1
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A novel computational strategy to predict the value of the evidence in the SNP-based forensic mixtures. PLoS One 2021; 16:e0247344. [PMID: 34653182 PMCID: PMC8519470 DOI: 10.1371/journal.pone.0247344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 09/30/2021] [Indexed: 11/24/2022] Open
Abstract
This study introduces a methodology for inferring the weight of the evidence (WoE) in the single nucleotide polymorphism (SNP)-typed DNA mixtures of forensic interest. First, we redefined some algebraic formulae to approach the semi-continuous calculation of likelihoods and likelihood ratios (LRs). To address the allelic dropouts, a peak height ratio index (“h,” an index of heterozygous state plausibility) was incorporated into semi-continuous formulae to act as a proxy for the “split-drop” model of calculation. Second, the original ratio at which a person of interest (POI) has entered into the mixture was inferred by evaluating the DNA amounts conferred by unique genotypes to any possible permutation of any locus of the typing protocol (unique genotypes are genotypes that appear just once in the relevant permutation). We compared this expected ratio (MRex) to all the mixing ratios emerging at all other permutations of the mixture (MRobs) using several (1 - χ2) tests to evaluate the probability of each permutation to exist in the mixture according to quantitative criteria. At the level of each permutation state, we multiplied the (1 - χ2) value to the genotype frequencies and the h index. All the products of all the permutation states were finally summed to give a likelihood value that accounts for three independent properties of the mixtures. Owing to the (1 - χ2) index and the h index, this approach qualifies as a fully continuous methodology of LR calculation. We compared the MRs and LRs emerging from our methodology to those generated by the EuroForMix software ver. 3.0.3. When the true contributors were tested as POIs, our procedure generated highly discriminant LRs that, unlike EuroForMix, never overcame the corresponding single-source LRs. When false contributors were tested as POIs, we obtained a much lower LR value than that from EuroForMix. These two findings indicate that our computational method is more reliable and realistic than EuroForMix.
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2
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Gill P, Benschop C, Buckleton J, Bleka Ø, Taylor D. A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™. Genes (Basel) 2021; 12:1559. [PMID: 34680954 PMCID: PMC8535381 DOI: 10.3390/genes12101559] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/24/2021] [Accepted: 09/28/2021] [Indexed: 11/24/2022] Open
Abstract
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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Affiliation(s)
- Peter Gill
- Forensic Genetics Research Group, Department of Forensic Sciences, Oslo University Hospital, 0372 Oslo, Norway;
- Department of Forensic Medicine, Institute of Clinical Medicine, University of Oslo, 0315 Oslo, Norway
| | - Corina Benschop
- Division of Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands;
| | - John Buckleton
- Department of Statistics, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand;
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
| | - Øyvind Bleka
- Forensic Genetics Research Group, Department of Forensic Sciences, Oslo University Hospital, 0372 Oslo, Norway;
| | - Duncan Taylor
- Forensic Science SA, GPO Box 2790, Adelaide, SA 5001, Australia;
- School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia
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3
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Interpretation of DNA data within the context of UK forensic science - evaluation. Emerg Top Life Sci 2021; 5:405-413. [PMID: 34027985 PMCID: PMC8760892 DOI: 10.1042/etls20200340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 04/24/2021] [Accepted: 05/04/2021] [Indexed: 12/30/2022]
Abstract
Forensic DNA provides a striking contribution to the provision of justice worldwide. It has proven to be crucial in the investigative phase of an unsolved crime where a suspect needs to be identified, e.g. from a DNA database search both nationally and internationally. It is also a powerful tool in the assignment of evidential weight to the comparison of a profile of a person of interest and a crime scene profile. The focus of this document is the evaluation of autosomal profiles for criminal trials in the UK. A separate review covers investigation and evaluation of Y-STR profiles, investigation using autosomal profiles, kinship analysis, body identification and Forensic Genetic Genealogy investigations. In less than 40 years, forensic DNA profiling has developed from a specialist technique to everyday use. Borrowing on advances in genome typing technology, forensic DNA profiling has experienced a substantial increase in its sensitivity and informativeness. Alongside this development, novel interpretation methodologies have also been introduced. This document describes the state of the art and future advances in the interpretation of forensic DNA data.
