ProbRank: An efficient DNA database search method for complex mixtures per a quantitative likelihood ratio model.


Journal

Forensic science international. Genetics
ISSN: 1878-0326
Titre abrégé: Forensic Sci Int Genet
Pays: Netherlands
ID NLM: 101317016

Informations de publication

Date de publication:
07 2023
Historique:
received: 13 02 2023
revised: 04 04 2023
accepted: 27 04 2023
medline: 16 6 2023
pubmed: 8 5 2023
entrez: 7 5 2023
Statut: ppublish

Résumé

Searching a DNA Database with a DNA profile from an evidentiary trace can provide investigative leads in a forensic case. Various searching approaches exist such as conventional methods based on matching alleles or more advanced methods computing likelihood ratios (LR) while considering drop-in and drop-out. Here we examine the potential of using a quantitative LR model (EuroForMix model incorporated in ProbRank method) that takes peak heights into account in comparison to a qualitative LR model (LRmix model implemented in SmartRank method). Both methods present DNA database candidates in order of decreasing LR. Especially regarding minor contributors in complex mixtures, the method using the quantitative model outperforms the method using the qualitative model in terms of sensitivity and specificity as more true donors and less adventitious matches are retrieved. ProbRank is to be implemented in DNAStatistX and is sufficiently fast for daily use.

Identifiants

pubmed: 37150077
pii: S1872-4973(23)00059-5
doi: 10.1016/j.fsigen.2023.102884
pii:
doi:

Substances chimiques

Complex Mixtures 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

102884

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest We have no conflict of interest. We confirm that neither the manuscript nor any parts of its content are under consideration or published in another journal.

Auteurs

Jerry Hoogenboom (J)

Division of Biological Traces, Netherlands Forensic Institute, The Hague, the Netherlands. Electronic address: j.hoogenboom@nfi.nl.

Titia Sijen (T)

Division of Biological Traces, Netherlands Forensic Institute, The Hague, the Netherlands; Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.

Corina Benschop (C)

Division of Biological Traces, Netherlands Forensic Institute, The Hague, the Netherlands.

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Classifications MeSH