DNA transfer by examination tools – a risk for forensic casework?

The introduction of profiling systems with increased sensitivity has led to a concurrent increase in the risk of detecting contaminating DNA in forensic casework. To evaluate the contamination risk of tools used during exhibit examination we have assessed the occurrence and level of DNA transferred between mock casework exhibits, comprised of cotton or glass substrates, and high-risk vectors (scissors, forceps, and gloves). The subsequent impact of such transfer in the profiling of a target sample was also investigated. Dried blood or touch DNA, deposited on the primary substrate, was transferred via the vector to the secondary substrate, which was either DNA-free or contained a target sample (dried blood or touch DNA). Pairwise combinations of both heavy and light contact were applied by each vector in order to simulate various levels of contamination.The transfer of dried blood to DNA-free cotton was observed for all vectors and transfer scenarios, with transfer substantially lower when glass was the substrate. Overall touch DNA transferred less efficiently, with significantly lower transfer rates than blood when transferred to DNA-free cotton; the greatest transfer of touch DNA occurred between cotton and glass substrates. In the presence of a target sample, the detectability of transferred DNA decreased due to the presence of background DNA. Transfer had no impact on the detectability of the target profile, however, in casework scenarios where the suspect profiles are not known, profile interpretation becomes complicated by the addition of contaminating alleles and the probative value of the evidence may be affected. The results of this study reiterate the need for examiners to adhere to stringent laboratory cleaning protocols, particularly in the interest of contamination minimisation, and to reduce the handling of items to prevent intra-item transfer.     

A molecular exploration of human DNA/RNA co-extracted from the palmar surface of the hands and fingers

“Touch DNA” refers to the DNA that is left behind when a person touches or comes into contact with an item. However, the source of touch DNA is still debated and the large variability in DNA yield from casework samples suggests that, besides skin, various body fluids can be transferred through contact. Another important issue concerning touch DNA is the possible occurrence of secondary transfer, but the data published in the literature in relation to the background levels of foreign DNA present on the hand surfaces of the general population are very limited.As the present study aimed at better understanding the nature and characteristics of touch DNA, samples were collected from the palmar surface of the hands and fingers (“PHF” samples) of 30 male and 30 female donors by tape-lifting/swabbing and subjected to DNA/RNA co-extraction. Multiplex mRNA profiling showed that cellular material different from skin could be observed in 15% of the PHF samples. The total amount of DNA recovered from these samples (median 5.1 ng) was significantly higher than that obtained from samples containing skin cells only (median 1.6 ng).The integrity of the DNA isolated from the donors’ hands and fingers as well as the prevalence of DNA mixtures were evaluated by STR typing and compared with reference STR profiles from buccal swabs. DNA integrity appeared significantly higher in the male rather than in the female subsample, as the average percentage of the donors’ alleles effectively detected in PHF profiles was 75.1% and 60.1%, respectively. The prevalence of mixtures with a foreign DNA contribution ≥20% was 19.2% (30.0% in the female PHF samples and 8.3% in the male PHF samples).The obtained results support the hypothesis that transfer of cellular material different from skin may underlie the occasional recovery of quality STR profiles from handled items. These results also suggest that gender may represent an important factor influencing the propensity of individuals to carry and transfer DNA through hand contact, possibly because of the differences in personal and hygiene habits between males and females.     

Interpreting a major component from a mixed DNA profile with an unknown number of minor contributors

Modern interpretation strategies typically require an assignment of the number of contributors (N) to a DNA profile. This can prove to be a difficult task, particularly when dealing with higher order mixtures or mixtures where one or more contributors have donated low amounts of DNA. Differences in the assigned N at interpretation can lead to differences in the likelihood ration (LR). If the number of contributors cannot reasonably be assigned, then an interpretation of the profile may not be able to be progressed.In this study, we investigate mixed DNA profiles of varying complexity and interpret them altering the assigned N. We assign LRs for true- and non- contributors and compare the results given different assignments of N over a range of mixture proportions. When a component of a mixture had a proportion of at least 10%, a ratio of at least 1.5:1 to the next highest component, and a DNA amount (as determined by STRmix™) of at least 50 rfu, the LR of the component for a true contributor was not significantly affected by varying N and was therefore suitable for interpretation and the assignment of an LR. LRs produced for minor contributors were found to vary significantly as the assigned N was changed. These heuristics may be used to identify profiles suitable for interpretation.     