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4
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A comprehensive study of allele drop-in over an extended period of time. Forensic Sci Int Genet 2020; 48:102332. [DOI: 10.1016/j.fsigen.2020.102332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 05/22/2020] [Accepted: 06/04/2020] [Indexed: 11/19/2022]
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5
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Butler JM, Willis S. Interpol review of forensic biology and forensic DNA typing 2016-2019. Forensic Sci Int Synerg 2020; 2:352-367. [PMID: 33385135 PMCID: PMC7770417 DOI: 10.1016/j.fsisyn.2019.12.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Accepted: 12/10/2019] [Indexed: 12/23/2022]
Abstract
This review paper covers the forensic-relevant literature in biological sciences from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.
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6
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Kuffel A, Gray A, Nic Daeid N. Human Leukocyte Antigen alleles as an aid to STR in complex forensic DNA samples. Sci Justice 2019; 60:1-8. [PMID: 31924284 DOI: 10.1016/j.scijus.2019.09.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 09/09/2019] [Accepted: 09/15/2019] [Indexed: 10/25/2022]
Abstract
Human biological samples with multiple contributors remain one of the most challenging aspects of DNA typing within a forensic science context. With the increasing sensitivity of commercially available kits allowing detection of low template DNA, complex mixtures are now a standard component of forensic DNA evidence. Over the years, various methods and techniques have been developed to try to resolve the issue of mixed profiles. However, forensic DNA analysis has relied on the same markers to generate DNA profiles for the past 30 years causing considerable challenges in the deconvolution of complex mixed samples. The future of resolving complicated DNA mixtures may rely on utilising markers that have been previously applied to gene typing of non-forensic relevance. With Massively Parallel Sequencing (MPS), techniques becoming more popular and accessible even epigenetic markers have become a source of interest for forensic scientists. The aim of this review is to consider the potential of alleles from the Human Leukocyte Antigen (HLA) complex as effective forensic markers. While Massively Parallel Sequencing of HLA is routinely used in clinical laboratories in fields such as transplantation, pharmacology or population studies, there have not been any studies testing its suitability for forensic casework samples.
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Affiliation(s)
- Agnieszka Kuffel
- Leverhulme Research Centre for Forensic Science, Ewing Building, University of Dundee, Small's Lane, Dundee DD1 4HR, United Kingdom.
| | - Alexander Gray
- Leverhulme Research Centre for Forensic Science, Ewing Building, University of Dundee, Small's Lane, Dundee DD1 4HR, United Kingdom.
| | - Niamh Nic Daeid
- Leverhulme Research Centre for Forensic Science, Ewing Building, University of Dundee, Small's Lane, Dundee DD1 4HR, United Kingdom.
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7
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An assessment of the performance of the probabilistic genotyping software EuroForMix: Trends in likelihood ratios and analysis of Type I & II errors. Forensic Sci Int Genet 2019; 42:31-38. [DOI: 10.1016/j.fsigen.2019.06.005] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 06/07/2019] [Accepted: 06/07/2019] [Indexed: 01/25/2023]
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8
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STRmix™ put to the test: 300 000 non-contributor profiles compared to four-contributor DNA mixtures and the impact of replicates. Forensic Sci Int Genet 2019; 41:24-31. [DOI: 10.1016/j.fsigen.2019.03.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 03/19/2019] [Accepted: 03/20/2019] [Indexed: 12/24/2022]
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Buckleton JS, Bright JA, Gittelson S, Moretti TR, Onorato AJ, Bieber FR, Budowle B, Taylor DA. The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity. J Forensic Sci 2018; 64:393-405. [PMID: 30132900 DOI: 10.1111/1556-4029.13898] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 07/14/2018] [Accepted: 07/17/2018] [Indexed: 01/08/2023]
Abstract
Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decision-making toward computer-based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG). Decision-making by laboratories to implement probability-based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. The principles behind STRmix™ are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights. All PG methods generate a likelihood ratio (LR) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG, and in particular, STRmix™. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STRmix™, one of the available PG software.
