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RFU derived LRs for activity level assignments using Bayesian Networks
Peter Gill1, Øyvind Bleka2, Ane Elida Fonneløp2
1Forensic Genetics Research Group, Oslo University Hospital, Oslo, Norway; Department of Clinical Medicine, University of Oslo, Oslo, Norway.
Abstract:
A comparative study has been carried out, comparing two different methods to estimate activity level likelihood ratios (LRa) using Bayesian Networks. The first method uses the sub-source likelihood ratio (log10LRϕ) as a 'quality indicator'. However, this has been criticised as introducing potential bias from population differences in allelic proportions. An alternative method has been introduced that is based upon the total RFU of a DNA profile that is adjusted using the mixture proportion (Mx) which is calculated from quantitative probabilistic genotyping software (EuroForMix). Bayesian logistic regressions of direct transfer data showed that the two methods were comparable. Differences were attributed to sampling error, and small sample sizes of secondary transfer data. The Bayesian approach facilitates comparative studies by taking account of sampling error; it can easily be extended to compare different methods.
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