Inter-sample contamination detection using mixture deconvolution comparison

Duncan Taylor, Emily Rowe, Maarten Kruijver, Damien Abarno, Jo Anne Bright, John Buckleton

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)160-167
Number of pages8
JournalForensic Science International: Genetics
Volume40
DOIs
Publication statusPublished - 1 May 2019

Keywords

  • Contamination
  • Deconvolution
  • Extraction batch
  • Mixture comparison

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