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.
Dawid
A P
AP
Department of Statistical Science, University College London, London, UK. dawid@stats.ucl.ac.uk
Mortera
J
J
Vicard
P
P
D001499:Bayes Theorem; D016172:DNA Fingerprinting; D053803:Forensic Genetics; D005819:Genetic Markers; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D009154:Mutation; D010334:Paternity; D010375:Pedigree
D005819:Genetic Markers