The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity |
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| Authors: | John S Buckleton DSc Simone Gittelson PhD Tamyra R Moretti PhD Anthony J Onorato MCIM MSFS Frederick R Bieber PhD Bruce Budowle PhD Duncan A Taylor PhD |
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| Institution: | 1. Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142 New Zealand;2. Department of Statistics, University of Auckland, Private Bag 92019, Auckland, New ZealandJSB and JB were supported in part by Grant Number 2011‐DN‐BX‐K541 from the US National Institute of Justice.Corresponding author: John S. Buckleton, D.Sc. E‐mail:;3. Centre for Forensic Science, University of Technology Sydney, P.O. Box 4. 123, Broadway, NSW, 2007 Australia;5. DNA Support Unit, Federal Bureau of Investigation Laboratory, 2501 Investigation Parkway, Quantico, VA, 22135;6. Center for Advanced Molecular Diagnostics, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115;7. 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;8. Forensic Science South Australia, 21 Divett Place, Adelaide, SA, Australia;9. Flinders University – School of Biology, Stuart Road, Bedford Park, Adelaide, SA, Australia |
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| 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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| Keywords: | forensic science
DNA
probabilistic genotyping validation STRmix™ |
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