Providing scientific guidance on DNA to the judiciary.

A series of short documents have been written in response to a request from the UK Judiciary for explanations of research that was commissioned in response to questions they had raised. These related principally to the potential impact of primer binding site mutation (PBSM) but it became clear at an early stage that it was necessary to explain related issues. The three scientific guidance papers (SGPs) that have been prepared thus far are presented in their entirety so that UK scientists may be aware of what has been presented to judges. Suggestions for further work, including possible communication to jurors are discussed.

Is it to the advantage of a defendant to infer a greater number of contributors to a questioned sample than is necessary to explain the observed DNA profile?

When a forensic scientist presents the results of a comparison between a DNA profile from a questioned sample with that of a defendant the interpretation will be based on the premise of a given number of contributors. It is quite common practice for defence counsel to ask how consideration of a greater number of putative contributors to the profile would affect the interpretation. This note discusses the response to such a request.

Helping formulate propositions in forensic DNA analysis.

The Bayesian paradigm is the preferred approach to evidence interpretation. It requires the evaluation of the probability of the evidence under at least two propositions. The value of the findings (i.e., our LR) will depend on these propositions and the case information, so it is crucial to identify which propositions are useful for the case at hand. Previously, a number of principles have been advanced and largely accepted for the evaluation of evidence. In the evaluation of traces involving DNA mixtures there may be more than two propositions possible. We apply these principles to some exemplar situations. We also show that in some cases, when there are no clear propositions or no defendant, a forensic scientist may be able to generate explanations to account for observations. In that case, the scientist plays a role of investigator, rather than evaluator. We believe that it is helpful for the scientist to distinguish those two roles.

A Logical Framework for Forensic DNA Interpretation.

The forensic community has devoted much effort over the last decades to the development of a logical framework for forensic interpretation, which is essential for the safe administration of justice. We review the research and guidelines that have been published and provide examples of how to implement them in casework. After a discussion on uncertainty in the criminal trial and the roles that the DNA scientist may take, we present the principles of interpretation for evaluative reporting. We show how their application helps to avoid a common fallacy and present strategies that DNA scientists can apply so that they do not transpose the conditional. We then discuss the hierarchy of propositions and explain why it is considered a fundamental concept for the evaluation of biological results and the differences between assessing results given propositions that are at the source level or the activity level. We show the importance of pre-assessment, especially when the questions relate to the alleged activities, and when transfer and persistence need to be considered by the scientists to guide the court. We conclude with a discussion on statement writing and testimony. This provides guidance on how DNA scientists can report in a balanced, transparent, and logical way.

Interpretation and reporting of mixed DNA profiles by seven forensic laboratories in the UK and Ireland.

In 2014, the UK Forensic Science Regulator (FSR) commissioned a collaborative trial to assess the methods used by forensic service providers (FSPs) in the UK and Ireland for analysis, interpretation and reporting of mixed DNA profiles. Five different mixed samples of varying complexity with supporting mock case circumstances were tested using SGMPlus™ and the newly introduced DNA-17(+) multiplexes and reported by participating laboratories. The results demonstrated a high degree of consistency in analytical methods and allele designations, but some variation in the statistical evaluation and reporting of results. Some of the differences noted were attributable to the major technology change to 17(+)-STR systems which had recently been implemented across the UK at that time. The FSR made recommendations based on the trial outcomes which were intended to produce a more consistent approach to mixtures analysis, interpretation and reporting. Four years later, the Association of Forensic Science Providers (AFSP) repeated the trial, with all major UK and Ireland FSPs (both public sector and private companies) again participating. This second trial used the same mixture set as the 2014 trial but was focussed on the methods for interpretation and evaluation. Since 2014, all UK and Ireland FSPs have implemented probabilistic statistical software using continuous models enabling statistical evaluation of more complex mixtures than was possible in 2014. The trial was therefore aimed at investigating the value of these improved capabilities and also to investigate if there appeared to be marked differences between the different software tools in use in the UK. The results demonstrate a high degree of concordance within and between FSPs and across different evaluation models, and will provide important support for the use of such models in evaluation of mixed DNA profiles.

Evidence evaluation: a response to the court of appeal judgment in R v T.

This is a discussion of a number of issues that arise from the recent judgment in R v T [1]. Although the judgment concerned with footwear evidence, more general remarks have implications for all disciplines within forensic science. Our concern is that the judgment will be interpreted as being in opposition to the principles of logical interpretation of evidence. We reiterate those principles and then discuss several extracts from the judgment that may be potentially harmful to the future of forensic science. A position statement with regard to evidence evaluation, signed by many forensic scientists, statisticians and lawyers, has appeared in this journal [2] and the present paper expands on the points made in that statement.

Calculating likelihood ratios for a mixed DNA profile when a contribution from a genetic relative of a suspect is proposed.