Searching mixed DNA profiles directly against profile databases

DNA databases have revolutionised forensic science. They are a powerful investigative tool as they have the potential to identify persons of interest in criminal investigations. Routinely, a DNA profile generated from a crime sample could only be searched for in a database of individuals if the stain was from single contributor (single source) or if a contributor could unambiguously be determined from a mixed DNA profile. This meant that a significant number of samples were unsuitable for database searching. The advent of continuous methods for the interpretation of DNA profiles offers an advanced way to draw inferential power from the considerable investment made in DNA databases. Using these methods, each profile on the database may be considered a possible contributor to a mixture and a likelihood ratio (LR) can be formed. Those profiles which produce a sufficiently large LR can serve as an investigative lead.In this paper empirical studies are described to determine what constitutes a large LR. We investigate the effect on a database search of complex mixed DNA profiles with contributors in equal proportions with dropout as a consideration, and also the effect of an incorrect assignment of the number of contributors to a profile. In addition, we give, as a demonstration of the method, the results using two crime samples that were previously unsuitable for database comparison. We show that effective management of the selection of samples for searching and the interpretation of the output can be highly informative.     

An investigation of a set of DIP-STR markers to detect unbalanced DNA mixtures among the southwest Chinese Han population

The resolution of DNA mixtures is still a difficult problem that is worthy of further study. A common method applied for analysing mixtures is the use of autosomal STR markers as well as related calculation software based on genotypes; however, these markers have a limitation in detecting minor DNA in unbalanced mixtures if major DNA constitutes over 95% of the stain. Novel biomarkers, such as Y-STR, DIP-STR and SNP-STR, have been shown to perform well in distinguishing DNA donors in this type of mixture. DIP-STR can successfully target minor DNA in 1000-fold background DNA using two separate allele-specific primers. However, whether this method can successfully detect minor DNA primarily depends on the distribution of the DIPs in a population. Until now, only Swiss population data have been reported; therefore in this study, we selected 10 DIP-STR markers that performed well in the Swiss population and investigated whether these markers were also useful among the southwest Chinese Han population. The allele frequencies were estimated based on 152 samples, and six of the ten DIP-STR makers had a relatively high probability of informative markers (I value), which indicated their potential usefulness in the southwest Chinese Han population. A comparative study of DIP-STR markers and autosomal STR markers demonstrated that DIP-STR markers detected minor DNA at a ratio of 1:1000, while autosomal STR markers often failed to genotype minor DNA because of strong background noises caused by large amount of major DNA. However, the discrimination power was not high enough using these six DIPs alone. Therefore, we suggest that development of a panel with more loci is imperative and that a panel combined with DIP-STR and SNP-STR markers may be a possible way to achieve better discrimination power.     

The efficacy of DNA mixture to mixture matching

Standard practice in forensic science is to compare a person of interest’s (POI) reference DNA profile with an evidence DNA profile and calculate a likelihood ratio that considers propositions including and excluding the POI as a DNA donor. A method has recently been published that provides the ability to compare two evidence profiles (of any number of contributors and of any level of resolution) comparing propositions that consider the profiles either have a common contributor, or do not have any common contributors. Using this method, forensic analysts can provide intelligence to law enforcement by linking crime scenes when no suspects may be available. The method could also be used as a quality assurance measure to identify potential sample to sample contamination. In this work we analyse a number of constructed mixtures, ranging from two to five contributors, and with known numbers of common contributors, in order to investigate the performance of using likelihood ratios for mixture to mixture comparisons. Our findings demonstrate the ability to identify common donors in DNA mixtures with the power of discrimination depending largely on the least informative mixture of the pair being considered. The ability to match mixtures to mixtures may provide intelligence information to investigators by identifying possible links between cases which otherwise may not have been considered connected.     

