New stutter ratio distribution for DNA mixture interpretation based on a continuous model. (March 2016)

• Record Type: Journal Article
• Authors: Manabe, Sho; Hamano, Yuya; Morimoto, Chie; Kawai, Chihiro; Fujimoto, Shuntaro; Tamaki, Keiji
• Is Part Of: Legal medicine. Volume 19(2016)
• Page Start: 16
• Page End: 21
• Publication Date: 2016-03
• Subjects: AIC Akaike information criterion -- LUS longest uninterrupted stretch -- MLE maximum likelihood estimation -- RFU relative fluorescence unit -- SR stutter ratio -- STR short tandem repeat; Forensic DNA typing -- Mixture interpretation -- Low-template DNA -- Continuous model -- Stutter ratio; Medical jurisprudence -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Medical jurisprudence; Periodicals; 614.1
• DOI: 10.1016/j.legalmed.2016.01.007
• Languages: English
• ISSNs: 1344-6223

Abstract

Highlights: We developed new models of SR distribution for loci with complex repeat structures. Using these SR models only requires us to type allele repeat numbers. The SR models can be applied to mixture interpretation based on a continuous model. Abstract: In forensic science, DNA mixture interpretation is traditionally based on a binary model, which does not account for peak-height information in DNA profiles. In recent years, some countries have adopted a continuous model in which peak heights are used and stochastic effects are considered to enable rigorous calculation of likelihood ratios. However, this model requires certain biological parameters which affect the expected allelic and stutter peak heights. In this paper, we focused on estimating the distribution of the stutter ratio ( SR ) in 15 short tandem repeat loci in relation to the allele repeat number. We estimated the SR values of 234 single-source DNA samples by using a commercially available kit. In all loci except for D8S1179, D21S11, and D2S1338, a simple log-normal distribution model was fitted to the variability of SR . For D21S11, we developed a new distribution model in which distinct log-normal distributions between complete and incomplete repeat units are used (a separate log-normal distribution model). For D8S1179 and D2S1338, we developed another new distribution model that mixes two log-normal distributions to explain two types of repeat structures appearing within the same number of allele repeats. These two models were fitted to the observed SR values more accurately than the simple log-normal distribution model. We expected these new SR models to be applied to DNA mixture interpretation based on a continuous model.