A solution for the rare type match problem when using the DIP-STR marker system
Détails
ID Serval
serval:BIB_DFEB9EEB24B7
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
A solution for the rare type match problem when using the DIP-STR marker system
Périodique
Forensic Science International: Genetics
ISSN
1872-4973
Statut éditorial
Publié
Date de publication
05/2018
Peer-reviewed
Oui
Volume
34
Pages
88-96
Résumé
The rare type match problem is an evaluative challenging situation in which the analysis of a DNA
profile reveals the presence of (at least) one allele which is not contained in the reference database. This situation is challenging because an estimate for the frequency of occurrence of the profile in a given population needs sophisticated evaluative procedures. The rare type match problem is very common when the DIP-STR marker system, which has proven itself very useful for dealing with unbalanced DNA mixtures, is used, essentially due to the limited size of the available database. The object-oriented Bayesian network proposed in Cereda et al. [7] to assess the value of the evidence for general scenarios, was not designed to deal with this particular situation. In this paper, the model is extended and partially modified to be able to calculate the full Bayesian likelihood ratio in presence of any (observed and not yet observed) allele of a given profile. The method is based on the approach developed in Cereda [5] for Y-STR data. Alternative solutions, such as the plug-in approximation and an empirical Bayesian methodology are also proposed and compared with the results obtained with the full Bayesian approach.
profile reveals the presence of (at least) one allele which is not contained in the reference database. This situation is challenging because an estimate for the frequency of occurrence of the profile in a given population needs sophisticated evaluative procedures. The rare type match problem is very common when the DIP-STR marker system, which has proven itself very useful for dealing with unbalanced DNA mixtures, is used, essentially due to the limited size of the available database. The object-oriented Bayesian network proposed in Cereda et al. [7] to assess the value of the evidence for general scenarios, was not designed to deal with this particular situation. In this paper, the model is extended and partially modified to be able to calculate the full Bayesian likelihood ratio in presence of any (observed and not yet observed) allele of a given profile. The method is based on the approach developed in Cereda [5] for Y-STR data. Alternative solutions, such as the plug-in approximation and an empirical Bayesian methodology are also proposed and compared with the results obtained with the full Bayesian approach.
Mots-clé
Object-oriented Bayesian networks, Deletion/Insertion Polymorphism, Likelihood ratio, Bayes Factor, Extremely unbalanced DNA mixtures
Pubmed
Web of science
Création de la notice
31/05/2018 14:19
Dernière modification de la notice
21/08/2019 5:12