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Affiliation(s)
- John S Buckleton
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142, New Zealand.,Department of Statistics, University of Auckland, Private Bag 92019, Auckland, New Zealand
| | - Jo-Anne Bright
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142, New Zealand
| | - Simone Gittelson
- Centre for Forensic Science, University of Technology Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia
| | - Tamyra R Moretti
- DNA Support Unit, Federal Bureau of Investigation Laboratory, 2501 Investigation Parkway, Quantico, VA, 22135
| | - Anthony J Onorato
- DNA Support Unit, Federal Bureau of Investigation Laboratory, 2501 Investigation Parkway, Quantico, VA, 22135
| | - Frederick R Bieber
- Center for Advanced Molecular Diagnostics, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115
| | - Bruce Budowle
- Center for Human Identification, Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107
| | - Duncan A Taylor
- Forensic Science South Australia, 21 Divett Place, Adelaide, SA, Australia.,Flinders University - School of Biology, Stuart Road, Bedford Park, Adelaide, SA, Australia
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Gill P, Hicks T, Butler JM, Connolly E, Gusmão L, Kokshoorn B, Morling N, van Oorschot RAH, Parson W, Prinz M, Schneider PM, Sijen T, Taylor D. DNA commission of the International society for forensic genetics: Assessing the value of forensic biological evidence - Guidelines highlighting the importance of propositions: Part I: evaluation of DNA profiling comparisons given (sub-) source propositions. Forensic Sci Int Genet 2018; 36:189-202. [PMID: 30041098 DOI: 10.1016/j.fsigen.2018.07.003] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 07/02/2018] [Indexed: 01/23/2023]
Abstract
The interpretation of evidence continues to be one of the biggest challenges facing the forensic community. This is the first of two papers intended to provide advice on difficult aspects of evaluation and in particular on the formulation of propositions. The scientist has a dual role: investigator (crime-focused), where often there is no suspect available and a database search may be required; evaluator (suspect-focused), where the strength of evidence is assessed in the context of the case. In investigative mode, generally the aim is to produce leads regarding the source of the DNA. Sub-source level propositions will be adequate to help identify potential suspects who can be further investigated by the authorities. Once in evaluative mode, given the defence version of events of the person of interest, it may become necessary to consider alternatives that go beyond the source of the DNA (i.e., to consider activity level propositions). In the evaluation phase, it is crucial that formulation of propositions allows the assessment of all the results that will help with the issue at hand. Propositions should therefore be precise (indication of the number of contributors, information on the relevant population etc.), be about causes, not effects (e.g. a 'matching' DNA profile) and to avoid bias, must not be findings-led. This means that ideally, propositions should be decided based on the case information and before the results of the comparisons are known. This paper primarily reflects upon what has been coined as "sub-source level propositions". These are restricted to the evaluation of the DNA profiles themselves, and help answer the issue regarding the source of the DNA. It is to be emphasised that likelihood ratios given sub-source level propositions cannot be carried over to a different level - for example, activity level propositions, where the DNA evidence is put into the context of the alleged activities. This would be highly misleading and could give rise to miscarriages of justice; this will be discussed in a second paper. The value of forensic results depends not only on propositions, but also on the type of results (e.g. allelic designations, peak heights, replicates) and upon the model used: it is therefore important to discuss these aspects. Finally, since communication is key to help understanding by courts, we will explore how to convey the value of the results and explain the importance of avoiding the practice of transposing the conditional.
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Affiliation(s)
- Peter Gill
- Oslo University Hospital, Oslo, Norway; University of Oslo, Oslo, Norway.
| | - Tacha Hicks
- Faculty of Law, Criminal Justice and Public Administration, School of Criminal Justice, University of Lausanne, Lausanne, Switzerland; Fondation pour la formation continue Universitaire Lausannoise (UNIL-EPFL), 1015 Dorigny, Switzerland.
