Addressing uncertain assumptions in DNA evidence evaluation

Maarten Kruijver, Hannah Kelly, Duncan Taylor, John Buckleton

Research output: Contribution to journalArticlepeer-review


Evidential value of DNA mixtures is typically expressed by a likelihood ratio. However, selecting appropriate propositions can be contentious, because assumptions may need to be made around, for example, the contribution of a complainant's profile, or relatedness between contributors. A choice made one way or another disregards any uncertainty that may be present about such an assumption. To address this, a complex proposition that considers multiple sub-propositions with different assumptions may be more appropriate. While the use of complex propositions has been advocated in the literature, the uptake in casework has been limited. We provide a mathematical framework for evaluating DNA evidence given complex propositions and discuss its implementation in the DBLR™ software. The software simultaneously handles multiple mixed samples, reference profiles and relationships as described by a pedigree, which unlocks a variety of applications. We provide several examples to illustrate how complex propositions can efficiently evaluate DNA evidence. The addition of this feature to DBLR™ provides a tool to approach the long-accepted, but often impractical suggestion that propositions should be exhaustive within a case context.

Original languageEnglish
Article number102913
Number of pages10
JournalForensic Science International: Genetics
Early online date11 Jul 2023
Publication statusPublished - Sept 2023


  • DBLR
  • Forensic DNA
  • Probabilistic genotyping
  • Propositions
  • STRmix™


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