Strategies for pairwise searches in forensic kinship analysis

Hilde Kjelgaard Brustad,Margherita Colucci,Mark A Jobling,Nuala A Sheehan,Thore Egeland

doi:10.1016/j.fsigen.2021.102562

Abstract

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.

Highlights

Inferring the relationship between pairs of individuals is central to many forensic applications
The second example demonstrates how to evaluate the performance of a blind search such as we present in the third example
We show by simulation a case where the likelihood ratio (LR) of a blind search are correlated

Summary

Introduction

Inferring the relationship between pairs of individuals is central to many forensic applications. Other applications are natural disasters like tsunamis, where the number of victims is unknown [4] and terrorism-related events [5]. The aim is to link DNA samples from the scene to putative victims (e.g. individuals reported missing since the event) and is known as disaster victim identification (DVI). There are various other important applications like searching for relationships among individuals in mass graves of archaeological relevance [6,7,8]. We may check databases collected to estimate population statistics such as allele frequencies. Duplicates and close relatives should be excluded prior to the statistical analysis to avoid biased estimates of allele frequencies [9]

Methods

Results

Conclusion