Interpretation of complex DNA profiles using empirical models and a method to measure their robustness

Abstract 

A new methodology is presented in order to report complex DNA profiles. We have brought together a number of different theories in order to devise a new protocol to interpret complex cases using likelihood ratios. The calculations are designed to be highly conservative and are widely applicable. We apply a low copy number (LCN) interpretation framework, which includes the probabilities of dropout and contamination, to ‘conventional’ DNA cases. In conventional casework, stutters often compromise calculations when they are observed with the same height as a minor contributor to a mixture. Stutters cannot be distinguished from minor alleles. We compensate by treating them as real alleles and including them in the calculation. By increasing the number of potential contributors to the DNA profile, we can account for the extra alleles that result. We propose that the likelihood ratio is qualified with additional robustness parameters to indicate the probability of misleading evidence in favour of the prosecution, under the assumption that a random man was a contributor instead of the suspect. To do this we apply a new kind of case-specific ‘Tippett’ test. Although the method is complex, we suggest a ‘user-friendly’ way to explain the results to a court. The method is easily extended to carry out ranked likelihood ratio (LR) searches for suspects in national DNA databases.

Keywords: Mixtures, Low copy number, Tippett test, Expert system, LoComatioN, Likelihood ratio