Optimal strategies for familial searching

Easykin: a flexible and user-friendly online tool for forensic kinship testing and missing person identification

In forensic kinship testing and missing person identification, it is a fundamental question to choose the most informative reference relatives, select appropriate genotyping systems, and evaluate the weight of evidence comprehensively. Despite that several useful tools have been developed, they have not addressed these questions satisfactorily. In this paper, we develop a flexible and user-friendly online tool, Easykin, to address the aforementioned issues. It has some promising features: (i) Pedigrees can be constructed easily and presented intuitively with just a few mouse clicks. (ii) System power can be estimated before testing based on certain set of markers and reference relatives. (iii) The pruning function of EasyKin enables users to choose appropriate subsets of available references. (iv) Parameters at a specific LR for a single case may ease evidence interpretation. (v) The user interface (UI) is an HTML-based dashboard, which is friendly to both professional and non-professional users and can be used anytime and anywhere. Here, we presented three common cases as examples to demonstrate how kinship testing and missing person identification can be improved with EasyKin. In conclusion, this tool provides a one-stop solution for forensic use, that is, instructing users to choose appropriate kits and reference relatives before testing, calculating LR in the testing, and providing parameters for data interpretation after testing. EasyKin is freely available at https://forensicsysu.shinyapps.io/EasyKin/ .

Incorporating non-genetic evidence in large scale missing person searches: A general approach beyond filtering

The search for missing persons implies several steps, from the preliminary investigation that involves collecting background data related to the case to the genetic kinship testing. Despite its crucial importance in identifications, only some approaches mathematically formalize the possibility of using preliminary investigation data. In some cases, a filtering strategy is applied, which implies selecting a subset of possible victims where some non-genetic variables perfectly match those of the missing. Through a Bayesian approach, we propose a mathematical model for computing the prior odds based on non-genetic variables usually collected during the preliminary investigation, such as biological sex, hair colour, and age. We use computational simulations to show how to incorporate these prior odds in DNA-database searches. Importantly, our results suggest that applying the proposed model leads to better search performance in underpowered cases from the genetic point of view, where few or distant relatives of the missing person are available for genotyping. Furthermore, the results are also helpful when using non-genetic data for prior odds in well-powered cases, where genetic data are enough to reach a reliable conclusion. It performs better than other approaches, such as using non-genetic data for filtering. The software mispitools, freely available on CRAN, implements all described methods (https://CRAN.R-project.org/package=mispitools).

Strategies for pairwise searches in forensic kinship analysis

Testing kinship between pairs of individuals is central to a wide range of applications. We focus on cases where many tests are done jointly. Typical examples include cases where DNA profiles are available from a burial site, a plane crash or a database of convicted offenders. The task is to determine the relationships between DNA profiles or individuals. Our approach generalises previous methods and implementations in several respects. We model general, possibly inbred, pairwise relationships which is important for non-human applications and in archaeological studies of ancient inbred populations. Furthermore, we do not restrict attention to autosomal markers. Some cases, such as distinguishing between maternal and paternal half siblings, can be solved using X-chromosomal markers. When many tests are done, the risk of errors increases. We address this problem by building on the theory of multiple testing and show how optimal thresholds for tests can be determined. We point out that the likelihood ratios in a blind search may be dependent so multiple testing methods and interpretation need to account for this. In addition, we show how a Bayesian approach can be helpful. Our examples, using simulated and real data, demonstrate the practical importance of the methods and implementation is based on freely available software.

Making decisions in missing person identification cases with low statistical power

The present work proposes a general strategy for dealing with missing person identification cases through DNA-database search. Our main example is the identification of abducted children in the last civic-dictatorship of Argentina, known as the "Missing Grandchildren of Argentina". Particularly we focus on those pedigrees where few, or only distant relatives of the missing person are available, resulting in low statistical power. For such complex cases we provide a statistical method for selecting a likelihood ratio (LR) threshold for each pedigree based on error rates. Furthermore, we provide an open-source user friendly software for computing LR thresholds and error rates. The strategy described in the paper could be applied to other large-scale cases of DNA-based identification hampered by low statistical power.

The effect of FBI CODIS Core STR Loci expansion on familial DNA database searching

1000 profiles chosen randomly from an in-house database of 6000 profiles were searched against the database for matches with at least one shared allele per locus. The database contains profiles that have been analyzed with Identifiler Plus (15 markers) for biological relationship and DNA identification purposes and both true and false matches are expected to be obtained. 100 pairs of at least one true paternity match and one false match were selected and were initially supplemented with 5 additional STRs representing the new Core CODIS set. Study of the LR value showed that when false matches were treated as paternity matches, the expansion of the marker set severely diminished the LR values obtained compared to true matches and the false positive ratio of familial database searching. When false matches were treated as full-sibling matches, the expansion to 20 STRs also diminished the number of false matches and the corresponding LR values compared to true full-sibling cases, but the effect was less dramatic. Addition of the SE33 marker, further promoted distinction between true and false matches both in paternity and full-sibling cases. Counting the number of shared alleles presented improved distinction efficiency between true and false matches after STR expansion to20 and 21 STRs but remains a less valuable method of familial DNA database searching compared to LR.