Abstract
We compare DNA mixture analysis via DNAˑVIEW® Mixture Solution™ and the current combined probability of inclusion (CPI) method of the South African Police Service (SAPS). South Africa has a high incidence of property-related crimes and sexual offences and consequently a great deal of low-template (LT-DNA) forensic DNA mixture casework and a perpetual backlog. A range of casework and laboratory-prepared sexual assault mixtures with initial male DNA amounts varying from about 2 to 200 cells were analysed to evaluate the benefits of a continuous model program. Unfortunately CPI methods are nearly useless for LT-DNA cases because of dropout—common from a mixture contribution of fewer than 20 or 30 cells. We further argue that proposed CPI elaborations to circumvent dropout lack supporting research or even explanation. Mixture Solution models mixture data as continuous rather than binary, with a mathematically coherent (“probabilistic”) model which incorporates dropout and other phenomena realistically. Much more information is thereby utilised resulting in applicability to more cases (7 or fewer contributor cells suffice), stronger evidence against a suspect who is a mixture contributor and stronger evidence to absolve a non-contributor. Mixture Solution incidentally provides information which, along with rfu data, allows estimating contributions in terms of number of cells, which is a useful perspective. The method of calculation is explained.
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Notes
Clearly detection threshold is related to analytical threshold (AT) since AT, defined as “the level above which signals can safely be assumed to be legitimate”, is an obvious choice for DT. But the terms are not synonymous. An analyst may choose and compute with various DT levels, whereas the definition of AT implies a fixed level imposed by nature.
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The Mixture Solution software is a creation of the paper’s last author. Otherwise, the authors declare no competing interests.
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Lucassen, A., Ehlers, K., Grobler, P.J. et al. Evaluating Mixture Solution™— rapid and non-MCMC probabilistic mixture analysis. Int J Legal Med 135, 2275–2284 (2021). https://doi.org/10.1007/s00414-021-02680-2
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DOI: https://doi.org/10.1007/s00414-021-02680-2