Applications and extensions of subpopulation theory: a caseworkers guide

This paper extends the calculation of conditional probabilities from those given by Balding and Nichols to casework situations where a series of possible DNA types are possible. Such situations may occur when a sample is identified containing a mixture of DNA from two or more people or where extra information can be determined about the subpopulation under consideration by analysis of additional samples. Using this approach, the error in the estimated likelihood ratios is expected to reduce as the number of additional individuals typed from the subpopulation increases.     

Choice of population database for forensic DNA profile analysis

When evaluating the weight of evidence (WoE) for an individual to be a contributor to a DNA sample, an allele frequency database is required. The allele frequencies are needed to inform about genotype probabilities for unknown contributors of DNA to the sample. Typically databases are available from several populations, and a common practice is to evaluate the WoE using each available database for each unknown contributor. Often the most conservative WoE (most favourable to the defence) is the one reported to the court. However the number of human populations that could be considered is essentially unlimited and the number of contributors to a sample can be large, making it impractical to perform every possible WoE calculation, particularly for complex crime scene profiles. We propose instead the use of only the database that best matches the ancestry of the queried contributor, together with a substantial F_ST adjustment. To investigate the degree of conservativeness of this approach, we performed extensive simulations of one- and two-contributor crime scene profiles, in the latter case with, and without, the profile of the second contributor available for the analysis. The genotypes were simulated using five population databases, which were also available for the analysis, and evaluations of WoE using our heuristic rule were compared with several alternative calculations using different databases. Using F_ST = 0.03, we found that our heuristic gave WoE more favourable to the defence than alternative calculations in well over 99% of the comparisons we considered; on average the difference in WoE was just under 0.2 bans (orders of magnitude) per locus. The degree of conservativeness of the heuristic rule can be adjusted through the F_ST value. We propose the use of this heuristic for DNA profile WoE calculations, due to its ease of implementation, and efficient use of the evidence while allowing a flexible degree of conservativeness.     

Validating TrueAllele® Interpretation of DNA Mixtures Containing up to Ten Unknown Contributors

Most DNA evidence is a mixture of two or more people. Cybergenetics TrueAllele^® system uses Bayesian computing to separate genotypes from mixture data and compare genotypes to calculate likelihood ratio (LR) match statistics. This validation study examined the reliability of TrueAllele computing on laboratory-generated DNA mixtures containing up to ten unknown contributors. Using log(LR) match information, the study measured sensitivity, specificity, and reproducibility. These reliability metrics were assessed under different conditions, including varying the number of assumed contributors, statistical sampling duration, and setting known genotypes. The main determiner of match information and variability was how much DNA a person contributed to a mixture. Observed contributor number based on data peaks gave better results than the number known from experimental design. The study found that TrueAllele is a reliable method for analyzing DNA mixtures containing up to ten unknown contributors.     

Removal of a PCR inhibitor and resolution of DNA STR types in mixed human-canine stains from a five year old case.

The analysis of biological trace evidence from a reopened investigation into a 1991 murder from Vernon, B.C. revealed mixed human and dog bloodstains on blue jean pants that contained a PCR inhibitory substance. The presence of the inhibitory substance was detected by the inhibition caused from adding a small aliquot of the test DNA extract into a PCR reaction designed to produce a known standard product. The removal of the PCR inhibitory substance was accomplished by treating the extracted DNA with Thiopropyl Sepharose 6B beads. DNA profiles from two human contributors and a canine were obtained using species specific polymorphic STR markers. The two human DNA profiles obtained from blue jean pants were resolved, one matched the suspect and the other matched the victim. The DNA profile from the canine component matched that obtained from the known sample of the victim's dog who was also slain during the assault. This evidence along with other DNA typing evidence was critical in obtaining a resolution of the case.     

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.     

