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Probabilistic approaches to interpreting two-person DNA mixtures from post-coital specimens.

Abstract

Biological samples submitted for sexual assault investigation typically involve mixtures of DNA from the victim and the assailant/s. Providing a statistical weight to such evidence may be mathematically complex and may be affected by subjective judgment of a human analyst. Software tools have been developed to address these issues. To contribute towards improving the system for routine DNA testing of sexual assault cases, we evaluated two likelihood ratio (LR) approaches: a semi-continuous model using LRmix Studio and a fully continuous approach employed in STRmix™ for interpreting two-person DNA mixtures. LRs conditioned on the presence of the receptive partner’s DNA were calculated for a total of 102 two-person DNA samples from simulated mixtures and various post-coital samples. Our results highlight the importance of maximising information provided into the LR calculation to generate strong support for the true hypothesis. This can be achieved by recovering sufficient DNA from a sample to minimise risk of drop-out and increase peak intensities and by implementing a statistical model that utilises as much of the electropherogram information as possible. LRmix is open-source and can handle profiles with allelic drop-out and drop-ins, however stuttering is not modelled and requires manual removal by a DNA analyst especially for mixtures with low template components. STRmix™ makes effective use of all available information by incorporating into its biological model complicating aspects of a DNA profile such as degradation, allele drop-out and drop-in, stutters, and peak height variability.

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