Multi-laboratory validation of DNAxs including the statistical library DNAStatistX

Benschop, Corina C.G.; Hoogenboom, Jerry; Bargeman, Fiep; Hovers, Pauline; Slagter, Martin; Linden, Jennifer van der; Parag, Raymond; Kruise, Dennis; Drobnič, Katja; Klucevsek, Gregor; Parson, Walther; Berger, Burkhard; Laurent, François-Xavier; Faivre, Magalie; Ulus, A.; Schneider, Peter M.; Bogus, Magdalena; Kneppers, A. L. J.; Sijen, Titia

doi:10.1016/j.fsigen.2020.102390

Cited by 8 publications

(10 citation statements)

References 11 publications

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“…At the locus level, and as expected, the EuroForMix deconvolution showed improved performance compared to LoCIM [50]. Regardless, since LoCIM is extremely fast and was regarded useful to many cases, this approach was implemented in DNAxs [62], chapter 10 and [37].…”

Section: Dnaxs and Related Modulessupporting

confidence: 56%

“…Both inter-and intra-laboratory studies involve the distribution of mixtures with known ground truth, usually as electronic files after analysis, among forensic scientists within a laboratory and/or to a number of different laboratories. The compiled results give a measure of the variability in performance within and between laboratories [28][29][30][31][32][33][34][35][36][37]. At least two studies [38,39] (hereafter the GHEP-ISFG study and NIST studies) have appeared in courtroom discussion due to the wide range of results observed.…”

Section: Inter and Intra-laboratory Studiesmentioning

confidence: 99%

“…The latest advances for estimating the NOC rely on machine learning approaches enabling optimal use of the available profile information. To date, a few models have been developed for use in forensic DNA casework [37,[90][91][92]. These models make use of more information than the previously developed approaches since they are trained on a separate ground truth dataset.…”

Section: Number Of Contributors (Noc)mentioning

confidence: 99%

“…Lastly, thresholds are used per locus type to infer the major component's alleles. It has been demonstrated that the LoCIM approach is successful regardless of the laboratory's STR typing kit and PCR and CE settings and the method is easy to implement (one only needs to specify the laboratory's stochastic threshold) [29,37].…”

Section: Dnaxs and Related Modulesmentioning

confidence: 99%

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A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Gill

Benschop

Buckleton

et al. 2021

Genes

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Probabilistic genotyping has become widespread. EuroForMix and DNAStatistX are both based upon maximum likelihood estimation using a γ model, whereas STRmix™ is a Bayesian approach that specifies prior distributions on the unknown model parameters. A general overview is provided of the historical development of probabilistic genotyping. Some general principles of interpretation are described, including: the application to investigative vs. evaluative reporting; detection of contamination events; inter and intra laboratory studies; numbers of contributors; proposition setting and validation of software and its performance. This is followed by details of the evolution, utility, practice and adoption of the software discussed.

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Section: Dnaxs and Related Modulessupporting

confidence: 56%

Section: Inter and Intra-laboratory Studiesmentioning

confidence: 99%

Section: Number Of Contributors (Noc)mentioning

confidence: 99%

Section: Dnaxs and Related Modulesmentioning

confidence: 99%

See 2 more Smart Citations

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Gill

Benschop

Buckleton

et al. 2021

Genes

View full text Add to dashboard Cite

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“…There have been other attempts to compare the reproducibility of outputs amongst different PG systems, but most of these (e.g., [23][24][25][26][27]) have involved submitting the same epgs from the same STR amplification kits to different PG algorithms. Benschop et al [28] describe a validation of one PG system (DNAxs) in five laboratories using STR genotype data (alleles and peak heights) generated within each laboratory from different STR assays. Each laboratory shared its genotyping results with the others, and LRs were mostly within an order of magnitude for the same genotype data.…”

mentioning

confidence: 99%

Proposed Framework for Comparison of Continuous Probabilistic Genotyping Systems amongst Different Laboratories

et al. 2021

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Continuous probabilistic genotyping (PG) systems are becoming the default method for calculating likelihood ratios (LRs) for competing propositions about DNA mixtures. Calculation of the LR relies on numerical methods and simultaneous probabilistic simulations of multiple variables rather than on analytical solutions alone. Some also require modelling of individual laboratory processes that give rise to electropherogram artefacts and peak height variance. For these reasons, it has been argued that any LR produced by continuous PG is unique and cannot be compared with another. We challenge this assumption and demonstrate that there are a set of conditions defining specific DNA mixtures which can produce an aspirational LR and thereby provide a measure of reproducibility for DNA profiling systems incorporating PG. Such DNA mixtures could serve as the basis for inter-laboratory comparisons, even when different STR amplification kits are employed. We propose a procedure for an inter-laboratory comparison consistent with these conditions.

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Comparison of genotyping and weight of evidence results when applying different genotyping strategies on samples from a DNA transfer experiment

et al. 2022

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In this study we assessed to what extent data on the subject of TPPR (transfer, persistence, prevalence, recovery) that are obtained through an older STR typing kit can be used in an activity-level evaluation for a case profiled with a more modern STR kit. Newer kits are generally more sensitive and consist of more loci which could increase the evidential value at the source-level. On the other hand, the increased genotyping information may invoke a higher number of contributors in weight of evidence calculations, which could affect the evidential values as well. An activity scenario well explored in earlier studies [1,2] was redone using volunteers with known DNA profiles. DNA extracts were analyzed with three different approaches, namely using the optimal DNA input for 1) an older and 2) a newer STR typing system, and 3) using a standard, volume-based input combined with replicate PCR analysis with only the newer STR kit. The genotyping results were analyzed for various aspects such as percentage detected alleles and relative peak height contribution for background and the contributors known to be involved in the activity. Next, source-level LRs were calculated and the same trends were observed with regards to inclusionary and exclusionary LRs for persons who had or had not been into direct contact with the sampled areas. We subsequently assessed the impact on the outcome of activity-level evaluation in an exemplary case by applying the assigned probabilities to a Bayesian network. We infer that data of different STR kits can be combined in activity-level evaluations.

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Multi-laboratory validation of DNAxs including the statistical library DNAStatistX

Cited by 8 publications

References 11 publications

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Proposed Framework for Comparison of Continuous Probabilistic Genotyping Systems amongst Different Laboratories

Comparison of genotyping and weight of evidence results when applying different genotyping strategies on samples from a DNA transfer experiment

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