Importance sampling allows Hd true tests of highly discriminating DNA profiles

H_d true testing is a way of assessing the performance of a model, or DNA profile interpretation system. These tests involve simulating DNA profiles of non-donors to a DNA mixture and calculating a likelihood ratio (LR) with one proposition postulating their contribution and the alternative postulating their non-contribution. Following Turing it is possible to predict that “The average LR for the H_d true tests should be one” [1]. This suggests a way of validating softwares. During discussions on the ISFG software validation guidelines [2] it was argued by some that this prediction had not been sufficiently examined experimentally to serve as a criterion for validation. More recently a high profile report [3] has emphasised large scale empirical examination.A limitation with H_d true tests, when non-donor profiles are generated at random (or in accordance with expectation from allele frequencies), is that the number of tests required depends on the discrimination power of the evidence profile. If the H_d true tests are to fully explore the genotype space that yields non-zero LRs then the number of simulations required could be in the 10 s of orders of magnitude (well outside practical computing limits). We describe here the use of importance sampling, which allows the simulation of rare events to occur more commonly than they would at random, and then adjusting for this bias at the end of the simulation in order to recover all diagnostic values of interest. Importance sampling, whilst having been employed by others for H_d true tests, is largely unknown in forensic genetics. We take time in this paper to explain how importance sampling works, the advantages of using it and its application to H_d true tests. We conclude by showing that employing an importance sampling scheme brings H_d true testing ability to all profiles, regardless of discrimination power.     

Investigation into the effect of mixtures comprising related people on non-donor likelihood ratios,and potential practises to mitigate providing misleading opinions

The interpretation of mixtures containing related individuals can be difficult due to allele sharing between the contributors. Challenges include the assignment of the number of contributors (NoC) to the mixture with the under assignment of NoC resulting in false exclusions of true donors. Non-donating relatives of the true contributors to mixtures of close relatives can result in likelihood ratios supporting their adventitious inclusion within the mixture. We examine the effect of non-donor likelihood ratios on mixtures of first order relatives. Mixtures of full siblings and parent-child were created by mixing the DNA from known family members in vitro, or by in silico simulation. Mixtures were interpreted using the probabilistic genotyping software STRmix™ and likelihood ratios were assigned for the true donors and non-donors who were either further relatives of the true donors or unrelated to the true donors. The two donor balanced mixtures deconvoluted straightforwardly when analysed as NoC = 2 giving approximately the experimental design 1:1 ratio. When analysed as NoC = 3 a very large number of non-donor genotypes produced LRs close to 1 including many instances of adventitious support. The in vitro three donor balanced mixtures proved difficult to assign as NoC = 3 by a blind examination of the profile. It is likely that many of these would be misassigned as NoC = 2. The analysis of the in vitro and in silico mixtures assuming NoC = 3 with no use of a conditioning profile or with the use of a conditioning profile but without informed priors on the mixture proportions (Mx priors) was ineffective. If the profile can be assigned as NoC = 3 then assignment of the Mx priors is straightforward. This analysis gave no false exclusions. Adventitious support did happen for relatives with high allele sharing. Adventitious support was not observed for any unrelated non-donors. The analysis of the three-person mixtures as NoC = 2 produced many false exclusions and fewer instances of adventitious support. The three donor unbalanced mixtures could all be assigned as NoC= 3. Analysis without Mx priors produced an alternate genotype explanation.     

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 H_d 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 (LR_POI), designated as p, and the average LR for H_d true tests. Theory predicts that p should always be less than or equal to 1/LR_POI and hence the observation of this in any particular case is of limited use. A better diagnostic is the average LR for H_d 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.     

Identifying common donors in DNA mixtures,with applications to database searches

Several methods exist to compute the likelihood ratio LR(M, g) evaluating the possible contribution of a person of interest with genotype g to a mixed trace M. In this paper we generalize this LR to a likelihood ratio LR(M₁, M₂) involving two possibly mixed traces M₁ and M₂, where the question is whether there is a donor in common to both traces. In case one of the traces is in fact a single genotype, then this likelihood ratio reduces to the usual LR(M, g). We explain how our method conceptually is a logical consequence of the fact that LR calculations of the form LR(M, g) can be equivalently regarded as a probabilistic deconvolution of the mixture.Based on simulated data, and using a semi-continuous mixture evaluation model, we derive ROC curves of our method applied to various types of mixtures. From these data we conclude that searches for a common donor are often feasible in the sense that a very small false positive rate can be combined with a high probability to detect a common donor if there is one. We also show how database searches comparing all traces to each other can be carried out efficiently, as illustrated by the application of the method to the mixed traces in the Dutch DNA database.     

Using big data from probabilistic genotyping to solve crime

Forensic Science South Australia (FSSA) has been using STRmix™ software to deconvolute all reported DNA mixtures since 2012. Almost a decade of deconvolutions had led to a substantial repository of analysed profile data that can be interrogated to observe trends in case type, location or occurrence. In addition, deconvolutions can be compared in order to identify common DNA donors and reveal new intelligence information in cases where DNA profiling has previously provided no investigative information. As a proof of concept all samples deconvoluted as part of criminal casework (suspect or no-suspect) were interrogated and compared to each other using the mixture-to-mixture comparison feature in STRmix™. Within the Adelaide region there were 32 groups of cases that had evidence samples linked by a common DNA donor with LR > 1 million which was in addition to direct links and mixture searching links identified previously. These groups of cases can then be interrogated to reveal additional information to inform Police intelligence gathering. Our paper reports on the findings of this proof-of-concept study.     

