Statistical Evaluation of Forensic DNA Profile Evidence

Steele, Christopher D.; Balding, David J.

doi:10.1146/annurev-statistics-022513-115602

Cited by 70 publications

(46 citation statements)

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“…The theta (sometimes denoted F ST as recently in [16]) correction implies that the probability of observing a specific allele depends on what has been seen been before. In this sense, independence does not apply and the random mating assumption of Hardy-Weinberg is not required.…”

Section: Discussionmentioning

confidence: 99%

“…In continuous models for mixtures [16] hyperparameters describing, say, the fraction of DNA coming from various contributors are typically modelled in a Bayesian manner and likelihoods for different markers can no longer be multiplied but rather need to be integrated with respect to the prior to obtain the overall likelihood. Our simple illustration of the use of peak heights in section "Two unknown donors, no dropout, peak height information" avoids problems leading to dependence.…”

Section: Discussionmentioning

confidence: 99%

“…The book [3] provides a general introduction to forensic genetics whereas [16] reviews recent developments relevant for mixtures. In general terms, the problem is to determine whether there is evidence that certain individuals have contributed to a mixture or not.…”

Section: Introductionmentioning

confidence: 99%

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Exclusion probabilities and likelihood ratios with applications to mixtures

Slooten

Egeland

2015

Int J Legal Med

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The statistical evidence obtained from mixed DNA profiles can be summarised in several ways in forensic casework including the likelihood ratio (LR) and the Random Man Not Excluded (RMNE) probability. The literature has seen a discussion of the advantages and disadvantages of likelihood ratios and exclusion probabilities, and part of our aim is to bring some clarification to this debate. In a previous paper, we proved that there is a general mathematical relationship between these statistics: RMNE can be expressed as a certain average of the LR, implying that the expected value of the LR, when applied to an actual contributor to the mixture, is at least equal to the inverse of the RMNE. While the mentioned paper presented applications for kinship problems, the current paper demonstrates the relevance for mixture cases, and for this purpose, we prove some new general properties. We also demonstrate how to use the distribution of the likelihood ratio for donors of a mixture, to obtain estimates for exceedance probabilities of the LR for non-donors, of which the RMNE is a special case corresponding to L R>0. In order to derive these results, we need to view the likelihood ratio as a random variable. In this paper, we describe how such a randomization can be achieved. The RMNE is usually invoked only for mixtures without dropout. In mixtures, artefacts like dropout and drop-in are commonly encountered and we address this situation too, illustrating our results with a basic but widely implemented model, a so-called binary model. The precise definitions, modelling and interpretation of the required concepts of dropout and drop-in are not entirely obvious, and we attempt to clarify them here in a general likelihood framework for a binary model.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Exclusion probabilities and likelihood ratios with applications to mixtures

Slooten

Egeland

2015

Int J Legal Med

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“…genotyping using what has been termed 'semicontinuous' (where only allele information is used) or 'fully continuous' (where alleles and peak height information are used) [57][58][59][60][61][62][63].…”

Section: (C) Stronger Conclusion With Challenging Samplesmentioning

confidence: 99%

The future of forensic DNA analysis

Butler

2015

Phil. Trans. R. Soc. B

163

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One contribution of 15 to a discussion meeting issue 'The paradigm shift for UK forensic science'. The author's thoughts and opinions on where the field of forensic DNA testing is headed for the next decade are provided in the context of where the field has come over the past 30 years. Similar to the Olympic motto of 'faster, higher, stronger', forensic DNA protocols can be expected to become more rapid and sensitive and provide stronger investigative potential. New short tandem repeat (STR) loci have expanded the core set of genetic markers used for human identification in Europe and the USA. Rapid DNA testing is on the verge of enabling new applications. Next-generation sequencing has the potential to provide greater depth of coverage for information on STR alleles. Familial DNA searching has expanded capabilities of DNA databases in parts of the world where it is allowed. Challenges and opportunities that will impact the future of forensic DNA are explored including the need for education and training to improve interpretation of complex DNA profiles.

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“…There is a broad scientific consensus that likelihoods are the primary tool for DNA evidence evaluation and that forensic experts should present the strength of DNA evidence using the likelihood ratio [1]. There are good reasons to do so [2]: the likelihood ratio measures the strength of the evidence and the likelihood ratio approach allows a finder of fact to combine the evidence with background information or other evidence in a coherent way [3].…”

Section: Introductionmentioning

confidence: 99%