Analysis of Matches and Partial-Matches in a Danish STR Data Set

• NCJ Number: 239327
• Journal: Forensic Science International: Genetics Volume: 6 Issue: 3 Dated: May 2012 Pages: 387-392
• Author(s): Torben Tvedebrink; Poul Svante Eriksen; James Michael Curran; Helle Smidt Mogensen; Niels Morling
• Date Published: May 2012
• Length: 6 pages
• Grant Number(s): 2011-DN-BX-K541
• Agencies: NIJ-Sponsored
• Publication Type: Report (Study/Research)
• Award: Population Genetic Issues for Forensic DNA Profiles

Annotation

This study analyzed 53,295 STR profiles from individuals investigated in relation to crime case investigations at the Department of Forensic Medicine, Faculty of Health Sciences, University of Copenhagen, Denmark.

Abstract

Over the recent years, the national databases of STR profiles have grown in size due to the success of forensic DNA analysis in solving crimes. The accumulation of DNA profiles implies that the probability of a random match or near match of two randomly selected DNA profiles in the database increases. The authors analyzed 53,295 STR profiles from individuals investigated in relation to crime case investigations at the Department of Forensic Medicine, Faculty of Health Sciences, University of Copenhagen, Denmark. Incomplete STR profiles (437 circa 0.8 percent of the total), 48 redundant STR profiles from monozygotic twins (0.09 percent), 6 redundant STR profiles of unknown cause and 1283 STR profiles from repeated testing of individuals were removed leaving 51,517 complete 10 locus STR profiles for analysis. The number corresponds to approximately 1 percent of the Danish population. The authors compared all STR profiles to each other, i.e. 1.3 x 10(9) comparisons. With these large numbers of comparisons, it is likely to observe DNA profiles that coincide on many loci, which has concerned some commentators and raised questions about "overstating" the power of DNA evidence. The authors used the method of Weir [11,12] and Curran et al. [3] to compare the observed and expected number of matches and near matches in the dataset. The authors extended the methods by computing the covariance matrix of the summary statistic and used it for the estimation of the identical-by-descent parameter, 0. The analysis demonstrated a number of close relatives in the Danish dataset and substructure. The main contribution to the substructure comes from close relatives. An overall 0-value of 1 percent compensated for the observed substructure, when close familial relationships were accounted for. (Published Abstract)