Exploring tapelifts as a method for dual workflow STR amplification

Although a version of direct PCR is implemented in forensic laboratories for reference material, its incorporation into workflow for the analysis of touch DNA, as a form of latent DNA, from casework exhibits is not. In addition to concerns about increased sensitivity causing more complex mixtures or the generation of more genetic data implicating an individual superfluous to the context of the alleged event, the complete use of the collected sample in the PCR as template has meant that there is no possibility for data reproducibility when needed. Here it is proposed that the use of tapelifts in touch DNA collection can facilitate replicate direct PCR analysis from a single sample allowing the sample to be re-tested. If all portions of the tapelift result in profiles with allelic and likelihood ratio concordance, these sub-samples may be accepted as technical replicates, thus meeting any accreditation guideline requirements. Furthermore, we assess the use of a single tapelift for both direct PCR and extraction-based PCR workflows to illustrate the potential for benefits of both systems to be facilitated. DNA was deposited by three donors onto six substrates with five sample replicates of each condition. Separation of each tapelift into three portions for three direct PCRs ensued using VeriFiler™ Plus. Separation of single tapelifts into three direct PCRs showed no statistical difference in donor allele calls or RFU, or subsequent LRs associated with their profiles. Comparison of profiles within the single tapelift showed more similarity, with high mixture-to-mixture match likelihoods, than when these sub-samples were compared with profiles generated from other samples. This allows each sub-sample taken from the tapelift to be considered as technical replicates. For dual workflow facilitation assessment, one donor deposited DNA through touch onto six substrates with five research replicates of each. Separation of single tapelifts into two portions, one for direct PCR and the retention and use of the remaining portion for extraction and subsequent PCR, showed no significant difference in allelic yield and subsequent donor comparison LRs. Comparison of deconvoluted profiles produced from a single tapelift showed high mixture-to-mixture match likelihoods, supporting DNA donor concordance. This indicates that removing a portion of a tapelift for direct PCR amplification, while processing the remainder through standard processes, allows increased sensitivity through direct PCR while offering the preparation of an eluate suitable for repeated analyses.     

Improved STR profiles from improvised explosive device (IED): fluorescence latent DNA detection and direct PCR

Bombing accounts for the largest share of terrorist incidents worldwide. Most involve an improvised explosive device (IED): a bomb made from household items. Touch DNA may be left on parts of an IED during assembly. However, an IED conflagration degrades DNA, and there has never been a way to locate where touch DNA may remain. To solve this problem, we combined the use of fluorescent dye to locate latent DNA and direct PCR to improve STR profiles of DNA obtained from IEDs. Six fluorescent DNA-binding dyes were evaluated at various concentrations for the purpose of staining latent DNA. SYBR® Green I and Diamond™ Nucleic Acid dye were able to visualize touch DNA on IED substrates. Inhibition studies with extracted DNA and touch DNA using both dyes revealed that Diamond™ dye inhibited direct STR amplification, while SYBR® Green I did not. Stability studies at three temperatures showed optimum performance of SYBR® Green I up to 24 h after formulation. As such, only SYBR® Green I was further used to develop a “visualized-direct PCR” method. Using the conventional approach and the novel “visualized-direct PCR” approach in a single-blind investigation of mock IED evidence, the “visualized-direct PCR” approach had a 98.6% chance of obtaining more alleles (95% highest density interval (HDI): 0.7 to 10.0 alleles). A decrease in non-donor’s alleles (mixed profiles) was also observed. The developed approach has the potential to revolutionize the process of STR typing from touch DNA.     