| | - John M Butler
- National Institute of Standards and Technology, Special Programs Office, Gaithersburg, MD, USA
| | - Ed Connolly
- Forensic Science Ireland, Garda HQ, Phoenix Park, Dublin 8, D08 HN3X, Ireland
| | - Leonor Gusmão
- State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil; IPATIMUP, Institute of Molecular Pathology and Immunology of the University of Porto, Portugal; Instituto de Investigação e Inovação em Saúde, University of Porto, Portugal
| | - Bas Kokshoorn
- Netherlands Forensic Institute, Division Biological Traces, P.O. Box 24044, 2490 AA The Hague, The Netherlands
| | - Niels Morling
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Roland A H van Oorschot
- Office of the Chief Forensic Scientist, Victoria Police Forensic Service Centre, Macleod, VIC 3085, Australia; School of Molecular Sciences, La Trobe University, Bundoora, VIC 3086, Australia
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, PA, USA
| | | | - Peter M Schneider
- Institute of Legal Medicine, Faculty of Medicine, University of Cologne, Germany
| | - Titia Sijen
- Netherlands Forensic Institute, Division Biological Traces, P.O. Box 24044, 2490 AA The Hague, The Netherlands
| | - Duncan Taylor
- Forensic Science South Australia, 21 Divett Place, Adelaide, SA 5000, Australia; School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, SA, 5001, Australia
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11
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Just RS, Irwin JA. Use of the LUS in sequence allele designations to facilitate probabilistic genotyping of NGS-based STR typing results. Forensic Sci Int Genet 2018. [DOI: 10.1016/j.fsigen.2018.02.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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12
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Gittelson S, Moretti TR, Onorato AJ, Budowle B, Weir BS, Buckleton J. The factor of 10 in forensic DNA match probabilities. Forensic Sci Int Genet 2017; 28:178-187. [PMID: 28273509 DOI: 10.1016/j.fsigen.2017.02.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 02/09/2017] [Accepted: 02/13/2017] [Indexed: 10/20/2022]
Abstract
An update was performed of the classic experiments that led to the view that profile probability assignments are usually within a factor of 10 of each other. The data used in this study consist of 15 Identifiler loci collected from a wide range of forensic populations. Following Budowle et al. [1], the terms cognate and non-cognate are used. The cognate database is the database from which the profiles are simulated. The profile probability assignment was usually larger in the cognate database. In 44%-65% of the cases, the profile probability for 15 loci in the non-cognate database was within a factor of 10 of the profile probability in the cognate database. This proportion was between 60% and 80% when the FBI and NIST data were used as the non-cognate databases. A second experiment compared the match probability assignment using a generalised database and recommendation 4.2 from NRC II (the 4.2 assignment) with a proxy for the matching proportion developed using subpopulation allele frequencies and the product rule. The findings support that the 4.2 assignment has a large conservative bias. These results are in agreement with previous research results.
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Affiliation(s)
- Simone Gittelson
- National Institute of Standards and Technology, 100 Bureau Drive, MS 8980 Gaithersburg, MD 20899, USA.
| | - Tamyra R Moretti
- DNA Support Unit, Federal Bureau of Investigation Laboratory, 2501 Investigation Parkway, Quantico, VA 22135, USA
| | - Anthony J Onorato
- DNA Support Unit, Federal Bureau of Investigation Laboratory, 2501 Investigation Parkway, Quantico, VA 22135, USA
| | - Bruce Budowle
- Center for Human Identification, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX 76107, USA; Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Bruce S Weir
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - John Buckleton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; ESR Ltd, Private Bag 92021, Auckland 1142, New Zealand
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13
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Coble M, Buckleton J, Butler J, Egeland T, Fimmers R, Gill P, Gusmão L, Guttman B, Krawczak M, Morling N, Parson W, Pinto N, Schneider P, Sherry S, Willuweit S, Prinz M. DNA Commission of the International Society for Forensic Genetics: Recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications. Forensic Sci Int Genet 2016; 25:191-197. [DOI: 10.1016/j.fsigen.2016.09.002] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Accepted: 09/02/2016] [Indexed: 10/21/2022]
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de Zoete J, Oosterman W, Kokshoorn B, Sjerps M. Cell type determination and association with the DNA donor. Forensic Sci Int Genet 2016; 25:97-111. [PMID: 27552692 DOI: 10.1016/j.fsigen.2016.08.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2016] [Revised: 06/07/2016] [Accepted: 08/09/2016] [Indexed: 11/18/2022]
Abstract
