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Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE

Motivation: Two methods are commonly used to report on evidence carried by forensic DNA profiles: the ‘Random Man Not Excluded’ (RMNE) approach and the likelihood ratio (LR) approach. It is often claimed a major advantage of the LR method that dropout can be assessed probabilistically. Results: In t...

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Detalles Bibliográficos
Autores principales: Van Nieuwerburgh, F., Goetghebeur, E., Vandewoestyne, M., Deforce, D.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639002/
https://www.ncbi.nlm.nih.gov/pubmed/19029128
http://dx.doi.org/10.1093/bioinformatics/btn608
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author Van Nieuwerburgh, F.
Goetghebeur, E.
Vandewoestyne, M.
Deforce, D.
author_facet Van Nieuwerburgh, F.
Goetghebeur, E.
Vandewoestyne, M.
Deforce, D.
author_sort Van Nieuwerburgh, F.
collection PubMed
description Motivation: Two methods are commonly used to report on evidence carried by forensic DNA profiles: the ‘Random Man Not Excluded’ (RMNE) approach and the likelihood ratio (LR) approach. It is often claimed a major advantage of the LR method that dropout can be assessed probabilistically. Results: In this article, a new RMNE measure is proposed that like-wise accounts for allelic dropout in an observed forensic DNA profile. We discuss the necessary calculations, underline their simplicity and provide a tool for performing the calculations. Availability: An Excel file with preprogrammed calculations of RMNE probabilities for DNA profiles up to 16 loci and with a maximum of two dropouts is available at: http://www.labfbt.UGent.be/RMNE.php Contact: dieter.deforce@ugent.be
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spelling pubmed-26390022009-02-25 Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE Van Nieuwerburgh, F. Goetghebeur, E. Vandewoestyne, M. Deforce, D. Bioinformatics Original Papers Motivation: Two methods are commonly used to report on evidence carried by forensic DNA profiles: the ‘Random Man Not Excluded’ (RMNE) approach and the likelihood ratio (LR) approach. It is often claimed a major advantage of the LR method that dropout can be assessed probabilistically. Results: In this article, a new RMNE measure is proposed that like-wise accounts for allelic dropout in an observed forensic DNA profile. We discuss the necessary calculations, underline their simplicity and provide a tool for performing the calculations. Availability: An Excel file with preprogrammed calculations of RMNE probabilities for DNA profiles up to 16 loci and with a maximum of two dropouts is available at: http://www.labfbt.UGent.be/RMNE.php Contact: dieter.deforce@ugent.be Oxford University Press 2009-01-15 2008-11-23 /pmc/articles/PMC2639002/ /pubmed/19029128 http://dx.doi.org/10.1093/bioinformatics/btn608 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Van Nieuwerburgh, F.
Goetghebeur, E.
Vandewoestyne, M.
Deforce, D.
Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE
title Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE
title_full Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE
title_fullStr Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE
title_full_unstemmed Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE
title_short Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE
title_sort impact of allelic dropout on evidential value of forensic dna profiles using rmne
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639002/
https://www.ncbi.nlm.nih.gov/pubmed/19029128
http://dx.doi.org/10.1093/bioinformatics/btn608
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