Literature DB >> 30851600

Inter-sample contamination detection using mixture deconvolution comparison.

Duncan Taylor1, Emily Rowe2, Maarten Kruijver3, Damien Abarno4, Jo-Anne Bright3, John Buckleton5.   

Abstract

A recent publication has provided the ability to compare two mixed DNA profiles and consider their probability of occurrence if they do, compared to if they do not, have a common contributor. This ability has applications to both quality assurance (to test for sample to sample contamination) and for intelligence gathering purposes (did the same unknown offender donate DNA to multiple samples). We use a mixture to mixture comparison tool to investigate the prevalence of sample to sample contamination that could occur from two laboratory mechanisms, one during DNA extraction and one during electrophoresis. By carrying out pairwise comparisons of all samples (deconvoluted using probabilistic genotyping software STRmix™) within extraction or run batches we identify any potential common DNA donors and investigate these with respect to their risk of contamination from the two proposed mechanisms. While not identifying any contamination, we inadvertently find a potential intelligence link between samples, showing the use of a mixture to mixture comparison tool for investigative purposes.
Copyright © 2019 Elsevier B.V. All rights reserved.

Keywords:  Contamination; Deconvolution; Extraction batch; Mixture comparison

Mesh:

Substances:

Year:  2019        PMID: 30851600     DOI: 10.1016/j.fsigen.2019.02.021

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


  2 in total

Review 1.  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

2.  Human DNA contamination of postmortem examination facilities: Impact of COVID-19 cleaning procedure.

Authors:  Carla Bini; Arianna Giorgetti; Elena Giovannini; Guido Pelletti; Paolo Fais; Susi Pelotti
Journal:  J Forensic Sci       Date:  2022-07-18       Impact factor: 1.717

  2 in total

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