Seymour Geisser Distinguished Lecture - January 31, 2007
University of Minnesota
School of Statistics
College of Liberal Arts

Interpreting DNA profile evidence in complex disputed paternity cases: Bayesian networks to the rescue

(Joint work with Julia Mortera and Paola Vicard, Universitá Roma Tre)

Philip Dawid
University College London

Wednesday, January 31, 2007
3:30 PM, 1-450G Moos Tower Minneapolis, East Bank Campus
Reception following at 4:30 PM, 300 Ford Hall

Abstract

Seymour Geisser made important contributions to statistical issues of disputed paternity analysis from genetic data, both as a theoretician and as an expert witness. Since that time technological advances, both genetic (DNA profiling) and computational (expert systems), have introduced new problems and solutions for these cases. In a simple case of disputed paternity we will have evidence in the form of DNA profiles from the child, mother and putative father: it is then relatively straightforward to determine the strength of the evidence bearing on paternity. But often the putative father is unavailable for testing, and instead we have to make do with DNA from one or more of his relatives. Other features, such as mutation, silent alleles, laboratory and handling errors, etc., introduce additional complications. The task of interpreting the forensic evidence in such cases can become extremely challenging, both logically and computationally. Recently it has been shown how the technology of Bayesian networks -- especially in its "object-oriented" version -- can be used to represent and solve such problems. I will describe the basics of this approach, present a collection of fundamental networks that can be flexibly combined (like a child's construction kit) to represent a very wide range of problems arising in forensic genetics, and illustrate their use in some real cases.