Low-template-DNA (Stochastic) Threshold--Its Determination Relative to Risk Analysis for National DNA Databases

• NCJ Number: 226995
• Journal: Forensic Science International: Genetics Volume: 3 Issue: 2 Dated: March 2009 Pages: 104-111
• Author(s): Peter Gill; Roberto Puch-Solis; James Curran
• Date Published: March 2009
• Length: 8 pages
• Publication Format: Article
• Publication Type: Report (Technical); Report (Study/Research)
• Language: English
• Country: Ireland

Annotation

Given that the low-template-DNA threshold T is widely used but has not been formally defined, this paper develops a definition of T, formalizes a method for determining T, provides a preliminary framework for conducting a risk analysis of misrecognition associated with database searches, and presents a definition of low-template (alternatively known as low-copy-number DNA) compared to conventional DNA relative to T.

Abstract

The perceived purpose of the low-template-DNA threshold T is to define the transition point between the conventional versus the low-template-DNA profile relative to the size of the present allele. This crude definition, however, does not accommodate the chance of a drop-out event relative to the increasing size of the present peak with a gradual decrease that is part of a continuum. This can be accommodated by providing a modified definition based on a determination of the proportion of events in which the present surviving allele exceeds threshold T. In a population of n heterozygotes, given a heterozygote (a,b), and drop-out of either a or b, then T is the peak height/area that will not be exceeded by the present allele with probability p. The acceptable risk (p) is determined by the end user and not by the scientist. The continuous nature of the heterozygote balance and allele drop-out is taken into account by making the definition of T probabilistic. In order to determine risk levels, the authors analyzed an experimental dataset that exhibited extreme drop-out using logistic regression. The derived probabilities are used in a graphical model in order to determine the relative risk of wrongful designations that may cause false inclusions and exclusions. The methods described in this paper provide a preliminary solution of risk evaluation for any DNA process that uses a stochastic threshold. 2 tables, 5 figures, and appended estimation of probability distributions for calculating extreme drop-out event probabilities and probability of a heterozygous genotype