Interpreting DNA Evidence: A Review

Foreman, Lindsey A.; Champod, Christophe; Evett, I.W.; Lambert, J.A.; Pope, Sue

doi:10.1111/j.1751-5823.2003.tb00207.x

Cited by 35 publications

(20 citation statements)

References 90 publications

(73 reference statements)

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“…Most of them focus on cases where only a few people contribute to the mixture. These methods usually compare short tandem repeats (STR) in the mixture to those in the individual (Fung and Hu, 2002;Balding, 2003;Foreman et al, 2003). When only interested in males, the comparison can be limited to STRs on the Y chromosome (Jobling and Gill, 2004).…”

Section: Introductionmentioning

confidence: 99%

Identifying Individuals in a Complex Mixture of DNA with Unknown Ancestry

Sampson

Zhao²

2009

Statistical Applications in Genetics and Molecular Biology

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A new test was recently developed that could use a high-density set of single nucleotide polymorphisms (SNPs) to determine whether a specific individual contributed to a mixture of DNA. The test statistic compared the genotype for the individual to the allele frequencies in the mixture and to the allele frequencies in a reference group. This test requires the ancestries of the reference group to be nearly identical to those of the contributors to the mixture. Here, we first quantify the bias, the increase in type I and type II error, when the ancestries are not well matched. Then, we show that the test can also be biased if the number of subjects in the two groups differ or if the platforms used to measure SNP intensities differ. We then introduce a new test statistic and a test that only requires the ancestries of the reference group to be similar to the individual of interest, and show that this test is not only robust to the number of subjects and platform, but also has increased power of detection. The two tests are compared on both HapMap and simulated data.

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Section: Introductionmentioning

confidence: 99%

Identifying Individuals in a Complex Mixture of DNA with Unknown Ancestry

Sampson

Zhao²

2009

Statistical Applications in Genetics and Molecular Biology

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“…As Koehler and Saks (1991, p 371) note: "Where presumptions exist, they should be provided by the law, not by expert witnesses." Using only the likelihood ratio from the forensic anthropological evidence should protect the expert from this error, but unfortunately it is all too easy for the likelihood ratio to be misinterpreted by "transposing" the conditioning (Thompson and Schumann, 1987;Evett, 1995;National Research Council Committee on DNA Technology in Forensic Science, 1996;Foreman et al, 2003). Evett (1995, p 129) gives a clear illustration of a transposed conditional probability:…”

Section: More On Priors and The Problem Of Transposed Conditionals Inmentioning

confidence: 99%

Bayes in biological anthropology

Konigsberg

Frankenberg

2013

American J Phys Anthropol

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In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available. Am J Phys Anthropol 57: 2013. V C 2013 Wiley Periodicals, Inc."The Bayesian approach can have a clarifying effect on one's thinking about evidence." (Koehler and Saks, 1991, p 364) Traditional training in statistical methods for those who go on to become practicing biological anthropologists has focused primarily on classical hypothesis testing. This is apparent in both textbooks geared toward anthropologists in general (Thomas, 1986;Madrigal, 1998;Bernard, 2011) and specialized texts for biological anthropologists (Slice, 2005;D'Aoãut and Vereecke, 2011). While Bayes' Theorem may be mentioned in passing in introductory statistics courses, this is typically restricted to examples of such limited interest that the student has little motivation to recall the theorem, and even less motivation to assume that there may be future value in having learned about Bayes' Theorem. In Bayesian terms, the prior probability that the student will retain Bayes' Theorem is quite low. In contrast, the student and eventual practitioner is likely to learn about confidence intervals, Type I and Type II errors in hypothesis testing, and P-values, and to blithely assume that what they have learned represents the near totality of what is available and useful within modern statistical practice. This represents an unfortunate omission of Ba...

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“…Descriptions of the likelihood-ratio framework can be found in numerous textbooks and articles including Aitken and Taroni [5], Balding [8], Buckleton [9], Evett [10], Lucy [11], Robertson and Vignaux [12], and with specific reference to forensic voice comparison Champod and Meuwly [13], González-Rodríguez et al [14], González-Rodríguez et al [15], and Rose [16,17]. For a history of developments in forensic statistics prior to the advent of forensic DNA analysis (including use of the likelihood-ratio framework) see Evett [6], and for a history of statistical procedures applied to the evaluation of DNA evidence and the ultimate adoption of the likelihood-ratio framework in that field see Foreman et al [18].…”

Section: The Likelihood-ratio Frameworkmentioning

confidence: 99%

“…151-153), this is simply the denominator of the likelihood ratio, or equivalently the inverse of the likelihood ratio given in Eq. (1), i.e., it is the probability of obtaining the matching DNA profile in question under the different-origin versus the same-origin hypothesis [8] (p. 24), [18] (p. 484).…”

Section: Differences Between Dna and Voice Datamentioning

confidence: 99%

“…(p. 142). The framework is a two-stage one, sequentially assessing similarity and typicality, reminiscent of frameworks which had been in use in other forensic comparison sciences, including DNA, before being supplanted by the likelihood-ratio framework [18,39]. Reliability is not mentioned in the UK position statement, and I have not seen any publications which test the reliability of forensic voice comparison conducted using the UK framework.…”

Section: Resistance To the Paradigm Shiftmentioning

confidence: 99%

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Forensic voice comparison and the paradigm shift

Morrison¹

2009

Science & Justice

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We are in the midst of a paradigm shift in the forensic comparison sciences. The new paradigm can be characterised as quantitative data-based implementation of the likelihood-ratio framework with quantitative evaluation of the reliability of results. The new paradigm was widely adopted for DNA profile comparison in the 1990s, and is gradually spreading to other branches of forensic science, including forensic voice comparison. The present paper first describes the new paradigm, then describes the history of its adoption for forensic voice comparison over approximately the last decade. The paradigm shift is incomplete and those working in the new paradigm still represent a minority within the forensic-voice-comparison community.

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Interpreting DNA Evidence: A Review

Cited by 35 publications

References 90 publications

Identifying Individuals in a Complex Mixture of DNA with Unknown Ancestry

Identifying Individuals in a Complex Mixture of DNA with Unknown Ancestry

Bayes in biological anthropology

Forensic voice comparison and the paradigm shift

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