This technical note describes a practical method for evaluating evidence in the case of a two person conditioned DNA mixture where the defence proposition is that the unknown contributor is genetically related to the suspect. A conditioned mixture is one where the presence of DNA from one of two individuals is accepted by both prosecution and defence. A typical example would be a vaginal swab in an alleged rape case, where the presence of the complainant's DNA would be expected and samples have been taken from the complainant and a suspect. Much has been written about the interpretation of such mixtures and the calculation of the conditional genotype probabilities that must be carried out. In general, such treatments assume that the unknown contributor, under the defence proposition, is unrelated to the known individuals. In this paper, we consider the case where the defence proposition is that the unknown contributor is genetically related to the suspect. We describe a method, incorporating a flow chart and reference tables that facilitate manual calculations of the likelihood ratio for several postulated genetic relationships.

A review of likelihood ratios in forensic science based on a critique of Stiffelman "No longer the Gold standard: Probabilistic genotyping is changing the nature of DNA evidence in criminal trials".

Stiffelman [1] gives a broad critique of the application of likelihood ratios (LRs) in forensic science, in particular their use in probabilistic genotyping (PG) software. These are discussed in this review. LRs do not infringe on the ultimate issue. The Bayesian paradigm clearly separates the role of the scientist from that of the decision makers and distances the scientist from comment on the ultimate and subsidiary issues. LRs do not affect the reasonable doubt standard. Fact finders must still make decisions based on all the evidence and they must do this considering all evidence, not just that given probabilistically. LRs do not infringe on the presumption of innocence. The presumption of innocence does not equate with a prior probability of zero but simply that the person of interest (POI) is no more likely than anyone else to be the donor. Propositions need to be exhaustive within the context of the case. That is, propositions deemed relevant by either defense or prosecution which are not fanciful must not be omitted from consideration.

A response to "Likelihood ratio as weight of evidence: A closer look" by Lund and Iyer.

Recently, Lund and Iyer (L&I) raised an argument regarding the use of likelihood ratios in court. In our view, their argument is based on a lack of understanding of the paradigm. L&I argue that the decision maker should not accept the expert's likelihood ratio without further consideration. This is agreed by all parties. In normal practice, there is often considerable and proper exploration in court of the basis for any probabilistic statement. We conclude that L&I argue against a practice that does not exist and which no one advocates. Further we conclude that the most informative summary of evidential weight is the likelihood ratio. We state that this is the summary that should be presented to a court in every scientific assessment of evidential weight with supporting information about how it was constructed and on what it was based.

Adventitious match probability for autosomal profiles when primer binding site mutation is possible.

This paper considers the situation where two DNA systems with differing primers have been used to produce DNA profiles for loading and searching of a DNA Database. With any profiling system there exists the possibility of a "primer binding site mutation" (PBSM). When such a mutation occurs at one of the loci in a profile, it has the effect that the associated allele is not visible in the profile. In the case where a person has two different alleles at a given locus (heterozygous) the effect of a PBSM would be that the profile would appear to be that of an individual with only one allele at that locus (homozygous). The paper investigates the potential for an adventitious match as a result of a PBSM when, for example, a crime profile and person profile that have originated from two different individuals are found to be the same as a result of a PBSM in one of the profiles. It is demonstrated, both by theory and using simulations, that the effect of PBSMs is to slightly decrease the adventitious match probability from what it would had the same DNA system been used.

A Practical Guide for the Formulation of Propositions in the Bayesian Approach to DNA Evidence Interpretation in an Adversarial Environment.

The interpretation of complex DNA profiles is facilitated by a Bayesian approach. This approach requires the development of a pair of propositions: one aligned to the prosecution case and one to the defense case. This note explores the issue of proposition setting in an adversarial environment by a series of examples. A set of guidelines generalize how to formulate propositions when there is a single person of interest and when there are multiple individuals of interest. Additional explanations cover how to handle multiple defense propositions, relatives, and the transition from subsource level to activity level propositions. The propositions depend on case information and the allegations of each of the parties. The prosecution proposition is usually known. The authors suggest that a sensible proposition is selected for the defense that is consistent with their stance, if available, and consistent with a realistic defense if their position is not known.

The logical foundations of forensic science: towards reliable knowledge.

The generation of observations is a technical process and the advances that have been made in forensic science techniques over the last 50 years have been staggering. But science is about reasoning-about making sense from observations. For the forensic scientist, this is the challenge of interpreting a pattern of observations within the context of a legal trial. Here too, there have been major advances over recent years and there is a broad consensus among serious thinkers, both scientific and legal, that the logical framework is furnished by Bayesian inference (Aitken et al. Fundamentals of Probability and Statistical Evidence in Criminal Proceedings). This paper shows how the paradigm has matured, centred on the notion of the balanced scientist. Progress through the courts has not been always smooth and difficulties arising from recent judgments are discussed. Nevertheless, the future holds exciting prospects, in particular the opportunities for managing and calibrating the knowledge of the forensic scientists who assign the probabilities that are at the foundation of logical inference in the courtroom.