Simulated approach to estimate the number and combination of known/unknown contributors in mixed DNA samples using 15 short tandem repeat loci

The calculation of likelihood ratios (LRs) for DNA mixture analysis is necessary to establish an appropriate hypothesis based on the estimated number of contributors and known contributor genotypes. In this paper, we recommend a relevant analytical method from the 15 short tandem repeat typing system (the Identifiler multiplex), which is used as a standard in Japanese forensic practice and incorporates a flowchart that facilitates hypothesis formulation. We postulate that: (1) all detected alleles need to be above the analytical threshold (e.g., 150 relative fluorescence unit (RFU)); (2) alleles of all known contributors should be detected in the mixture profile; (3) there should be no contribution from close relatives. Furthermore, we deduce that mixtures of four or more persons should not be interpreted by Identifiler as the LR values of 100,000 simulated cases have a lower expectation of exceeding our temporal LR threshold (10,000) which strongly supports the prosecution hypothesis. We validated the method using various computer-based simulations. The estimated number of contributors is most likely equal to the actual number if all alleles detected in the mixture can be assigned to those from the known contributors. By contrast, if an unknown contributor(s) needs to be designated, LRs should be calculated from both two-person and three-person contributions. We also consider some cases in which the unknown contributor(s) is genetically related to the known contributor(s).     

Probabilistic genotyping of single cell replicates from complex DNA mixtures recovers higher contributor LRs than standard analysis

DNA mixtures are a common source of crime scene evidence and are often one of the more difficult sources of biological evidence to interpret. With the implementation of probabilistic genotyping (PG), mixture analysis has been revolutionized allowing previously unresolvable mixed profiles to be analyzed and probative genotype information from contributors to be recovered. However, due to allele overlap, artifacts, or low-level minor contributors, genotype information loss inevitably occurs. In order to reduce the potential loss of significant DNA information from donors in complex mixtures, an alternative approach is to physically separate individual cells from mixtures prior to performing DNA typing thus obtaining single source profiles from contributors. In the present work, a simplified micro-manipulation technique combined with enhanced single-cell DNA typing was used to collect one or few cells, referred to as direct single-cell subsampling (DSCS). Using this approach, single and 2-cell subsamples were collected from 2 to 6 person mixtures. Single-cell subsamples resulted in single source DNA profiles while the 2-cell subsamples returned either single source DNA profiles or new mini-mixtures that are less complex than the original mixture due to the presence of fewer contributors. PG (STRmix™) was implemented, after appropriate validation, to analyze the original bulk mixtures, single source cell subsamples, and the 2-cell mini mixture subsamples from the original 2–6-person mixtures. PG further allowed replicate analysis to be employed which, in many instances, resulted in a significant gain of genotype information such that the returned donor likelihood ratios (LRs) were comparable to that seen in their single source reference profiles (i.e., the reciprocal of their random match probabilities). In every mixture, the DSCS approach gave improved results for each donor compared to standard bulk mixture analysis. With the 5- and 6- person complex mixtures, DSCS recovered highly probative LRs (≥10²⁰) from donors that had returned non-probative LRs (<10³) by standard methods.     

DNA mixtures in forensic casework: a 4-year retrospective study

Occasionally interpretation guidelines from validation studies are difficult to apply to real forensic casework, especially in the case of mixed samples. Exogenous contamination, an unknown number of contributors or unbalanced proportion of each one in the sample and a varied degree of degradation of the biological materials, contribute to the difficulties in the interpretation of sample profiles. In this paper we have reviewed all the mixed genetic STR profiles encountered in our laboratory over 4 years (1997-2000) and evaluated the problems in the interpretation of the results. From 1547 criminal cases with 2424 samples typed, 163 showed a mixed profile (6.7%). We have observed that occasionally, a mixture appeared in the same sample with one multiplex amplification kit (e.g. Blue) and not with another (e.g. Green). From our results, it can be suggested that technical characteristics of the different fluorochrome groups in the multiplexes override the molecular characteristics of each STR in their capacity to detect mixtures.     

Two or three contributors of DNA mixtures? – Some practical considerations

The number of contributors is hard to determine in DNA mixture profiles. Here, we deal with the special but frequent case that either two or three contributors are possible. In fact, it might happen that two contributors can explain the number of alleles seen but that three contributors are necessary if a specific person of interest is to be included in the mixture. Then the likelihood ratio assuming two contributors will be zero while the likelihood ratio for three contributors may be large. We evaluate this situation and offer suggestions on how to arrive at an overall likelihood ratio. To exemplify our line of reasoning we use an example proposed by Biedermann, Taroni and Thompson.     

