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A new implementation of a semi-continuous method for DNA mixture interpretation.
Alfieri, Jacob; Coble, Michael D; Conroy, Carole; Dahl, Angela; Hares, Douglas R; Weir, Bruce S; Wolock, Charles; Zhao, Edward; Kingston, Hanley; Zolandz, Timothy W.
Afiliação
  • Alfieri J; Department of Biostatistics, University of Washington, Seattle, WA 98194-7232, USA.
  • Coble MD; Center for Human Identification, Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX 76107, USA.
  • Conroy C; ECS, 2750 Prosperity Ave STE 600, Fairfax, VA 22031, USA.
  • Dahl A; Department of Biostatistics, University of Washington, Seattle, WA 98194-7232, USA.
  • Hares DR; CODIS Unit, FBI Laboratory, 2501 Investigation Parkway, Quantico, VA 22135, USA.
  • Weir BS; Department of Biostatistics, University of Washington, Seattle, WA 98194-7232, USA.
  • Wolock C; Department of Biostatistics, University of Washington, Seattle, WA 98194-7232, USA.
  • Zhao E; Department of Biostatistics, University of Washington, Seattle, WA 98194-7232, USA.
  • Kingston H; Department of Biostatistics, University of Washington, Seattle, WA 98194-7232, USA.
  • Zolandz TW; CODIS Unit, FBI Laboratory, 2501 Investigation Parkway, Quantico, VA 22135, USA.
Article em En | MEDLINE | ID: mdl-38077656
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article