Artículo
Bayesian networks for DNA-based kinship analysis: Functionality and validation of the GENis missing person identification module
Chernomoretz, Ariel
; Marsico, Franco Leonel
; Iserte, Javier Alonso
; Herrera Piñero, Mariana; Escobar, Maria Soledad; Balparda, Manuel
; Sibilla, Gustavo
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Fecha de publicación:
12/2022
Editorial:
Elsevier
Revista:
Forensic Science International: Genetics Supplement Series
ISSN:
1875-1768
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
GENis is a recently published open-source multi-tier information system developed to run forensic DNA databases. It relies on a Bayesian Networks framework and it is particularly well suited to efficiently perform large-size queries against databases of missing individuals. In this contribution we present a validation of the missing person identification capabilities of GENis. To that end we introduce fbnet, a free-software package written in the R statistical language that implements the complete GENis functionality to perform kinship analysis based on DNA profiles. With the aid of fbnet, we could validate likelihood ratios against estimations draw with Familias and forrel (two well-recognized R packages for kinship quantification) for complex pedigrees provided by the Argentinian reference databank (Banco Nacional de Datos Geneticos, BNDG). We found that our methodological approach presented an excellent performance in terms of accuracy and computation times.
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Articulos(IFIBA)
Articulos de INST.DE FISICA DE BUENOS AIRES
Articulos de INST.DE FISICA DE BUENOS AIRES
Citación
Chernomoretz, Ariel; Marsico, Franco Leonel; Iserte, Javier Alonso; Herrera Piñero, Mariana; Escobar, Maria Soledad; et al.; Bayesian networks for DNA-based kinship analysis: Functionality and validation of the GENis missing person identification module; Elsevier; Forensic Science International: Genetics Supplement Series; 8; 12-2022; 131-132
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