Implementing statistical learning methods through Bayesian networks (Part 2): Bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures – introduced through the use of Bayesian networks in Part I of this series of papers – for ‘learning’ probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.     

A method to enable forensic genetic genealogy investigations from DNA mixtures

The presence of more than one DNA contributor in an evidentiary sample may preclude attempts to use forensic genetic genealogy to develop an investigative lead. To address this issue, we developed a workflow for deconvolution of SNP mixtures into single source profiles that are suitable for matching against a genealogical database. Using the method, two-contributor DNA mixtures assayed using a commercial SNP typing kit can produce informative match results for both major and minor contributors.     

The influence of police interventions and alternative income sources on the dynamic process of choosing crime as a career

This paper demonstrates how a rational process of choice may be influenced by both deterrence forces and economic opportunities. This choice is modeled by a dynamic (Markov) process which captures self-sorting by youth among the categories of innocents, desisters, and persisters. in crime. A key to the results is the introduction of the perceived probability of punishment and its influence on the sorting process. The analysis shows how this force and the availability, or lack of, economic opportunities or income sources modify transition probabilities. The long-run consequences will be a larger subpopulation of individuals who have experimented with crime but subsequently revert to crime-free behavior and a smaller subpopulation of individuals who commit a greater share of crime. Empirical evidence is based on data from the New Youth Cohort of the National Longitudinal Surveys.     

A MCMC method for resolving two person mixtures

In this paper a Monte Carlo Markov Chain (MCMC) method for resolving DNA mixtures containing at most four peaks per locus into a major and a minor contributor is presented. Unlike previous methods, this method can provide posterior probability assessments of the most probable genotype and a likely range for the mixing proportion. The proposed method is applied to two DNA mixtures where the true genotypes of the contributors are known. The method provides posterior probabilities of the genotypes of the contributes which concord strongly with the known facts.     

PENDULUM--a guideline-based approach to the interpretation of STR mixtures

Several years ago, a theory to interpret mixed DNA profiles was proposed that included a consideration of peak area using the method of least squares. This method of mixture interpretation has not been widely adopted because of the complexity of the associated calculations. Most reporting officers (RO) employ an experience and judgement based approach to the interpretation of mixed DNA profiles. Here we present an approach that has formalised the thinking behind this experience and judgement. This has been written into a computer program package called PENDULUM. The program uses a least squares method to estimate the pre-amplification mixture proportion for two potential contributors. It then calculates the heterozygous balance for all of the potential sets of genotypes. A list of "possible" genotypes is generated using a set of heuristic rules. External to the programme the candidate genotypes may then be used to formulate likelihood ratios (LR) that are based on alternative casework propositions. The system does not represent a black box approach; rather it has been integrated into the method currently used by the reporting officers at the Forensic Science Service (FSS). The time saved in automating routine calculations associated with mixtures analysis is significant. In addition, the computer program assists in unifying reporting processes, thereby improving the consistency of reporting.     

Identification and separation of DNA mixtures using peak area information

We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic identification problems involving DNA mixture traces using quantitative peak area information. Peak area is modelled with conditional Gaussian distributions. The expert system can be used for ascertaining whether individuals, whose profiles have been measured, have contributed to the mixture. It can also be used to predict DNA profiles of unknown contributors by separating the mixture into its individual components. The potential of our probabilistic methodology is illustrated on case data examples and compared with alternative approaches. The advantages are that identification and separation issues can be handled in a unified way within a single probabilistic model and the uncertainty associated with the analysis is quantified. Further work, required to bring the methodology to a point where it could be applied to the routine analysis of casework, is discussed.     

