A solution for the rare type match problem when using the DIP-STR marker system

TL;DR

This paper introduces an extended Bayesian network model to effectively evaluate DNA profiles with rare alleles in the DIP-STR marker system, addressing the challenge of limited databases and improving forensic analysis accuracy.

Contribution

It extends existing Bayesian models to handle rare alleles in DIP-STR DNA analysis, incorporating new methods for more accurate likelihood ratio calculations.

Findings

The extended model accurately assesses rare allele profiles.

Alternative methods like empirical Bayesian are compared with the full Bayesian approach.

The approach improves forensic DNA evidence evaluation in limited database scenarios.

Abstract

The rare type match problem is an evaluative challenging situation in which the analysis of a DNA profile reveals the presence of (at least) one allele which is not contained in the reference database. This situation is challenging because an estimate for the frequency of occurrence of the profile in a given population needs sophisticated evaluative procedures. The rare type match problem is very common when the DIP-STR marker system, which has proven itself very useful for dealing with unbalanced DNA mixtures, is used, essentially due to the limited size of the available database. The object-oriented Bayesian network proposed in Cereda, Biedermann, Hall and Taroni (2014) to assess the value of the evidence for general scenarios, was not designed to deal with this particular situation. In this paper, the model is extended and partially modified to be able to calculate the full Bayesian likelihood ratio in presence of any (observed and not yet observed) allele of a given profile. The method is based on the approach developed in Cereda (2017) for Y-STR data. Alternative solutions, such as the plug-in approximation and an empirical Bayesian methodology are also proposed and compared with the results obtained with the full Bayesian approach.