An Information Gap in DNA Evidence Interpretation

Perlin, Mark W.; Sinelnikov, A. A.

doi:10.2139/ssrn.1516366

Cited by 19 publications

(34 citation statements)

References 44 publications

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“…TrueAllele is widely used in criminal casework by Cybergenetics and crime laboratories. It has been tested on up to five unknown contributors (Perlin et al ., ), with five published validation studies (Perlin and Sinelnikov, ; Perlin et al ., , , ; Ballantyne et al ., ).…”

Section: Discussion On the Paper By Cowell Graversen Lauritzen And mentioning

confidence: 99%

Analysis of Forensic DNA Mixtures with Artefacts

Cowell

Graversen

Lauritzen

et al. 2014

Journal of the Royal Statistical Society Series C: Applied Statistics

112

153

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DNA is now routinely used in criminal investigations and court cases, although DNA samples taken at crime scenes are of varying quality and therefore present challenging problems for their interpretation. We present a statistical model for the quantitative peak information obtained from an electropherogram of a forensic DNA sample and illustrate its potential use for the analysis of criminal cases. In contrast with most previously used methods, we directly model the peak height information and incorporate important artefacts that are associated with the production of the electropherogram. Our model has a number of unknown parameters, and we show that these can be estimated by the method of maximum likelihood in the presence of multiple unknown individuals contributing to the sample, and their approximate standard errors calculated; the computations exploit a Bayesian network representation of the model. A case example from a UK trial, as reported in the literature, is used to illustrate the efficacy and use of the model, both in finding likelihood ratios to quantify the strength of evidence, and in the deconvolution of mixtures for finding likely profiles of the individuals contributing to the sample. Our model is readily extended to simultaneous analysis of more than one mixture as illustrated in a case example. We show that the combination of evidence from several samples may give an evidential strength which is close to that of a single-source trace and thus modelling of peak height information provides a potentially very efficient mixture analysis.

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Section: Discussion On the Paper By Cowell Graversen Lauritzen And mentioning

confidence: 99%

Analysis of Forensic DNA Mixtures with Artefacts

Cowell

Graversen

Lauritzen

et al. 2014

Journal of the Royal Statistical Society Series C: Applied Statistics

112

153

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show abstract

“…The International Society for Forensic Genetics (ISFG) DNA commission [1] recognized likelihood ratios (LRs) to be the preferred way to associate strength of evidence of DNA mixtures. Since then a number of different methods have been described [2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Euroforgen-NoE collaborative exercise on LRmix to demonstrate standardization of the interpretation of complex DNA profiles

Prieto¹,

Haned

Mosquera

et al. 2014

Forensic Science International: Genetics

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There has been very little work published on the variation of reporting practices of mixtures between laboratories, but it has been previously demonstrated that there is little consistency. This is because there is no current uniformity of practice, so different laboratories will operate using different rules. The interpretation of mixtures is not solely a matter of using some software to provide 'an answer'. An assessment of a case will usually begin with a consideration of the circumstances of a crime. Assumptions made about the numbers of contributors follow from an examination of the electropherogram(s)--and these may differ between the prosecution and the defence hypotheses. There may be a necessity to evaluate several sets of hypotheses for any given case if the circumstances are uncertain. Once the hypotheses are formulated, the mathematical analysis is complex and can only be accomplished by the use of specialist software. In order to obtain meaningful results, it is essential that scientists are trained, not only in the use of the software, but also in the methodology to understand the likelihood ratio concept that is used. The Euroforgen-NoE initiative has developed a training course that utilizes the LRmix program to carry out the calculations. This software encompasses the recommendations of the ISFG DNA commissions on mixture interpretation and is able to interpret samples that may come from two or more contributors and may also be partial profiles. Recently, eighteen different laboratories were trained in the methodology. Afterwards they were asked to independently analyze two different cases with partial mixture DNA evidence and to write a statement court-report. We show that by introducing a structured training programme, it is possible to demonstrate, for the first time, that a high degree of standardization, leading to uniformity of results can be achieved by participating laboratories.

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“…Having different explanations leads to genotype uncertainty. The uncertainty can arise from mixtures of two or more contributors to a DNA specimen [21] , damaged or small amounts of DNA [22] , or reconstructed genotypes from relatives [23] .…”

Section: Methodsmentioning

confidence: 99%

Efficient construction of match strength distributions for uncertain multi-locus genotypes

Perlin

2018

Heliyon

Self Cite

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Natural variation in biological evidence leads to uncertain genotypes. Forensic comparison of a probabilistic genotype with a person's reference gives a numerical strength of DNA association. The distribution of match strength for all possible references usefully represents a genotype's potential information. But testing more genetic loci exponentially increases the number of multi-locus possibilities, making direct computation infeasible.At each locus, Bayesian probability can quickly assemble a match strength random variable. Multi-locus match strength is the sum of these independent variables. A multi-locus genotype's match strength distribution is efficiently constructed by convolving together the separate locus distributions. This convolution construction can accurately collate all trillion trillion reference outcomes in a fraction of a second.This paper shows how to rapidly construct multi-locus match strength distributions by convolution. Function convergence demonstrates that distribution accuracy increases with numerical resolution. Convolution construction has quadratic computational complexity, relative to the exponential number of reference genotypes. A suitably defined random variable reduces high-dimensional computational cost to fast real-line arithmetic.Match strength distributions are used in forensic validation studies. They provide error rates for match results. The convolution construction applies to discrete or continuous variables in the forensic, natural and social sciences. Computer-derived match strength distributions elicit the information inherent in DNA evidence, often overlooked by human analysis.

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An Information Gap in DNA Evidence Interpretation

Cited by 19 publications

References 44 publications

Analysis of Forensic DNA Mixtures with Artefacts

Analysis of Forensic DNA Mixtures with Artefacts

Euroforgen-NoE collaborative exercise on LRmix to demonstrate standardization of the interpretation of complex DNA profiles

Efficient construction of match strength distributions for uncertain multi-locus genotypes

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