Implication of population structure in the resolution of cattle stealing cases

Estimation of population subdivision using genetic markers shows that genetic differentiation in livestock and pet breeds is significantly higher than in human populations. Nevertheless, the influence of population substructure and sample size on match probability has not been extensively analyzed in domestic species. To evaluate the magnitude of the subpopulation effect on estimation of match probabilities in bovine robbery cases, we calculated and compared the match probabilities obtained from cattle breed databases using both real, adjudicated cases from the Buenos Aires Province (Argentina), as well as simulated data. While the Balding and Nichols' correction, when applied to the population database used in the case, produce a more conservative value favorable to the defendant, the match probabilities calculated using the simple product estimator produce a value favorable to the prosecution. We suggest an alternative procedure that can be used. The method consists of choosing the highest value from all match probabilities calculated from the database of each breed. This approach represents an intermediate and more accurate estimation of match probability, although it still produces a slight conservative value favorable to the defense.     

Using FastID to analyze complex SNP mixtures from indoor dust

Forensically relevant single nucleotide polymorphisms (SNPs) can provide valuable supplemental information to short tandem repeats (STRs) for investigative leads, and genotyping can now be streamlined using massively parallel sequencing (MPS). Dust is an attractive evidence source, as it accumulates on undisturbed surfaces, often is overlooked by perpetrators, and contains sufficient human DNA for analysis. To assess whether SNPs genotyped from indoor dust using MPS could be used to detect known household occupants, 13 households were recruited and provided buccal samples from each occupant and dust from five predefined indoor locations. Thermo Fisher Scientific Precision ID Identity and Ancestry Panels were utilized for SNP genotyping, and sequencing was completed using Illumina^® chemistry. FastID, a software developed to permit mixture analysis and identity searching, was used to assess whether known occupants could be detected from associated household dust samples. A modified “subtraction” method was also used in FastID to estimate the percentage of alleles in each dust sample contributed by known and unknown occupants. On average, 72% of autosomal SNPs were recovered from dust samples. When using FastID, (a) 93% of known occupants were detected in at least one indoor dust sample and could not be excluded as contributors to the mixture, and (b) non-contributor alleles were detected in 54% of dust samples (29 ± 11 alleles per dust sample). Overall, this study highlights the potential of analyzing human DNA present in indoor dust to detect known household occupants, which could be valuable for investigative leads.     

Beyond traditional paternity and identification cases. Selecting the most probable pedigree

The paper extends on the traditional methodology used to quantify DNA evidence in paternity or identification cases. By extending we imply that there are more than two alternatives to choose between. In a standard paternity case the two competing explanations H(1): "John Doe is the father of the child and H(2): "A random man is the father of the child, are typically considered. A paternity index of 100000 implies that the data is 100000 more likely assuming hypothesis H(1) rather than H(2). If H(2) is replaced by "A brother of John Doe is the father", the LR may change dramatically. The main topic of this paper is to determine the most probable pedigree given a certain set of data including DNA profiles. In the previous example this corresponds to determining the most likely relation between John Doe and the child. Based on DNA obtained from victims of a fire, bodies found in an ancient grave or from individuals seeking to confirm their anticipated family relations, we would like to determine the most probable pedigree. The approach we present provides the possibility to combine non-DNA evidence, say age of individuals, and DNA profiles. The program familias, obtainable as shareware from http://www.nr.no/familias, delivers the probabilities for the various family constellations. More precisely, the information (if any) prior to DNA is combined with the DNA-profiles in a Bayesian manner to deliver the posterior probabilities. We exemplify using the well published Romanov data where the accepted solution emerges among 4536 possibilities considered. Various other applications based on forensic case work are discussed. In addition we have simulated data to resemble an incest case. Since the true family relation is known in this case, we may evaluate the method.     

Analysis of artificial fireplace logs by high temperature gas chromatography

High temperature gas chromatography is used to analyze the wax of artificial fireplace logs (firelogs). Firelogs from several different manufacturers are studied and compared. This study shows that the wax within a single firelog is homogeneous and that the wax is also uniform throughout a multi-firelog package. Different brands are shown to have different wax compositions. Firelogs of the same brand, but purchased in different locations, also have different wax compositions. With this information it may be possible to associate an unknown firelog sample to a known sample, but a definitive statement of the origin cannot be made.