In forensic casework, evidence regarding the type of cell material contained in a stain can be crucial in determining what happened. For example, a DNA match in a sexual offense can become substantially more incriminating when there is evidence supporting that semen cells are present. Besides the question which cell types are present in a sample, also the question who donated what (association) is very relevant. This question is surprisingly difficult, even for stains with a single donor. The evidential value of a DNA profile needs to be combined with knowledge regarding the specificity and sensitivity of cell type tests. This, together with prior probabilities for the different donor-cell type combinations, determines the most likely combination. We present a Bayesian network that can assist in associating donors and cell types. A literature overview on the sensitivity and specificity of three cell type tests (PSA test for seminal fluid, RSID saliva and RSID semen) is helpful in assigning conditional probabilities. The Bayesian network is linked with a software package for interpreting mixed DNA profiles. This allows for a sensitivity analysis that shows to what extent the conclusion depends on the quantity of available research data. This can aid in making decisions regarding further research. It is shown that the common assumption that an individual (e.g. the victim) is one of the donors in a mixed DNA profile can have unwanted consequences for the association between donors and cell types.
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Affiliation(s)
- Jacob de Zoete
- University of Amsterdam, Korteweg de Vries Instituut voor Wiskunde, Postbus 94248, 1090 GE Amsterdam, The Netherlands.
| | - Wessel Oosterman
- University of Amsterdam, Korteweg de Vries Instituut voor Wiskunde, Postbus 94248, 1090 GE Amsterdam, The Netherlands.
| | - Bas Kokshoorn
- Netherlands Forensic Institute, Laan van Ypenburg 6, 2497 GB Den Haag, The Netherlands(1).
| | - Marjan Sjerps
- Netherlands Forensic Institute, Laan van Ypenburg 6, 2497 GB Den Haag, The Netherlands(1).
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15
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Validating multiplexes for use in conjunction with modern interpretation strategies. Forensic Sci Int Genet 2016; 20:6-19. [DOI: 10.1016/j.fsigen.2015.09.011] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2015] [Revised: 09/21/2015] [Accepted: 09/22/2015] [Indexed: 11/18/2022]
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16
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Gill P, Haned H, Bleka O, Hansson O, Dørum G, Egeland T. Genotyping and interpretation of STR-DNA: Low-template, mixtures and database matches-Twenty years of research and development. Forensic Sci Int Genet 2015; 18:100-17. [PMID: 25866376 DOI: 10.1016/j.fsigen.2015.03.014] [Citation(s) in RCA: 99] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2014] [Revised: 03/19/2015] [Accepted: 03/24/2015] [Indexed: 12/17/2022]
Abstract
The introduction of Short Tandem Repeat (STR) DNA was a revolution within a revolution that transformed forensic DNA profiling into a tool that could be used, for the first time, to create National DNA databases. This transformation would not have been possible without the concurrent development of fluorescent automated sequencers, combined with the ability to multiplex several loci together. Use of the polymerase chain reaction (PCR) increased the sensitivity of the method to enable the analysis of a handful of cells. The first multiplexes were simple: 'the quad', introduced by the defunct UK Forensic Science Service (FSS) in 1994, rapidly followed by a more discriminating 'six-plex' (Second Generation Multiplex) in 1995 that was used to create the world's first national DNA database. The success of the database rapidly outgrew the functionality of the original system - by the year 2000 a new multiplex of ten-loci was introduced to reduce the chance of adventitious matches. The technology was adopted world-wide, albeit with different loci. The political requirement to introduce pan-European databases encouraged standardisation - the development of European Standard Set (ESS) of markers comprising twelve-loci is the latest iteration. Although development has been impressive, the methods used to interpret evidence have lagged behind. For example, the theory to interpret complex DNA profiles (low-level mixtures), had been developed fifteen years ago, but only in the past year or so, are the concepts starting to be widely adopted. A plethora of different models (some commercial and others non-commercial) have appeared. This has led to a confusing 'debate' about the 'best' to use. The different models available are described along with their advantages and disadvantages. A section discusses the development of national DNA databases, along with details of an associated controversy to estimate the strength of evidence of matches. Current methodology is limited to searches of complete profiles - another example where the interpretation of matches has not kept pace with development of theory. STRs have also transformed the area of Disaster Victim Identification (DVI) which frequently requires kinship analysis. However, genotyping efficiency is complicated by complex, degraded DNA profiles. Finally, there is now a detailed understanding of the causes of stochastic effects that cause DNA profiles to exhibit the phenomena of drop-out and drop-in, along with artefacts such as stutters. The phenomena discussed include: heterozygote balance; stutter; degradation; the effect of decreasing quantities of DNA; the dilution effect.