Human background DNA on stones in an urban environment

Stones are frequently used as tools in criminal acts. In our department, around 5 % of all analysed crime scene related trace samples are contact or touch DNA traces swabbed from stones. These samples are primarily related to cases of damage to property and burglary. In court, questions can arise about DNA transfer and the persistence of background DNA not related to the respective crime. To shed some light on the question of how likely it is to detect human DNA as background DNA on stones from an urban environment, the surfaces of 108 stones sampled throughout the city of Bern, the Swiss capital, were swabbed. We detected a median quantity of 33 pg on the sampled stones. STR-profiles suitable for a CODIS (Combined DNA Index System) registration in the Swiss DNA database were established from 6.5 % of all sampled stone surfaces. For comparison, retrospective casework data analysis from routine crime scene samples demonstrates a success rate of 20.6 % for the establishment of CODIS-suitable DNA profiles from stones sampled for touch DNA. We further investigated how climatic conditions, location and properties of the stones affected the quantity and quality of the recovered DNA. In this study, we show that the quantity of the measurable DNA decreases significantly with increasing temperature. Furthermore, less DNA could be recovered from porous stones, compared to smooth ones.     

An assessment of the performance of the probabilistic genotyping software EuroForMix: Trends in likelihood ratios and analysis of Type I & II errors

Continuous probabilistic genotyping software enables the interpretation of highly complex DNA profiles that are prone to stochastic effects and/or consist of multiple contributions. The process of introducing probabilistic genotyping into an accredited forensic laboratory requires testing, validation, documentation and training. Documents that include guidelines and/or requirements have been published in order to guide forensic laboratories through this extensive process and there has been encouragements to share the results obtained from internal laboratory studies. To this end, we present the results obtained from the quantitative probabilistic genotyping system EuroForMix applied to mixed DNA profiles with known contributions mixed in known proportions, levels of allele sharing and levels of allelic drop-out. The mixtures were profiled using the PowerPlex® Fusion 6C (PPF6C) kit. Using these mixtures, 427 Hp-true tests and 408 Hd-true tests were performed. In the Hd-true tests, non-contributors were selected deliberately to a have large overlap with the alleles within the mixture and worst-case scenarios were examined in which a simulated relative of one of the true donors was considered as the person of interest under the prosecution hypothesis. The effects of selecting different EuroForMix modelling options, the use of PCR replicates, allelic drop-out, and varying the assigned number of contributors were examined. Instances of Type I and Type II errors are discussed. In addition 330 likelihood ratio results from EuroForMix are compared to the semi-continuous model LRmix Studio. Results demonstrate the performance and trends of EuroForMix when applied to PPF6C profiles.     

Speed of accumulation of DNA in a fingermark

ABSTRACT

Variation has been reported in the amount of DNA accumulating on the skin of individuals. A shedder status is the propensity of a person to transfer DNA to a substrate by touch. In previous tests of shedders, individuals washed their hands and after 15 minutes made contact with substrates at time points up to 180 minutes after handwashing. No examination has looked at the accumulation of cellular material between time zero and this 15 minute time point. Here we present the results of an examination of cellular material within thumbprints at time points 0, 2, 5, 15 and 60 minutes after handwashing using donors who are representative of heavy, intermediate and light shedders. The rate of accumulation of cellular material and the total amount detected in thumbprints showed a difference between these donors, but for all donors the initial rate of accumulation is surprisingly fast. Informative STR profiles can be generated only 2 minutes after handwashing from 100%, 33% and none of the heavy, intermediate and light shedders, respectively. These results confirmed that there was a correlation between the cellular material present on the thumbprint and the percentage success of an STR profile for each individual and time point.     

Shedding light on the relative DNA contribution of two persons handling the same object

Traces collected on crime scene objects frequently result in challenging DNA mixtures from several contributors in different DNA proportions. Understanding how the relative proportion of DNA deposited by different persons who handled the same object evolves through time has important bearings. For instance, this information may help determine whether the major contributor in a mixed DNA profile is more likely to correspond to the object owner or to the person who may have stolen this object. In this perspective, a simulation-based protocol was designed where randomly paired participants were asked to act either as first (object owner) or second (last) users. The first user was asked to handle/wear 9 different plastic-, metal-, nitrile- and fabric-made objects, commonly found at burglary/robbery crime scenes, for a minimum of 20 min during 8 or 10 consecutive days. The second user subsequently used them for 5, 30 or 120 min in three distinct simulation sessions. The analysis of the relative DNA contribution on the resulting 234 mock DNA traces revealed a large variability in the contribution depending on the time, substrate and pairs of participants. Despite this, a progressive increase of the second user’s DNA contribution, relative to the first user, was observed over time in 93% of the traces. The second user was shown to become the major contributor in approximately 15%, 33% and 55% of the traces recovered from objects used for 5, 30 and 120 min, respectively. Single-source DNA profiles were shown to represent only 1% of the traces. In addition, the DNA profiles of 165 out of 234 (71%) simulated traces displayed extra alleles. Most of these occurred in the minor fraction of mixed DNA profiles and were interpreted as artefacts. Nevertheless, DNA profiles of known participants either involved or not in the simulations were observed in 9 cases (4%). This confirms that indirect DNA transfer should be taken into account when interpreting “touch” DNA evidence.     

