Analysis of the Hamiltonian Monte Carlo genotyping algorithm on PROVEDIt mixtures including a novel precision benchmark

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

We provide an internal validation study of a recently published precise DNA mixture algorithm based on Hamiltonian Monte Carlo sampling (Susik et al., 2022). We provide results for all 428 mixtures analysed by Riman et al. (2021) and compare the results with two state-of-the-art software products: STRmix™ v2.6 and Euroformix v3.4.0. The comparison shows that the Hamiltonian Monte Carlo method provides reliable values of likelihood ratios (LRs) close to the other methods. We further propose a novel large-scale precision benchmark and quantify the precision of the Hamiltonian Monte Carlo method, indicating its improvements over existing solutions. Finally, we analyse the influence of the factors discussed by Buckleton et al. (2022).

Details

Original languageEnglish
Article number102840
Number of pages13
JournalForensic Science International: Genetics
Volume64 (2023)
Early online date1 Feb 2023
Publication statusPublished - May 2023
Peer-reviewedYes

External IDs

PubMed 36764220
ORCID /0000-0003-4414-4340/work/159608273

Keywords

Keywords

  • DNA mixtures, HMC, Probabilistic genotyping, Validation

Library keywords