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Affiliation(s)
- Peter Gill
- Norwegian Institute of Public Health, Department of Forensic Biology, PO Box 4404 Nydalen, 0403 Oslo, Norway; Department of Forensic Medicine, Sognsvannsveien 20, Rikshospitalet, 0372 Oslo, Norway.
| | - Hinda Haned
- Netherlands Forensic Institute, Department of Human Biological Traces, The Hague, The Netherlands
| | - Oyvind Bleka
- Norwegian Institute of Public Health, Department of Forensic Biology, PO Box 4404 Nydalen, 0403 Oslo, Norway
| | - Oskar Hansson
- Norwegian Institute of Public Health, Department of Forensic Biology, PO Box 4404 Nydalen, 0403 Oslo, Norway
| | - Guro Dørum
- Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway
| | - Thore Egeland
- Norwegian Institute of Public Health, Department of Forensic Biology, PO Box 4404 Nydalen, 0403 Oslo, Norway; Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway
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17
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Cowell RG, Graversen T, Lauritzen SL, Mortera J. Analysis of forensic DNA mixtures with artefacts. J R Stat Soc Ser C Appl Stat 2014. [DOI: 10.1111/rssc.12071] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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18
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Haned H, Benschop CCG, Gill PD, Sijen T. Complex DNA mixture analysis in a forensic context: evaluating the probative value using a likelihood ratio model. Forensic Sci Int Genet 2014; 16:17-25. [PMID: 25485478 DOI: 10.1016/j.fsigen.2014.11.014] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 11/14/2014] [Accepted: 11/16/2014] [Indexed: 12/01/2022]
Abstract
The interpretation of mixed DNA profiles obtained from low template DNA samples has proven to be a particularly difficult task in forensic casework. Newly developed likelihood ratio (LR) models that account for PCR-related stochastic effects, such as allelic drop-out, drop-in and stutters, have enabled the analysis of complex cases that would otherwise have been reported as inconclusive. In such samples, there are uncertainties about the number of contributors, and the correct sets of propositions to consider. Using experimental samples, where the genotypes of the donors are known, we evaluated the feasibility and the relevance of the interpretation of high order mixtures, of three, four and five donors. The relative risks of analyzing high order mixtures of three, four, and five donors, were established by comparison of a 'gold standard' LR, to the LR that would be obtained in casework. The 'gold standard' LR is the ideal LR: since the genotypes and number of contributors are known, it follows that the parameters needed to compute the LR can be determined per contributor. The 'casework LR' was calculated as used in standard practice, where unknown donors are assumed; the parameters were estimated from the available data. Both LRs were calculated using the basic standard model, also termed the drop-out/drop-in model, implemented in the LRmix module of the R package Forensim. We show how our results furthered the understanding of the relevance of analyzing high order mixtures in a forensic context. Limitations are highlighted, and it is illustrated how our study serves as a guide to implement likelihood ratio interpretation of complex DNA profiles in forensic casework.
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Affiliation(s)
- Hinda Haned
- Department of Human Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands.
| | - Corina C G Benschop
- Department of Human Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands.
| | - Peter D Gill
- National Institute of Public Health, Department of Forensic Biology, P.O. Box 4404 Nydalen, 0403 Oslo, Norway; National Institute of Public Health, Department of Forensic Medicine, P.O. Box 4950 Nydalen, 0424 Oslo, Norway.
| | - Titia Sijen
- Department of Human Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands.
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