Object-oriented Bayesian networks for complex forensic DNA profiling problems

We describe a flexible computational toolkit, based on object-oriented Bayesian networks, that can be used to model and solve a wide variety of complex problems of relationship testing using DNA profiles. In particular this can account for such complicating features as missing individuals, mutation and null alleles. We illustrate the use of this toolkit with several examples, including disputed paternity with missing or additional measurements, and criminal identification. We investigate the effects on likelihood ratios of introducing mutation and/or null alleles, and show that this can be substantial even when the underlying perturbations are small.     

Non-fatherhood or mutation? A probabilistic approach to parental exclusion in paternity testing.

The occurrence of germline mutations at microsatellite loci poses problems in ascertaining non-fatherhood status in paternity testing. We describe the appropriate probabilistic analysis for computing the likelihood ratio in favour of paternity while allowing for mutation, for all 18 relevant combinations of seemingly incompatible parental genotypes. We allow arbitrary and possibly different mutation rates in paternal and maternal germlines. We describe a stationary mutation model for expressing the required allele-specific transition mutation rates in terms of overall mutation rates, and compare the likelihood ratios calculated from this and from other mutation models suggested in the literature. We also show how to derive an upper bound on the likelihood ratio, depending only on the overall mutation rate.