Prioritising family members for genotyping in missing person cases: A general approach combining the statistical power of exclusion and inclusion

Vigeland, Magnus Dehli; Mársico, Franco; Piñero, Mariana Herrera; Egeland, Thore

doi:10.1016/j.fsigen.2020.102376

Cited by 22 publications

(20 citation statements)

References 27 publications

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“…1.000 V 3 0.996 0.004 V 4 1.000 V 5 1.000 V 6 1.000 V 7 1.000 V 8 1.000 Table 9. Posterior pairing probabilities in the plane crash example calculated using a flat prior and a proportional mutational model with rate 0.001.…”

Section: Discussionmentioning

confidence: 99%

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Joint DNA-based Disaster Victim Identification

Vigeland

Egeland

2021

Preprint

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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.

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Section: Discussionmentioning

confidence: 99%

“…6.75e-02 6.79e+04 6.66e-02 V 3 1.03e-04 3.82e-03 V 4 3.78e-05 3.19e+07 V 5 9.62e-04 3.92e-03 V 6 1.08e+06 1.29e-05 V 7 5.90e-04 1.90e-01 V 8 1.91e-04 2.72e-01 Table 6. Pairwise LRs for the plane crash example.…”

Section: A Comparison Of Methodsmentioning

confidence: 99%

Joint DNA-based Disaster Victim Identification

Vigeland

Egeland

2021

Preprint

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“…Familial searching and kinship analysis, section 'Investigation Using Autosomal STR Profiles', may be used when there is prior information (e.g. clothing, tattoos, passenger records, identification by relatives) suggesting a potential identity for the remains [47]. Forensic genealogy, section 'Forensic Genealogy', is also being used, e. g. the DNA Doe project [48] and The Centre for Human Identification [49] in the U.S.A.…”

Section: Body Identificationmentioning

confidence: 99%

Interpretation of DNA data within the context of UK forensic science — investigation

Pope¹,

Puch-Solis

2021

Emerging Topics in Life Sciences

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This article is the second part of a review of the interpretation of DNA data in forensic science. The first part describes the evaluation of autosomal profile for criminal trials where an evidential weight is assigned to the profile of a person of interest (POI) and a crime-scene profile. This part describes the state of the art and future advances in the interpretation of forensic DNA data for providing intelligence information during an investigation. Forensic DNA is crucial in the investigative phase of an undetected crime where a POI needs to be identified. A sample taken from a crime scene is profiled using a range of forensic DNA tests. This review covers investigation using autosomal profiles including searching national and international crime and reference DNA databases. Other investigative methodologies described are kinship analysis; familial searching; Y chromosome (Y-STR) and mitochondrial (mtDNA) profiles; appearance prediction and geographic ancestry; forensic genetic genealogy; and body identification. For completeness, the evaluation of Y-STRs, mtDNA and kinship analysis are briefly described. Taken together, parts I and II, cover the range of interpretation of DNA data in a forensic context.

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“…Ultimately, however, the same threshold is applied to every kinship DNA case, regardless of the available pedigree. When performing DNA kinship matching, the weight of the DNA evidence is obviously increased by adding as many close relatives as possible to the pedigree or by performing pair-wise searches [29][30][31]. The reality is that the best scenario to support the identification may not be feasible as it depends directly on which relatives were selected and were available to have their DNA collected at the time of the investigation, which can date back several decades.…”

Section: Introductionmentioning

confidence: 99%

Streamlining the decision-making process for international DNA kinship matching using Worldwide allele frequencies and tailored cutoff log10LR thresholds

Laurent¹,

Fischer²,

Oldt³

et al. 2022

Forensic Science International: Genetics

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The identification of human remains belonging to missing persons is one of the main challenges for forensic genetics. Although other means of identification can be applied to missing person investigations, DNA is often extremely valuable to further support or refute potential associations. When reference DNA samples cannot be collected from personal items belonging to a missing person, a direct DNA identification cannot be carried out. However, identifications can be made indirectly using DNA from the missing person's relatives. The ranking of likelihood ratio (LR) values, which measure the fit of a missing person for any given pedigree, is often the first step in selecting candidates in a DNA database. Although implementing DNA kinship matching in a national environment is feasible, many challenges need to be resolved before applying this method to an international configuration. In this study, we present an innovative and intuitive method to perform international DNA kinship matching and facilitate the comparison of DNA profiles when the ancestry is unknown or unsure and/or when different marker sets are used. This straightforward method, which is based on calculations performed with the DNA matching software BONAPARTE, Worldwide allele frequencies and tailored cutoff log 10 LR thresholds, allows for the classification of potential candidates according to the strength of the DNA evidence and the predicted proportion of adventitious matches. This is a powerful method for streamlining the decision-making process in missing person investigations and DVI processes, especially when there are low numbers of overlapping typed STRs. Intuitive interpretation tables and a decision tree will help strengthen international data comparison for the identification of reported missing individuals discovered outside their national borders.

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Prioritising family members for genotyping in missing person cases: A general approach combining the statistical power of exclusion and inclusion

Cited by 22 publications

References 27 publications

Joint DNA-based Disaster Victim Identification

Joint DNA-based Disaster Victim Identification

Interpretation of DNA data within the context of UK forensic science — investigation

Streamlining the decision-making process for international DNA kinship matching using Worldwide allele frequencies and tailored cutoff log10LR thresholds

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