Navigating population-level coancestry in forensic mixture analysis

The genetic similarity of unrelated individuals of the same population can be measured through the coancestry coefficient, which quantifies the probability of a pair of alleles randomly chosen having a common ancestor. It is thus expected that the higher this coefficient, the lower the genetic variation between individuals of a population. This may weaken the evidence's weight in forensic genetics settings, whenever a person of interest cannot be excluded as a contributor to the evidence. Under simple assumptions, the impact of disregarding coancestry when quantifying the likelihood of an individual having contributed to a mixture evidence sample can be evaluated through an algebraic approach. This methodology becomes, however, unfeasible when considering all the information currently obtained from samples in forensic cases, whose analyses are software-dependent. Innovatively, this work assessed the impact of disregarding coancestry when quantifying the weight of the evidence in a modern population under the scope of identification problems involving mixtures. Methodology relied on both an algebraic approach (for simulated data) and an informatics one (for more complex real casework data). The results reinforce the importance of considering the proper population coancestry, whose impact is expected to be even higher for more isolated, substructured, or smaller populations.