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Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors

Most DNA evidence is a mixture of two or more people. Cybergenetics TrueAllele(®) system uses Bayesian computing to separate genotypes from mixture data and compare genotypes to calculate likelihood ratio (LR) match statistics. This validation study examined the reliability of TrueAllele computing o...

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Detalles Bibliográficos
Autores principales: Bauer, David W., Butt, Nasir, Hornyak, Jennifer M., Perlin, Mark W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065088/
https://www.ncbi.nlm.nih.gov/pubmed/31580496
http://dx.doi.org/10.1111/1556-4029.14204
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author Bauer, David W.
Butt, Nasir
Hornyak, Jennifer M.
Perlin, Mark W.
author_facet Bauer, David W.
Butt, Nasir
Hornyak, Jennifer M.
Perlin, Mark W.
author_sort Bauer, David W.
collection PubMed
description Most DNA evidence is a mixture of two or more people. Cybergenetics TrueAllele(®) system uses Bayesian computing to separate genotypes from mixture data and compare genotypes to calculate likelihood ratio (LR) match statistics. This validation study examined the reliability of TrueAllele computing on laboratory‐generated DNA mixtures containing up to ten unknown contributors. Using log(LR) match information, the study measured sensitivity, specificity, and reproducibility. These reliability metrics were assessed under different conditions, including varying the number of assumed contributors, statistical sampling duration, and setting known genotypes. The main determiner of match information and variability was how much DNA a person contributed to a mixture. Observed contributor number based on data peaks gave better results than the number known from experimental design. The study found that TrueAllele is a reliable method for analyzing DNA mixtures containing up to ten unknown contributors.
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spelling pubmed-70650882020-03-16 Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors Bauer, David W. Butt, Nasir Hornyak, Jennifer M. Perlin, Mark W. J Forensic Sci Criminalistics Most DNA evidence is a mixture of two or more people. Cybergenetics TrueAllele(®) system uses Bayesian computing to separate genotypes from mixture data and compare genotypes to calculate likelihood ratio (LR) match statistics. This validation study examined the reliability of TrueAllele computing on laboratory‐generated DNA mixtures containing up to ten unknown contributors. Using log(LR) match information, the study measured sensitivity, specificity, and reproducibility. These reliability metrics were assessed under different conditions, including varying the number of assumed contributors, statistical sampling duration, and setting known genotypes. The main determiner of match information and variability was how much DNA a person contributed to a mixture. Observed contributor number based on data peaks gave better results than the number known from experimental design. The study found that TrueAllele is a reliable method for analyzing DNA mixtures containing up to ten unknown contributors. John Wiley and Sons Inc. 2019-10-03 2020-03 /pmc/articles/PMC7065088/ /pubmed/31580496 http://dx.doi.org/10.1111/1556-4029.14204 Text en © 2019 The Authors. Journal of Forensic Sciences published by Wiley Periodicals, Inc. on behalf of American Academy of Forensic Sciences. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Criminalistics
Bauer, David W.
Butt, Nasir
Hornyak, Jennifer M.
Perlin, Mark W.
Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors
title Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors
title_full Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors
title_fullStr Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors
title_full_unstemmed Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors
title_short Validating TrueAllele(®) Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors
title_sort validating trueallele(®) interpretation of dna mixtures containing up to ten unknown contributors
topic Criminalistics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7065088/
https://www.ncbi.nlm.nih.gov/pubmed/31580496
http://dx.doi.org/10.1111/1556-4029.14204
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