| Literature DB >> 30132900 |
John S Buckleton1,2, Jo-Anne Bright1, Simone Gittelson3, Tamyra R Moretti4, Anthony J Onorato4, Frederick R Bieber5, Bruce Budowle6, Duncan A Taylor7,8.
Abstract
Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decision-making toward computer-based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG). Decision-making by laboratories to implement probability-based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. The principles behind STRmix™ are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights. All PG methods generate a likelihood ratio (LR) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG, and in particular, STRmix™. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STRmix™, one of the available PG software.Entities:
Keywords: zzm321990DNAzzm321990; STRmix™; forensic science; probabilistic genotyping; validation
Mesh:
Year: 2018 PMID: 30132900 DOI: 10.1111/1556-4029.13898
Source DB: PubMed Journal: J Forensic Sci ISSN: 0022-1198 Impact factor: 1.832