Joint DNA-based disaster victim identification

Abstract We address computational and statistical aspects of DNA-based identification of victims in the aftermath of disasters. Current methods and software for such identification typically consider each victim individually, leading to suboptimal power of identification and potential inconsistencie...

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Autores principales:	Magnus D. Vigeland, Thore Egeland
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0978c8fabeec49e6aeb2c59b533aabaf
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spelling	oai:doaj.org-article:0978c8fabeec49e6aeb2c59b533aabaf2021-12-02T18:18:44ZJoint DNA-based disaster victim identification10.1038/s41598-021-93071-52045-2322https://doaj.org/article/0978c8fabeec49e6aeb2c59b533aabaf2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93071-5https://doaj.org/toc/2045-2322Abstract We address computational and statistical aspects of DNA-based identification of victims in the aftermath of disasters. Current methods and software for such identification typically consider each victim individually, leading to suboptimal power of identification and potential inconsistencies in the statistical summary of the evidence. We resolve these problems by performing joint identification of all victims, using the complete genetic data set. Individual identification probabilities, conditional on all available information, are derived from the joint solution in the form of posterior pairing probabilities. A closed formula is obtained for the a priori number of possible joint solutions to a given DVI problem. This number increases quickly with the number of victims and missing persons, posing computational challenges for brute force approaches. We address this complexity with a preparatory sequential step aiming to reduce the search space. The examples show that realistic cases are handled efficiently. User-friendly implementations of all methods are provided in the R package dvir, freely available on all platforms.Magnus D. VigelandThore EgelandNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Magnus D. Vigeland Thore Egeland Joint DNA-based disaster victim identification
description	Abstract We address computational and statistical aspects of DNA-based identification of victims in the aftermath of disasters. Current methods and software for such identification typically consider each victim individually, leading to suboptimal power of identification and potential inconsistencies in the statistical summary of the evidence. We resolve these problems by performing joint identification of all victims, using the complete genetic data set. Individual identification probabilities, conditional on all available information, are derived from the joint solution in the form of posterior pairing probabilities. A closed formula is obtained for the a priori number of possible joint solutions to a given DVI problem. This number increases quickly with the number of victims and missing persons, posing computational challenges for brute force approaches. We address this complexity with a preparatory sequential step aiming to reduce the search space. The examples show that realistic cases are handled efficiently. User-friendly implementations of all methods are provided in the R package dvir, freely available on all platforms.
format	article
author	Magnus D. Vigeland Thore Egeland
author_facet	Magnus D. Vigeland Thore Egeland
author_sort	Magnus D. Vigeland
title	Joint DNA-based disaster victim identification
title_short	Joint DNA-based disaster victim identification
title_full	Joint DNA-based disaster victim identification
title_fullStr	Joint DNA-based disaster victim identification
title_full_unstemmed	Joint DNA-based disaster victim identification
title_sort	joint dna-based disaster victim identification
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/0978c8fabeec49e6aeb2c59b533aabaf
work_keys_str_mv	AT magnusdvigeland jointdnabaseddisastervictimidentification AT thoreegeland jointdnabaseddisastervictimidentification
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Joint DNA-based disaster victim identification

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