The aim of this workshop was to gather together a sufficiently expert group with interests ranging across diverse areas of genetic epidemiological application in order to focus on the computational and methodological issues that are common to family studies, genetic association studies and the analyses of complex traits. One objective was to assess existing methods of analysis of large and complex datasets, to consider appropriate adaptation of these methods and to investigate the potential for new methods which address common problematic features of all these datasets. Another was to actively encourage young researchers into this field by providing the opportunity to become acquainted with the main research issues in the area and to make vital contacts with the leading people and their groups in an informal small group setting.
Workshop
Statistical Methods for Genetic Epidemiology
07 - 11 May 2007
ICMS
Organiser
About
Programme
Meet the speakers
David Clayton
University of Cambridge
Genome-Wide Association Studies; Experiences of the WTCCC
Duncan Thomas
University of Southern California
Complex Biological Pathways
Francoise Clerget Darpoux
INSERM & Paris-Sud University
Multifactorial Diseases: A Gap Between Association Information and the Understanding of the Pathogenic Process
Laura Almasy
Southwest Foundation for Biomedical Research
Quantitative Risk Factors for Identifying Genes in Complex Diseases
Elizabeth A Thompson
University of Washington
Assessing the Significance of Linkage Signals
David Balding
Imperial College London
Population Structure and Genetic Associations
Peter Holmans
University of Wales College of Medicine
Use of Covariates in Model-Free Linkage and Association
Sarah Lewis
University of Bristol
Some Practical Examples Illustrating the Use of Mendelian Randomisation
Tim Bishop
Cancer Research UK
Challenges to Understanding Disease Aetiology with Family Studies
Wally Gilks
University of Leeds
DNA is not a Straight Line
Dawn Teare
University of Sheffield
Study of a Candidate Copy Number Polymorphism in Asthma Families
Juni Palmgren
Karolinska Institute
The GeneStat Web Portal
Vanessa Didelez
University College London
Causal Inference for Genetic Epidemiology Using Mendelian Randomisation
Alun Thomas
University of Utah
Towards Linkage Analysis with Markers in Linkage Disequilibrium by Graphical Modelling
John Whittaker
London School of Hygiene and Tropical Medicine
Baysian Meta-Analysis of Genetic Association Studies
Heather Cordell
Newcastle University
Testing and Estimation of Genotype and Haplotype Effects in Family-Based Analysis of Quantitative Traits with Missing Genotype Data
Simon Heath
National Genotyping Centre
Detection/Reconstruction of Family Relationships Using Genotype Data from Whole Genome Arrays
Elja Arjas
University of Helsinki
Estimating Genealogies from Marker Data: a Bayesian Approach
Cornelia Van Duijn
Erasmus University Medical Centre
Splitting Complex Pedigrees for Linkage Analysis
Thore Egeland
Ullevål University Hospital
Adjusting for Relatedness Among Founders in Linkage Analysis
Konstantin Strauch
Philipps University Marburg
A Close View of the Possible Triangle