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A new implementation of a semi-continuous method for DNA mixture interpretation

Authors :
Jacob Alfieri
Michael D. Coble
Carole Conroy
Angela Dahl
Douglas R. Hares
Bruce S. Weir
Charles Wolock
Edward Zhao
Hanley Kingston
Timothy W. Zolandz
Source :
Forensic Science International: Reports, Vol 6, Iss , Pp 100281- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

A new calculation module within the PopStats module of the CODIS software package, based on the underlying mathematics presented in the MixKin software package, has been developed for assigning the Likelihood Ratio (LR) of DNA mixture profiles. This module uses a semi-continuous model that allows for population structure and allelic drop-out and drop-in but does not require allelic peak heights or other laboratory-specific parameters. This new implementation (named SC Mixture), like MixKin, does not specify or estimate a probability of drop-out. Instead, each contributor to a mixture has an independent drop-out rate, and the probability of the mixture profile for a specified proposition concerning the contributors is integrated over the range of possible drop-out rates. The allelic drop-in rate and the population structure parameter, theta, used by the software are specified by the user. The user can examine up to five contributors to a mixture, however, conditioning on assumed contributors and limiting the number of unknowns in both numerator and denominator hypotheses greatly improves performance. We report results from an extensive validation study performed for ten mixtures with each of one (single source), two, three, four, or five contributors, with four combinations of drop-in rate and a population structure parameter. Each mixture was run as a complete profile or with the random removal of alleles to simulate drop-out. All 1620 combinations were evaluated with PopStats, MixKin, and LRmix and considerable consistency was found among the results with all three packages.

Details

Language :
English
ISSN :
26659107
Volume :
6
Issue :
100281-
Database :
Directory of Open Access Journals
Journal :
Forensic Science International: Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.552435f3867545fba1c29227c54cd1a5
Document Type :
article
Full Text :
https://doi.org/10.1016/j.fsir.2022.100281