Modelling the Dependence Structure of Y-STR Haplotypes Using Graphical Models

• NCJ Number: 254147
• Journal: Forensic Science International-Genetics Volume: 37 Dated: November 2018 Pages: 29-36
• Author(s): Mikkel M. Andersen; James Curran; Jacob de Zoete; Duncan Taylor; John Buckleton
• Date Published: November 2018
• Length: 8 pages
• Grant Number(s): 2011-DN-BX-K541
• Agencies: NIJ-Sponsored
• Sponsoring Agency: National Institute of Justice (NIJ)
• Publication Format: Article
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description
• Language: English
• Country: United States of America

Annotation

This article reports on a reconsideration of the problem of population frequency estimation by application of Bayesian networks and the Chow-Liu algorithm to model dependencies between loci.

Abstract

Many methods have been suggested for evaluating the evidential value of a matching Y-chromosomal DNA profile obtained from a biological stain associated with a crime scene and the Y-chromosomal DNA profile of a suspect. Most of these methods are based on estimating the population frequency of the Y-profile. The common independence assumption between loci for autosomal DNA profiles cannot be used for Y-chromosomal DNA profiles. The study found that the method based on the Chow-Liu algorithm performs almost as well as the discrete Laplace method. The study also made comparisons to the independence model, demonstrating once again that the independence method for Y-profiles cannot be supported. (publisher abstract modified)