STRmix™ collaborative exercise on DNA mixture interpretation

Jo Anne Bright, Kevin Cheng, Zane Kerr, Catherine McGovern, Hannah Kelly, Tamyra R. Moretti, Michael A. Smith, Frederick R. Bieber, Bruce Budowle, Michael D. Coble, Rashed Alghafri, Paul Stafford Allen, Amy Barber, Vickie Beamer, Christina Buettner, Melanie Russell, Christian Gehrig, Tacha Hicks, Jessica Charak, Kate Cheong-WingAnne Ciecko, Christie T. Davis, Michael Donley, Natalie Pedersen, Bill Gartside, Dominic Granger, Mary Margaret Greer-Ritzheimer, Erick Reisinger, Jarrah Kennedy, Erin Grammer, Marla Kaplan, David Hansen, Hans J. Larsen, Alanna Laureano, Christina Li, Eugene Lien, Emilia Lindberg, Ciara Kelly, Ben Mallinder, Simon Malsom, Alyse Yacovone-Margetts, Andrew McWhorter, Sapana M. Prajapati, Tamar Powell, Gary Shutler, Kate Stevenson, April R. Stonehouse, Lindsey Smith, Julie Murakami, Eric Halsing, Darren Wright, Leigh Clark, Duncan A. Taylor, John Buckleton

    Research output: Contribution to journalArticle

    7 Citations (Scopus)

    Abstract

    An intra and inter-laboratory study using the probabilistic genotyping (PG) software STRmix™ is reported. Two complex mixtures from the PROVEDIt set, analysed on an Applied Biosystems™ 3500 Series Genetic Analyzer, were selected. 174 participants responded. For Sample 1 (low template, in the order of 200 rfu for major contributors) five participants described the comparison as inconclusive with respect to the POI or excluded him. Where LRs were assigned, the point estimates ranging from 2 × 10 4 to 8 × 10 6 . For Sample 2 (in the order of 2000 rfu for major contributors), LRs ranged from 2 × 10 28 to 2 × 10 29 . Where LRs were calculated, the differences between participants can be attributed to (from largest to smallest impact): • varying number of contributors (NoC), • the exclusion of some loci within the interpretation, • differences in local CE data analysis methods leading to variation in the peaks present and their heights in the input files used, • and run-to-run variation due to the random sampling inherent to all MCMC-based methods. This study demonstrates a high level of repeatability and reproducibility among the participants. For those results that differed from the mode, the differences in LR were almost always minor or conservative.

    Original languageEnglish
    Pages (from-to)1-8
    Number of pages8
    JournalForensic Science International: Genetics
    Volume40
    DOIs
    Publication statusPublished - May 2019

    Keywords

    • Forensic DNA interpretation
    • Inter-laboratory study
    • Intra-laboratory study
    • Probabilistic genotyping
    • STRmix

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    Bright, J. A., Cheng, K., Kerr, Z., McGovern, C., Kelly, H., Moretti, T. R., Smith, M. A., Bieber, F. R., Budowle, B., Coble, M. D., Alghafri, R., Allen, P. S., Barber, A., Beamer, V., Buettner, C., Russell, M., Gehrig, C., Hicks, T., Charak, J., ... Buckleton, J. (2019). STRmix™ collaborative exercise on DNA mixture interpretation. Forensic Science International: Genetics, 40, 1-8. https://doi.org/10.1016/j.fsigen.2019.01.006