In discussing the estimation of population structure parameter, this report indicates that a DNA match probability is the probability that an untyped person has a DNA profile, given that a typed person has the profile. This depends on the genetic structure of the population to which these two people belong. The problems with structured populations arises when the people of interest belong, or are assumed to belong, to the same subpopulation, but data are available from only the whole population. The number and nature of subpopulations is generally unknown. The discussion of the estimation of population structure parameter is followed by a section on Y-STR match probabilities, since there is growing interest in the use of Y-STR profiles for forensic purposes. How relevant issues have been addressed in this project are described. This is followed by a description of a continuous model for mixtures. This discussion notes that over the past 3 years, the researchers in the current project have made contributions to the literature on providing numerical characterization of the evidentiary strength of DNA evidence. This work assumes the applicability of likelihood ratios, and it has been designed to avoid problems with the "binary model," in which decision rules on allelic presence in a profile are based on detection or analysis thresholds. This work is described in three stages. The concluding section of this report describes outreach activities from this project. It is noted that the work on population structure and Y-STR matching had a significant role in the "SWGDAM Interpretation Guidelines for Y-Chromosome STR Typing by Forensic DNA Laboratories." 4 figures, 1 table, and 25 references
Population Genetic Issues for Forensic DNA Profiles, Final Report
NCJ Number
251644
Date Published
May 2015
Length
21 pages
Annotation
Findings and methodology are reported for a research project with the objectives of developing and applying new population genetic theory to assist in the interpretation of DNA profiles, with a focus on population structure, lineage markers, and mixtures.
Abstract
Date Published: May 1, 2015