuals. Use of genetic markers for forensic calculations, parentage and relationship estimation, and remains identification. Effects of population structure. Analysis of mixed profiles from multiple contributors. The concept of ``identity.'' Expected numbers of matches and partial matches in large databases. Y- and mitochondrial markers.

Background reading: Balding, D.J. (2005) ``Weight-of-evidence for forensic DNA profiles,'' Wiley Buckleton, J.S., C.M. Triggs and S.J. Walsh. (2004). ``Forensic DNA Evidence Interpretation,'' CRC Press.

Module 6: Computing for Statistical Genetics

Instructors: Thomas Lumley and Ken Rice

Dates: Monday December 15 and Tuesday December 16

This module introduces software for analysis of genetic data in the R statistical environment. It assumes no prior knowledge of R. Data management in R, programming concepts for R, and standard regression analyses will be discussed. These topics will be followed by analysis more specific to genetic data, including association analysis, and haplotype inference. Use of the extensive collection of genomics packages from the Bioconductor project will be introduced. Finally, the use of R as an interface to other more specialized, `legacy' software will be demonstrated. Reference will be made to current analyses of whole-genome association study data.

Daily Schedule

Time	Daily Activity
8:00 am - 8:30 am	Coffee (and registration on the first day of each module)
8:30 am - 10:00 am	Class session
10:00 am - 10:30 am	Break
10:30 am - 12:00 noon	Class session
12:00 noon - 1:30 pm	Lunch
1:30 pm - 3:00 pm	Class session
3:00 pm - 3:30 pm	Break
3:30 pm - 5:00 pm	Class session

Organisers:

• Department of Statistics, University of Auckland
• Department of Biostatistics, University of Washington

Sponsors: