Prem S. Puri Memorial Lecture

Genetic Mapping in Experimental and Human Genetics

Professor David Siegmund
Stanford University

Start Date and Time: Fri, 13 May 2005, 4:30 PM

End Date and Time: Fri, 13 May 2005, 6:00 PM

Venue: MATH 175

Refreshments: 4:00-4:30 p.m. in the Math Library Lounge

Abstract:

The goal of genetic mapping is to locate genes affecting particular traits (e.g., genes that affect human suspectibility to particular diseases or genes that affect productivity of agriculturally important species) by comparing the phenotypes and genotypes of related individuals. Changes in experimental technique that provide large numbers of informative genetic markers at known locations throughout a genome have led to genome scans to identify anonymous genes. These in turn raise new statistical questions of experimental design and analysis. In this talk I will describe statistical models for genetic mapping, starting from the standard components of variance model and a parameterization of the genetic effects that makes “linkage parameters” orthogonal to “segregation parameters” and uses the framework of local alternatives employed in large sample statistical theory, in order to obtain explicit expressions for robust score statistics and for asymptotic noncentrality parameters. This will allow us to answer a number of questions of recent interest, especially (i) problems of multiple comparisons arising from the simultaneous testing of many markers for linkage to the trait of interest; and (ii) methods to map multiple genes taking account of possible gene-gene and gene-environment interactions.

References

Tang and Siegmund (2001) Biostatistics 2, 147-162.

Tang and Siegmund (2002) Genetic Epidemiology, 22 313-327.

Peng and Siegmund (2004) PNAS 101, 7845-7850.