An illustration of the effect of various sources of uncertainty on DNA likelihood ratio calculations

• NCJ Number: 307106
• Journal: Forensic Science International-Genetics Volume: 11 Dated: 2014 Pages: 56-63
• Author(s): D. Taylor; J-A. Bright; J. Buckleton; J. Curran
• Date Published: 2014
• Length: 8 pages
• Grant Number(s): 2011-DN-BX-K541
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical)
• Award: Population Genetic Issues for Forensic DNA Profiles

Annotation

This paper discusses the effects of various sources of uncertainty on a likelihood ratio calculation of forensic DNA evidence, and demonstrate how changes in the distribution of those parameters affect the reported value.

Abstract

A typical assessment of the strength of forensic DNA evidence is based on a population genetic model and estimated allele frequencies determined from a population database. Some experts provide a confidence or credible interval which takes into account the sampling variation inherent in deriving these estimates from only a sample of a total population. This interval is given in conjunction with the statistic of interest, be it a likelihood ratio (LR), match probability, or cumulative probability of inclusion. Bayesian methods of addressing database sampling variation produce a distribution for the statistic from which the bound(s) of the desired interval can be determined. Population database sampling uncertainty represents only one of the sources of uncertainty that affects estimation of the strength of DNA evidence. There are other uncertainties which can potentially have a much larger effect on the statistic such as, those inherent in the value of F_st, the weights given to genotype combinations in a continuous interpretation model, and the composition of the relevant population. In this paper, the authors model the effect of each of these sources of uncertainty on a likelihood ratio (LR) calculation and demonstrate how changes in the distribution of these parameters affect the reported value. In addition, the authors illustrate the impact the different approaches of accounting for sampling uncertainties has on the LR for a four person mixture. (Publisher Abstract Provided)