Literature DB >> 30665115

STRmix™ collaborative exercise on DNA mixture interpretation.

Jo-Anne Bright1, Kevin Cheng2, Zane Kerr2, Catherine McGovern2, Hannah Kelly2, Tamyra R Moretti3, Michael A Smith3, Frederick R Bieber4, Bruce Budowle5, Michael D Coble5, Rashed Alghafri6, Paul Stafford Allen7, Amy Barber8, Vickie Beamer9, Christina Buettner10, Melanie Russell11, Christian Gehrig12, Tacha Hicks13, Jessica Charak14, Kate Cheong-Wing15, Anne Ciecko16, Christie T Davis17, Michael Donley18, Natalie Pedersen19, Bill Gartside20, Dominic Granger21, MaryMargaret Greer-Ritzheimer22, Erick Reisinger23, Jarrah Kennedy24, Erin Grammer25, Marla Kaplan26, David Hansen27, Hans J Larsen28, Alanna Laureano29, Christina Li30, Eugene Lien31, Emilia Lindberg32, Ciara Kelly33, Ben Mallinder34, Simon Malsom35, Alyse Yacovone-Margetts36, Andrew McWhorter37, Sapana M Prajapati38, Tamar Powell39, Gary Shutler40, Kate Stevenson2, April R Stonehouse41, Lindsey Smith42, Julie Murakami43, Eric Halsing44, Darren Wright45, Leigh Clark46, Duncan A Taylor47, John Buckleton48.   

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 × 104 to 8 × 106. For Sample 2 (in the order of 2000 rfu for major contributors), LRs ranged from 2 × 1028 to 2 × 1029. Where LRs were calculated, the differences between participants can be attributed to (from largest to smallest impact): 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.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Forensic DNA interpretation; Inter-laboratory study; Intra-laboratory study; Probabilistic genotyping; STRmix

Mesh:

Substances:

Year:  2019        PMID: 30665115     DOI: 10.1016/j.fsigen.2019.01.006

Source DB:  PubMed          Journal:  Forensic Sci Int Genet        ISSN: 1872-4973            Impact factor:   4.882


  7 in total

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Authors:  John M Butler; Sheila Willis
Journal:  Forensic Sci Int       Date:  2020-02-20       Impact factor: 2.395

3.  Uncertainty in estimating the number of contributors from simulated DNA mixture profiles, with and without allele dropout, from Chinese, Malay, Indian, and Caucasian ethnic populations.

Authors:  Kevin Wai Yin Chong; Christopher Kiu-Choong Syn
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.996

Review 4.  A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™.

Authors:  Peter Gill; Corina Benschop; John Buckleton; Øyvind Bleka; Duncan Taylor
Journal:  Genes (Basel)       Date:  2021-09-30       Impact factor: 4.096

Review 5.  On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime.

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Journal:  Genes (Basel)       Date:  2021-10-28       Impact factor: 4.096

Review 6.  A practical tool for information management in forensic decisions: Using Linear Sequential Unmasking-Expanded (LSU-E) in casework.

Authors:  Adele Quigley-McBride; Itiel E Dror; Tiffany Roy; Brandon L Garrett; Jeff Kukucka
Journal:  Forensic Sci Int Synerg       Date:  2022-02-20

7.  Pushing the Boundaries: Forensic DNA Phenotyping Challenged by Single-Cell Sequencing.

Authors:  Marta Diepenbroek; Birgit Bayer; Katja Anslinger
Journal:  Genes (Basel)       Date:  2021-08-30       Impact factor: 4.096

  7 in total

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