Testing likelihood ratios produced from complex DNA profiles.

The performance of any model used to analyse DNA profile evidence should be tested using simulation, large scale validation studies based on ground-truth cases, or alignment with trends predicted by theory. We investigate a number of diagnostics to assess the performance of the model using Hd true tests. Of particular focus in this work is the proportion of comparisons to non-contributors that yield a likelihood ratio (LR) higher than or equal to the likelihood ratio of a known contributor (LRPOI), designated as p, and the average LR for Hd true tests. Theory predicts that p should always be less than or equal to 1/LRPOI and hence the observation of this in any particular case is of limited use. A better diagnostic is the average LR for Hd true which should be near to 1. We test the performance of a continuous interpretation model on nine DNA profiles of varying quality and complexity and verify the theoretical expectations.

A series of recommended tests when validating probabilistic DNA profile interpretation software.

There has been a recent push from many jurisdictions for the standardisation of forensic DNA interpretation methods. Current research is moving from threshold-based interpretation strategies towards continuous interpretation strategies. However laboratory uptake of software employing probabilistic models is slow. Some of this reluctance could be due to the perceived intimidating calculations to replicate the software answers and the lack of formal internal validation requirements for interpretation software. In this paper we describe a set of experiments which may be used to internally validate in part probabilistic interpretation software. These experiments included both single source and mixed profiles calculated with and without dropout and drop-in and studies to determine the reproducibility of the software with replicate analyses. We do this by way of example using three software packages: STRmix™, LRmix, and Lab Retriever. We outline and demonstrate the profile examples where the expected answer may be calculated and provide all calculations.

Interpreting small quantities of DNA: the hierarchy of propositions and the use of Bayesian networks.

The dramatic increase in the sensitivity of DNA profiling systems that has occurred over recent years has led to the need to address a wider range of interpretational problems in forensic science. The issues surrounding questions of the kind "whose DNA is this?" have been the subject of considerable controversy but now it is clear that the emphasis is shifting to questions of the kind "how did this DNA get here?" Such issues are discussed in this paper and new insights are provided by two particular recent developments. First, the notion of the "hierarchy of propositions" that has arisen from a project called Case Assessment and Interpretation (CAI) that has been running in the British Forensic Science Service (FSS). Second, a technique for drawing inferences in the face of many interacting considerations, known as "Bayesian networks"--or "Bayes' nets" for short--that has been the subject of an earlier paper in this journal (1). The discussion is carried out by means of case studies, based on actual cases. It is clear that, whereas the inference in relation to the source of the DNA in a crime sample might be overwhelmingly strong, the inference in relation to the propositions that a jury must consider relating to the identity of the actual offender may be much more tentative.

Evaluating forensic DNA profiles using peak heights, allowing for multiple donors, allelic dropout and stutters.

Increases in the sensitivity of DNA profiling technology now allow profiles to be obtained from smaller and more degraded DNA samples than was previously possible. The resulting profiles can be highly informative, but the subjective elements in the interpretation make it problematic to achieve the valid and efficient evaluation of evidential strength required in criminal cases. The problems arise from stochastic phenomena such as "dropout" (absence of an allele in the profile that is present in the underlying DNA) and experimental artefacts such as "stutter" that can generate peaks of ambiguous allelic status. Currently in the UK, evidential strength evaluation uses an approach in which the complex signals in the DNA profiles are interpreted in a semi-manual fashion by trained experts aided by a set of guidelines, but also relying substantially on professional judgment. We introduce a statistical model to calculate likelihood ratios for evaluating DNA evidence arising from multiple known and unknown contributors that allows for such stochastic phenomena by incorporating peak heights. Efficient use of peak heights allows for more crime scene profiles to be reported to courts than is currently possible. The model parameters are estimated from experimental data incorporating multiple sources of variability in the profiling system. We report and analyse experimental results from the SGMPlus system, run at 28 amplification cycles with no enhancements, currently used in the UK. Our methods are readily adapted to other DNA profiling systems provided that the experimental data for the parameter estimation is available.

Quantitative assessment of evidential weight for a fingerprint comparison. Part II: a generalisation to take account of the general pattern.

The authors have proposed a quantitative method for assessing weight of evidence in the case where a fingermark from a crime scene is compared with a set of control prints from the ten fingers of a suspect. The approach is based on the notion of calculating a Likelihood Ratio (LR) that addresses a pair of propositions relating to the individual who left the crime mark. The current method considers only information extracted from minutiae, such as location, direction and type. It does not consider other information usually taken into account by fingerprint examiners, such as the general pattern of the ridge flow on the mark and the control prints. In this paper, we propose an improvement to our model that allows a fingerprint examiner to take advantage of pattern information when assessing the evidential weight to be assigned to a fingerprint comparison. We present an extension of the formal analysis proposed earlier and we illustrate our approach with an example.