Exploring the DNA mixture deconvolution through simulation

ABSTRACT

If an unambiguous single-source DNA profile is obtained from a crime scene, then a potential person of interest can either match or not match the crime scene profile and the likelihood ratio for the single matching genotype can be easily computed. Mixed DNA profiles on the other hand are typically ambiguous and a vast number of different likelihood ratios can be obtained depending on the genotype of a potential person of interest that is compared with the mixture later. In the absence of a person of interest it can be unclear how suitable the profile is for discriminating between donors and non-donors. We introduce a simulation method to explore the range of likelihood ratios that is expected to be obtained when a non-donor or a true donor is compared with the mixed DNA profile. Sampling is conditional on the mixture deconvolution obtained using probabilistic genotyping. These simulations help to decide whether or not a (mixed) profile is suitable for comparison to a person of interest. Moreover, the methods can be used to determine whether a profile is suitable for upload to a database and whether or not potential rework could be advised.     

Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach

The number of contributors (NOC) to (complex) autosomal STR profiles cannot be determined with absolute certainty due to complicating factors such as allele sharing and allelic drop-out. The precision of NOC estimations can be improved by increasing the number of (highly polymorphic) markers, the use of massively parallel sequencing instead of capillary electrophoresis, and/or using more profile information than only the allele counts.In this study, we focussed on machine learning approaches in order to make maximum use of the profile information. To this end, a set of 590 PowerPlex® Fusion 6C profiles with one up to five contributors were generated from a total of 1174 different donors. This set varied for the template amount of DNA, mixture proportion, levels of allele sharing, allelic drop-out and degradation. The dataset contained labels with known NOC and was split into a training, test and hold-out set. The training set was used to optimize ten different algorithms with selection of profile characteristics. Per profile, over 250 characteristics, denoted ‘features’, were calculated. These features were based on allele counts, peak heights and allele frequencies. The features that were most related to the NOC were selected based on partial correlation using the training set. Next, the performance of each model (=combination of features plus algorithm) was examined using the test set. A random forest classifier with 19 features, denoted the ‘RFC19-model’ showed best performance and was selected for further validation. Results showed improved accuracy compared to the conventional maximum allele count approach and an in-house nC-tool based on the total allele count. The method is extremely fast and regarded useful for application in forensic casework.     

An investigation of the robustness of the consensus method of interpreting low-template DNA profiles

Forensic STR profiles generated from low-template DNA samples are more noticeably subject to effects such as allele dropout, contamination with spurious alleles (‘drop-in’) and proportionally larger stutter. The profiles obtained are frequently partial, and are challenging to interpret. Specifically, interpretation guidelines which are used when the template DNA is in the optimal range for the STR test kit in use must be adapted to the low-template regime. A commonly used approach to such modified interpretation is known as the ‘consensus’ or ‘biological’ method, and relies on replication to achieve reliable results.We have carried out a study to assess the robustness of the consensus method as applied to SGM Plus^® STR profiles obtained after applying a set of post-PCR purification methods together known as DNA SenCE, and report the results here. Multiple repeat analysis of DNA at five template quantities (ranging between 5 pg and 100 pg) and from five single donors, was carried out, and the resulting profiles were used to produce consensus profiles using several different evaluation criteria.Our aim was to determine whether the consensus profiles produced are conservative, that is, that the alleles reported are associated with the donor and that drop-in is reduced or eliminated. To this end, the alleles in the consensus profiles were compared with those of the donors, and the degree of concordance determined. The results suggest that increasingly stringent requirements for the number of times an allele must be observed in a set of repeat runs do, as expected, reduce the effect of drop-in, but also reduce the evidential value of the consensus profiles. However, the former is reduced to a much greater extent than the latter, resulting in a relative increase in profile information content versus drop-in peak risk with increased stringency.We also found that approximately half of the non-donor peaks appearing in consensus profiles were in −4 stutter positions for donor alleles present in the same profile, suggesting that many of these so-called drop-in alleles are, in fact, large stutter peaks rather than ‘true’ drop-in. Nevertheless, the appearance of non-donor peaks in a profile, including what are assumed to be oversized stutter peaks, appears to be an essentially random event.