分析包括新精度基准在内的 PROVEDIt 混合物中的哈密顿蒙特卡罗基因分型算法。
Analysis of the Hamiltonian Monte Carlo genotyping algorithm on PROVEDIt mixtures including a novel precision benchmark.
机构信息
Biotype GmbH, Dresden, 01109, Germany; Technische Universität Dresden, Faculty of Computer Science, Dresden, 01187, Germany.
Technische Universität Dresden, Faculty of Computer Science, Dresden, 01187, Germany; Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, 01307, Germany; Center for Systems Biology Dresden, Dresden, 01307, Germany.
出版信息
Forensic Sci Int Genet. 2023 May;64:102840. doi: 10.1016/j.fsigen.2023.102840. Epub 2023 Feb 1.
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).
我们对最近发表的一种基于哈密顿蒙特卡罗抽样的精确 DNA 混合物算法（Susik 等人，2022）进行了内部验证研究。我们提供了 Riman 等人（2021）分析的所有 428 种混合物的结果，并将结果与两种最先进的软件产品进行了比较：STRmix™ v2.6 和 Euroformix v3.4.0。比较表明，哈密顿蒙特卡罗方法提供了可靠的似然比（LR）值，接近其他方法。我们进一步提出了一种新的大规模精度基准，并量化了哈密顿蒙特卡罗方法的精度，表明其优于现有解决方案。最后，我们分析了 Buckleton 等人（2022）讨论的因素的影响。
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